Develop Reference

How to diagnose a conda install that forces downgrade of other packages?

I tried to use Anaconda to install Pandas. However, as part of doing so, conda forcibly downgraded other unrelated packages, such as TensorFlow and Numpy. Pandas eventually installed with version 1.2.4.
I don't want these other packages to be downgraded. How do I diagnose this problem? Is the problem with Pandas, conda, or the conda package server?
> conda install pandas
The following packages will be downloaded:
package | build
---------------------------|-----------------
h5py-2.10.0 | py39hec9cf62_0 1.1 MB
intel-openmp-2020.2 | 254 947 KB
mkl-2020.2 | 256 213.9 MB
mkl-service-2.3.0 | py39he8ac12f_0 58 KB
mkl_fft-1.3.0 | py39h54f3939_0 195 KB
mkl_random-1.0.2 | py39h63df603_0 379 KB
numpy-1.19.2 | py39h89c1606_0 21 KB
numpy-base-1.19.2 | py39h2ae0177_0 5.3 MB
pandas-1.2.4 | py39h2531618_0 11.4 MB
python-dateutil-2.8.2 | pyhd3eb1b0_0 241 KB
pytz-2021.1 | pyhd3eb1b0_0 244 KB
scipy-1.6.2 | py39h91f5cce_0 20.6 MB
tensorflow-2.4.1 |mkl_py39h4683426_0 3 KB
tensorflow-base-2.4.1 |mkl_py39h43e0292_0 125.5 MB
------------------------------------------------------------
Total: 379.7 MB
The following NEW packages will be INSTALLED:
pandas pkgs/main/linux-64::pandas-1.2.4-py39h2531618_0
python-dateutil pkgs/main/noarch::python-dateutil-2.8.2-pyhd3eb1b0_0
pytz pkgs/main/noarch::pytz-2021.1-pyhd3eb1b0_0
The following packages will be DOWNGRADED:
h5py 3.2.1-py39h6c542dc_0 --> 2.10.0-py39hec9cf62_0
intel-openmp 2021.3.0-h06a4308_3350 --> 2020.2-254
mkl 2021.3.0-h06a4308_520 --> 2020.2-256
mkl-service 2.4.0-py39h7f8727e_0 --> 2.3.0-py39he8ac12f_0
mkl_fft 1.3.0-py39h42c9631_2 --> 1.3.0-py39h54f3939_0
mkl_random 1.2.2-py39h51133e4_0 --> 1.0.2-py39h63df603_0
numpy 1.20.3-py39hf144106_0 --> 1.19.2-py39h89c1606_0
numpy-base 1.20.3-py39h74d4b33_0 --> 1.19.2-py39h2ae0177_0
scipy 1.6.2-py39had2a1c9_1 --> 1.6.2-py39h91f5cce_0
tensorflow 2.5.0-mkl_py39h4a0693c_0 --> 2.4.1-mkl_py39h4683426_0
tensorflow-base 2.5.0-mkl_py39h35b2a3d_0 --> 2.4.1-mkl_py39h43e0292_0
Proceed ([y]/n)?

Updating conda environment from file offline

I am successfully creating a Conda environment from the environment.yml file. The problem is when I decide to add a new dependency on the environment and I want to update it offline. I modified the environment.yml file and tried this:
conda env update --file environment.yml
But the result is:
Collecting package metadata (repodata.json): done
Solving environment: done
Downloading and Extracting Packages
cffi-1.14.2 | 227 KB | ################################################################################################################################# | 100%
setuptools-49.6.0 | 748 KB | ################################################################################################################################# | 100%
cryptography-3.0 | 573 KB | ################################################################################################################################# | 100%
pip-20.2.2 | 1.7 MB | ################################################################################################################################# | 100%
selenium-3.141.0 | 820 KB | ################################################################################################################################# | 100%
python-3.8.5 | 49.3 MB | #########################################################################1 | 57% python-3.8.5 | 49.3 MB | #########################################################################7 | 57%
CondaSignalInterrupt: Signal interrupt SIGINT
It downloaded python-3.8.5, which should not happen since I already have it on my base environment. However, if I tried:
conda env update --file environment.yml --offline
It results on:
usage: conda-env [-h] {create,export,list,remove,update,config} ...
conda-env: error: unrecognized arguments: --offline
After I read the manual, there is no --use-index-cache either. Currently I found a way to work around this by removing and creating the environment again. Any idea how to solve this?

conda install packages without upgrading python [duplicate]

I had been using Anaconda with python 2.7
$ python
Python 2.7.14 |Anaconda custom (64-bit)| (default, Dec 7 2017, 17:05:42)
[GCC 7.2.0] on linux2
Type "help", "copyright", "credits" or "license" for more information.
When I decided to install tensorflow (since for some reason I had the non-gpu version)
The command I used was:
$ conda install -c anaconda tensorflow-gpu
However, after it was done (detail on output of this cmd to follow), I no longer had conda:
$ conda install -c conda-forge keras
Traceback (most recent call last):
File "/home/me/anaconda2/bin/conda", line 12, in <module>
from conda.cli import main
ModuleNotFoundError: No module named 'conda'
(Note: I also no longer had Keras) and was now running Python 3.7(!?):
$ python
Python 3.6.8 |Anaconda, Inc.| (default, Dec 30 2018, 01:22:34)
[GCC 7.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>>
What happened? How do I stop it from happening again? This happened once before and I ended up deleting all my anaconda files, then reinstalling. I don't want to make that a habit.
The output of my conda install was:
$ conda install -c anaconda tensorflow-gpu
Collecting package metadata: done
Solving environment: done
## Package Plan ##
environment location: /home/me/anaconda2
added / updated specs:
- tensorflow-gpu
The following packages will be downloaded:
package | build
---------------------------|-----------------
_tflow_190_select-0.0.1 | gpu 2 KB anaconda
absl-py-0.7.0 | py36_0 156 KB anaconda
astor-0.7.1 | py36_0 43 KB anaconda
c-ares-1.15.0 | h7b6447c_1 98 KB anaconda
ca-certificates-2018.12.5 | 0 123 KB anaconda
certifi-2018.11.29 | py36_0 146 KB anaconda
cudatoolkit-9.0 | h13b8566_0 340.4 MB anaconda
cudnn-7.1.2 | cuda9.0_0 367.8 MB anaconda
cupti-9.0.176 | 0 1.6 MB anaconda
curl-7.63.0 | hbc83047_1000 145 KB anaconda
gast-0.2.2 | py36_0 138 KB anaconda
git-2.11.1 | 0 9.5 MB anaconda
grpcio-1.16.1 | py36hf8bcb03_1 1.1 MB anaconda
krb5-1.16.1 | h173b8e3_7 1.4 MB anaconda
libcurl-7.63.0 | h20c2e04_1000 550 KB anaconda
libedit-3.1.20181209 | hc058e9b_0 188 KB anaconda
libssh2-1.8.0 | h1ba5d50_4 233 KB anaconda
markdown-3.0.1 | py36_0 107 KB anaconda
mkl_fft-1.0.10 | py36ha843d7b_0 170 KB anaconda
mkl_random-1.0.2 | py36hd81dba3_0 407 KB anaconda
ncurses-6.1 | he6710b0_1 958 KB anaconda
numpy-1.15.4 | py36h7e9f1db_0 47 KB anaconda
numpy-base-1.15.4 | py36hde5b4d6_0 4.3 MB anaconda
openssl-1.1.1 | h7b6447c_0 5.0 MB anaconda
pip-18.1 | py36_0 1.8 MB anaconda
protobuf-3.5.2 | py36hf484d3e_1 610 KB anaconda
python-3.6.8 | h0371630_0 34.4 MB anaconda
qt-4.8.7 | 2 34.1 MB anaconda
setuptools-40.6.3 | py36_0 625 KB anaconda
six-1.12.0 | py36_0 22 KB anaconda
sqlite-3.26.0 | h7b6447c_0 1.9 MB anaconda
tensorboard-1.9.0 | py36hf484d3e_0 3.3 MB anaconda
tensorflow-1.9.0 |gpu_py36h02c5d5e_1 3 KB anaconda
tensorflow-base-1.9.0 |gpu_py36h6ecc378_0 170.8 MB anaconda
tensorflow-gpu-1.9.0 | hf154084_0 2 KB anaconda
termcolor-1.1.0 | py36_1 7 KB anaconda
tk-8.6.8 | hbc83047_0 3.1 MB anaconda
werkzeug-0.14.1 | py36_0 423 KB anaconda
wheel-0.32.3 | py36_0 35 KB anaconda
------------------------------------------------------------
Total: 985.7 MB
The following NEW packages will be INSTALLED:
_tflow_190_select anaconda/linux-64::_tflow_190_select-0.0.1-gpu
c-ares anaconda/linux-64::c-ares-1.15.0-h7b6447c_1
cudatoolkit anaconda/linux-64::cudatoolkit-9.0-h13b8566_0
cudnn anaconda/linux-64::cudnn-7.1.2-cuda9.0_0
cupti anaconda/linux-64::cupti-9.0.176-0
krb5 anaconda/linux-64::krb5-1.16.1-h173b8e3_7
pip anaconda/linux-64::pip-18.1-py36_0
tensorflow-gpu anaconda/linux-64::tensorflow-gpu-1.9.0-hf154084_0
The following packages will be UPDATED:
absl-py conda-forge/noarch::absl-py-0.1.10-py~ --> anaconda/linux-64::absl-py-0.7.0-py36_0
ca-certificates conda-forge::ca-certificates-2018.11.~ --> anaconda::ca-certificates-2018.12.5-0
curl pkgs/main::curl-7.60.0-h84994c4_0 --> anaconda::curl-7.63.0-hbc83047_1000
gast 0.2.0-py27_0 --> 0.2.2-py36_0
grpcio pkgs/main::grpcio-1.12.1-py27hdbcaa40~ --> anaconda::grpcio-1.16.1-py36hf8bcb03_1
libcurl pkgs/main::libcurl-7.60.0-h1ad7b7a_0 --> anaconda::libcurl-7.63.0-h20c2e04_1000
libedit pkgs/main::libedit-3.1-heed3624_0 --> anaconda::libedit-3.1.20181209-hc058e9b_0
markdown conda-forge/noarch::markdown-2.6.11-p~ --> anaconda/linux-64::markdown-3.0.1-py36_0
mkl_fft pkgs/main::mkl_fft-1.0.6-py27hd81dba3~ --> anaconda::mkl_fft-1.0.10-py36ha843d7b_0
ncurses pkgs/main::ncurses-6.0-h9df7e31_2 --> anaconda::ncurses-6.1-he6710b0_1
openssl conda-forge::openssl-1.0.2p-h14c3975_~ --> anaconda::openssl-1.1.1-h7b6447c_0
protobuf conda-forge::protobuf-3.5.2-py27hd28b~ --> anaconda::protobuf-3.5.2-py36hf484d3e_1
python pkgs/main::python-2.7.14-h1571d57_29 --> anaconda::python-3.6.8-h0371630_0
setuptools pkgs/main::setuptools-38.4.0-py27_0 --> anaconda::setuptools-40.6.3-py36_0
six pkgs/main::six-1.11.0-py27h5f960f1_1 --> anaconda::six-1.12.0-py36_0
sqlite pkgs/main::sqlite-3.23.1-he433501_0 --> anaconda::sqlite-3.26.0-h7b6447c_0
tensorflow conda-forge::tensorflow-1.3.0-py27_0 --> anaconda::tensorflow-1.9.0-gpu_py36h02c5d5e_1
tk pkgs/main::tk-8.6.7-hc745277_3 --> anaconda::tk-8.6.8-hbc83047_0
wheel pkgs/main::wheel-0.30.0-py27h2bc6bb2_1 --> anaconda::wheel-0.32.3-py36_0
The following packages will be SUPERSEDED by a higher-priority channel:
certifi conda-forge::certifi-2018.11.29-py27_~ --> anaconda::certifi-2018.11.29-py36_0
git pkgs/main::git-2.17.0-pl526hb75a9fb_0 --> anaconda::git-2.11.1-0
libssh2 pkgs/main::libssh2-1.8.0-h9cfc8f7_4 --> anaconda::libssh2-1.8.0-h1ba5d50_4
mkl_random pkgs/main::mkl_random-1.0.2-py27hd81d~ --> anaconda::mkl_random-1.0.2-py36hd81dba3_0
numpy pkgs/main::numpy-1.15.4-py27h7e9f1db_0 --> anaconda::numpy-1.15.4-py36h7e9f1db_0
numpy-base pkgs/main::numpy-base-1.15.4-py27hde5~ --> anaconda::numpy-base-1.15.4-py36hde5b4d6_0
qt pkgs/main::qt-5.9.4-h4e5bff0_0 --> anaconda::qt-4.8.7-2
tensorflow-base pkgs/main::tensorflow-base-1.9.0-eige~ --> anaconda::tensorflow-base-1.9.0-gpu_py36h6ecc378_0
werkzeug pkgs/main::werkzeug-0.14.1-py27_0 --> anaconda::werkzeug-0.14.1-py36_0
The following packages will be DOWNGRADED:
astor 0.7.1-py27_0 --> 0.7.1-py36_0
tensorboard 1.10.0-py27hf484d3e_0 --> 1.9.0-py36hf484d3e_0
termcolor 1.1.0-py27_1 --> 1.1.0-py36_1
Proceed ([y]/n)? y
Downloading and Extracting Packages
tensorflow-gpu-1.9.0 | 2 KB | ########################################################################################################################################## | 100%
absl-py-0.7.0 | 156 KB | ########################################################################################################################################## | 100%
six-1.12.0 | 22 KB | ########################################################################################################################################## | 100%
git-2.11.1 | 9.5 MB | ########################################################################################################################################## | 100%
_tflow_190_select-0. | 2 KB | ########################################################################################################################################## | 100%
setuptools-40.6.3 | 625 KB | ########################################################################################################################################## | 100%
c-ares-1.15.0 | 98 KB | ########################################################################################################################################## | 100%
cupti-9.0.176 | 1.6 MB | ########################################################################################################################################## | 100%
libssh2-1.8.0 | 233 KB | ########################################################################################################################################## | 100%
gast-0.2.2 | 138 KB | ########################################################################################################################################## | 100%
ncurses-6.1 | 958 KB | ########################################################################################################################################## | 100%
protobuf-3.5.2 | 610 KB | ########################################################################################################################################## | 100%
tensorflow-base-1.9. | 170.8 MB | ########################################################################################################################################## | 100%
ca-certificates-2018 | 123 KB | ########################################################################################################################################## | 100%
python-3.6.8 | 34.4 MB | ########################################################################################################################################## | 100%
cudatoolkit-9.0 | 340.4 MB | ########################################################################################################################################## | 100%
qt-4.8.7 | 34.1 MB | ########################################################################################################################################## | 100%
sqlite-3.26.0 | 1.9 MB | ########################################################################################################################################## | 100%
astor-0.7.1 | 43 KB | ########################################################################################################################################## | 100%
tensorboard-1.9.0 | 3.3 MB | ########################################################################################################################################## | 100%
mkl_fft-1.0.10 | 170 KB | ########################################################################################################################################## | 100%
mkl_random-1.0.2 | 407 KB | ########################################################################################################################################## | 100%
certifi-2018.11.29 | 146 KB | ########################################################################################################################################## | 100%
wheel-0.32.3 | 35 KB | ########################################################################################################################################## | 100%
numpy-base-1.15.4 | 4.3 MB | ########################################################################################################################################## | 100%
numpy-1.15.4 | 47 KB | ########################################################################################################################################## | 100%
curl-7.63.0 | 145 KB | ########################################################################################################################################## | 100%
openssl-1.1.1 | 5.0 MB | ########################################################################################################################################## | 100%
tk-8.6.8 | 3.1 MB | ########################################################################################################################################## | 100%
libedit-3.1.20181209 | 188 KB | ########################################################################################################################################## | 100%
markdown-3.0.1 | 107 KB | ########################################################################################################################################## | 100%
werkzeug-0.14.1 | 423 KB | ########################################################################################################################################## | 100%
krb5-1.16.1 | 1.4 MB | ########################################################################################################################################## | 100%
termcolor-1.1.0 | 7 KB | ########################################################################################################################################## | 100%
pip-18.1 | 1.8 MB | ########################################################################################################################################## | 100%
libcurl-7.63.0 | 550 KB | ########################################################################################################################################## | 100%
tensorflow-1.9.0 | 3 KB | ########################################################################################################################################## | 100%
grpcio-1.16.1 | 1.1 MB | ########################################################################################################################################## | 100%
cudnn-7.1.2 | 367.8 MB | ########################################################################################################################################## | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
(OK - I see the change to Python 3.7 now, but that's still a nasty thing to have to be careful about. Is there some way to force it to leave my Python version alone?)

Cause
Changing Python versions without updating the conda package breaks Conda. . The Python version change (2.7.14 -> 3.6.8) created a situation where the new python has a new site-packages which no longer contains a conda package, whereas if you only update within 2.7.x, this wouldn't be an issue.
Conda includes both a set of binaries (e.g., what you're invoking when you type conda in a shell) and a Python package by the same name. The Python package is necessary for Conda as a whole to function and it get's loaded whenever you try to use conda.
It is problematic that many packages on Anaconda seem to be triggering Python version changes, but not subsequently triggering a conda package update. This sounds like something the dependency resolver is overlooking - i.e., default behavior should be to protect integrity of base environment where conda lives.
Trying to Recover
One possible route to recovery is to temporarily use micromamba (a standalone build of mamba) to repair the base environment. You can do all the following from any directory, so maybe use a temporary one or wherever you put downloads. Please report in the comments if this works or needs adjusting!
Installing Micromamba
Download the appropriate micromamba for your platform (here we'll use the latest linux-64 build). The actual binary will be at bin/micromamba:
# download and unpack
wget -qO- https://micro.mamba.pm/api/micromamba/linux-64/latest | tar -xvj bin/micromamba
Temporarily set MAMBA_ROOT_PREFIX to the base of your install. Typically this is the anaconda3 or miniconda3 folder; in this case, we'll use the path given by OP:
export MAMBA_ROOT_PREFIX=/home/me/anaconda2
Temporarily configured the shell to add the micromamba command:
eval "$(./bin/micromamba shell hook -s posix)"
Test that is works by checking the configuration information:
micromamba info
The key thing to check for is that base environment: correctly identifies to where your base env is and shows it as (writable). You should also see the pkgs folder in your base env in the package cache: .
Reinstall conda for the Current Python
(Re-)Install the conda package in the base env:
micromamba install -n base conda
Make sure that the build of Conda that is suggested corresponds to the version of Python currently installed. The --force-reinstall flag might be useful if it claims the requirement is already satisfied. Alternatively, try
micromamba upgrade -n base conda
Try a new shell and see if conda is working. You don't need to keep the micromamba around. However, I do enthusiastically encourage users to permanently install mamba (see next step).
(Optional) Install Mamba in base
Consider also installing Mamba directly in the base environment. It is a compiled (fast!) alternative frontend to Conda environment management.
micromamba install -n base mamba
One can then use mamba in most places where conda would be used.
Last Recourse
If all else fails you may just have to reinstall. Others have reported installing in other directories and being able to still use and access their environmentss.
Preventions
Avoiding Breakage through Better Practice
First, just a general (opinionated) recommendation: leverage virtual environments more. This isn't directly solving the problem, but it will help you have a workflow that is significantly less prone to encountering such pitfalls. You shouldn't have accepted such a huge change in the first place, not to base. Personally, I rarely install things in base outside of infrastructure (emacs, jupyter-related things, conda, etc.).1 Software packages go into project-specific or at least development-type environments.
For example, were I doing the install shown, I would have made a new environment for it
mamba create -n tf36 anaconda::tensorflow-gpu python=3.6
or whatever Python version you actually wish to work in.
Direct Solution: Pinning
Conda does support package pinning, and this is the more direct way to ensure you never ruin your base install again by transitioning Python 2 to 3. Namely, in the environment's conda-meta folder create a file, pinned and add the line
python 2.7.*
Note that some users have reported similar issues for 3.6 -> 3.7 transitions, so I believe including the minor version here is necessary. See the documentation on pinning.
[1] Note that I use a Miniforge variant (Mambaforge), not the Anaconda installer, so I have more control over base from the start.

I have solved this issue by removing any PYTHONHOME sys PATH(s).

RemoveError: 'requests' is a dependency of conda and cannot be removed from conda's operating environment

Having trouble installing a third party library and I have not seen this error before using Windows 10 with Anaconda installed:
C:\Users\XYZ>conda env create -f python3.6-environment-windows.yml
Collecting package metadata: done
Solving environment: done
Downloading and Extracting Packages
certifi-2018.1.18 | 144 KB | ############################################################################ | 100%
mkl-2018.0.1 | 155.2 MB | ############################################################################ | 100%
pytz-2018.9 | 229 KB | ############################################################################ | 100%
icc_rt-2019.0.0 | 9.4 MB | ############################################################################ | 100%
icu-58.2 | 21.8 MB | ############################################################################ | 100%
pip-9.0.1 | 1.7 MB | ############################################################################ | 100%
xz-5.2.3 | 348 KB | ############################################################################ | 100%
sip-4.18.1 | 269 KB | ############################################################################ | 100%
libpng-1.6.36 | 1.3 MB | ############################################################################ | 100%
vc-14 | 985 B | ############################################################################ | 100%
numpy-1.14.0 | 3.7 MB | ############################################################################ | 100%
python-3.6.4 | 17.6 MB | ############################################################################ | 100%
jpeg-9c | 314 KB | ############################################################################ | 100%
wheel-0.30.0 | 85 KB | ############################################################################ | 100%
wincertstore-0.2 | 13 KB | ############################################################################ | 100%
freetype-2.9.1 | 475 KB | ############################################################################ | 100%
scipy-1.0.0 | 13.0 MB | ############################################################################ | 100%
pyparsing-2.3.1 | 54 KB | ############################################################################ | 100%
kiwisolver-1.0.1 | 60 KB | ############################################################################ | 100%
qt-5.6.2 | 55.6 MB | ############################################################################ | 100%
python-dateutil-2.7. | 218 KB | ############################################################################ | 100%
vs2015_runtime-14.0. | 1.9 MB | ############################################################################ | 100%
ca-certificates-2017 | 489 KB | ############################################################################ | 100%
tk-8.6.7 | 3.5 MB | ############################################################################ | 100%
setuptools-38.4.0 | 540 KB | ############################################################################ | 100%
matplotlib-2.2.2 | 6.5 MB | ############################################################################ | 100%
six-1.12.0 | 21 KB | ############################################################################ | 100%
openssl-1.0.2n | 5.4 MB | ############################################################################ | 100%
pyqt-5.6.0 | 4.5 MB | ############################################################################ | 100%
zlib-1.2.11 | 236 KB | ############################################################################ | 100%
tornado-5.1.1 | 665 KB | ############################################################################ | 100%
sqlite-3.22.0 | 907 KB | ############################################################################ | 100%
cycler-0.10.0 | 8 KB | ############################################################################ | 100%
Preparing transaction: done
Verifying transaction: failed
RemoveError: 'requests' is a dependency of conda and cannot be removed from
conda's operating environment.
RemoveError: 'setuptools' is a dependency of conda and cannot be removed from
conda's operating environment.
In reference to the instructions here - https://enigma.co/catalyst/install.html#installing-with-conda

I had the same problem on Mac Mojave, and in my case run conda update --force conda first worked for me.

running conda update conda before solved the problem for me

conda update --force conda
will solve : Verifying transaction: failed Remove Error: 'request' is a dependency of conda and cannot be removed from conda is operating environment.

This worked for me on Linux:
Uninstall the package via pip:
pip uninstall setuptools
Reinstall using the following command:
conda install -c anaconda setuptools
Consider also that system packages (python3-setuptools, python-setuptools in Ubuntu) might need to be removed.

conda update --force conda
this worked for me in win64 when I
conda install -c https://conda.anaconda.org/sdvillal openslide-python

Silly point to make here but I've been caught by this before: you may not be in the environment you think you are. Just before killing off any package run a quick check to see:
conda env list
Performing ops on the base environment can cause issues, so you may want to create or change environment.

I had the same problem, which was due to a bad installation of a package (OpenEXR in my case).
Try to verify your package with conda list yourPackage.
If you find which one it is, prefer installing it with pre-built packages here : https://www.lfd.uci.edu/~gohlke/pythonlibs/.
A stack-overflow thread that helped me : Python 2.7, PIP: "Failed building wheel for ..."
EDIT :
Two friends had the same error, one solved it by installing/executing with admin rights.
The other one succeeded by creating a new virtual environnement for python.

I ran into the same problem, on macos, after removing all R packages installed by anaconda. Unfortunately, the only solution I found is to reinstall anaconda. Alternatively, you could download miniconda shell script installer, run it with -U option and point the installer at your conda directory. This fixed the issue for me while maintaining settings such as channel priority. However, many of previously installed packages were not importable (Python couldn't find them) and i ended up re-installing all of them.

I had the same problem. Try to use the command prompt to install wheel file if you get an error something like this(as shown in picture) then you must install that wheel file:
Extra(how to install wheel file from command prompt):
download wheel file as per the system specifications: -search required file here https://www.lfd.uci.edu/~gohlke/pythonlibs/ -e.g.
bsddb3 -click bsddb3 and search required file
open command prompt on your system
change the location on the command prompt to: where you have downloaded wheel file e.g C:\Users\Name\Downloads
go to the location, where you have installed python>>go to script>> copy the path (e.g C:\Program Files (x86)\Python36-32\Scripts)
write the command, to install wheel file using pip install (e.g. C:\Program Files (x86)\Python36-32\Scripts\pip install
copy_name_of_the_wheel_file)
run the command

try conda env create --force -f python3.6-environment-windows.yml
I'm not sure exactly where to place it but I use the --force whenever I run into issues like this like conda update --force conda or conda install --force ...
use it as last solution since it force conda to perform the command and you might run into some issues later on

I had solved the problem
RemoveError: 'setuptools' is a dependency of conda and cannot be removed from
conda's operating environment.
As the following way:
pip uninstall setuptools
conda update conda
conda update setuptools
and then check tools
I haven't met any mistakes yet, but help me correct my way , if something wrong, please

For me, deactivating the current conda environment solves the problem, i.e. run conda deactivate before upgrading.

I had to do the following steps to get it to work for me
conda update --force conda
This will run and update conda then run the following command
conda update conda
At each stage update all packages. After that, everything should work fine.

Cloning conda env fails: error conda.core.link:_execute(543)

I'm trying to clone a conda environment in order to use it on a new machine. On first machine:
conda-env export -n dvina > dvina.yml
On target machine:
conda-env create -n dvina -f=dvina.yml
This fails with error conda.core.link:_execute(543). Searching reveals numerous posts with conda.core.link, but none with 543. This is the the bash shell output from the target machine:
$ conda-env create -n dvina -f=dvina.yml
Collecting package metadata: done
Solving environment: done
Downloading and Extracting Packages
numpy-base-1.15.4 | 4.2 MB | ##################################### | 100%
mkl_random-1.0.2 | 383 KB | ##################################### | 100%
mkl_fft-1.0.6 | 191 KB | ##################################### | 100%
gcc_linux-64-7.3.0 | 10 KB | ##################################### | 100%
pytz-2018.7 | 248 KB | ##################################### | 100%
gxx_linux-64-7.3.0 | 9 KB | ##################################### | 100%
graphite2-1.3.12 | 106 KB | ##################################### | 100%
ca-certificates-2018 | 124 KB | ##################################### | 100%
libcurl-7.62.0 | 517 KB | ##################################### | 100%
python-dateutil-2.7. | 274 KB | ##################################### | 100%
intel-openmp-2019.1 | 885 KB | ##################################### | 100%
gfortran_linux-64-7. | 9 KB | ##################################### | 100%
libgcc-7.2.0 | 304 KB | ##################################### | 100%
pandas-0.23.4 | 10.0 MB | ##################################### | 100%
numpy-1.15.4 | 47 KB | ##################################### | 100%
mkl-2019.1 | 204.6 MB | ##################################### | 100%
curl-7.62.0 | 143 KB | ##################################### | 100%
six-1.12.0 | 22 KB | ##################################### | 100%
openbabel-2.4.1 | 5.1 MB | ##################################### | 100%
binutils_linux-64-2. | 9 KB | ##################################### | 100%
libpng-1.6.35 | 335 KB | ##################################### | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: failed
ERROR conda.core.link:_execute(543): An error occurred while installing package 'defaults::icu-58.2-h9c2bf20_1'.
IsADirectoryError(21, 'Is a directory')
Attempting to roll back.
Rolling back transaction: done
[Errno 21] Is a directory: '/home/mheller/anaconda3/pkgs/icu-58.2-h9c2bf20_1/lib/icu/current'
Both machines are running Ubuntu; the source machine 16.04.2, the target machine 16.04.5. I've updated conda on both: conda update -n base conda -c anaconda.
A folder called dvina is created, but only contains a folder conda-meta with json files.
As a note, this happens on two machines with Ubuntu 16.04.5, but works if I clone an environment on the source machine itself with Ubuntu 16.04.2. Also, I observe the same behavior if I try to create a new environment from scratch, but only on the Ubuntu 16.04.5 machines. My understanding is that I cannot roll back to Ubuntu 16.04.2, so how can I solve this issue from the conda side?

TL;DR:
use conda install icu -c conda-forge first.
Hey, friends, I have been troubled by this problem for months. Today it comes up again and I decided to solve it.
I think it may be a bug of icu side. I have seen the problem several times, and it all happens when installing icu = 58.2-h9c2bf20_1.
Guess what? When I tried a new version of icu, it is solved!
I use the following command:
conda install icu -c conda-forge
The version of icu in conda-forge is about 60+, and it can be installed without pain.
After installing icu, then I continue to install other packages, and it works!
Hope it works for you :)