- Permission denied errors during installation
- Permission denied errors after using sudo conda command
- Already installed error message
- Conda reports that a package is installed, but it appears not to be
- pkg_resources.DistributionNotFound: conda==3.6.1-6-gb31b0d4-dirty
- macOS error “ValueError unknown locale: UTF-8”
- AttributeError or missing getproxies
- Shell commands open from the wrong location
- Programs fail due to invoking conda Python instead of system Python
- UnsatisfiableSpecifications error
- Package installation fails from a specific channel
- Conda automatically upgrades to unwanted version
- ValidationError: Invalid value for timestamp
- Unicode error after installing Python 2
umask command determines the mask settings that control
how file permissions are set for newly created files. If you
have a very restrictive
umask, such as
077, you get
“permission denied” errors.
Set a less restrictive
umask before calling conda commands.
Conda was intended as a user space tool, but often users need to
use it in a global environment. One place this can go awry is
with restrictive file permissions. Conda creates links when you
install files that have to be read by others on the system.
To give yourself full permissions for files and directories, but prevent the group and other users from having access:
Before installing, set the
umaskto the original setting:
umask 007 conda install umask 077
For more information on
Once you run conda with sudo, you must use sudo forever. We recommend that you NEVER run conda with sudo.
If you are trying to fix conda problems without removing the current installation and you try to reinstall Miniconda or Anaconda to fix it, you get an error message that Miniconda or Anaconda is already installed, and you cannot continue.
Install using the –force option.
Download and install the appropriate Miniconda
for your operating system from the Miniconda download page using the force option
bash Miniconda3-latest-MacOSX-x86_64.sh -f
NOTE: Substitute the appropriate filename and version for your operating system.
NOTE: Be sure that you install to the same install location as your existing install so it overwrites the core conda files and does not install a duplicate in a new folder.
Sometimes conda claims that a package is already installed, but it does not appear to be, for example, a Python package that gives ImportError.
There are several possible causes for this problem, each with its own solution.
You are not in the same conda environment as your package.
Make sure that you are in the same conda environment as your package. The
conda infocommand tells you what environment is currently active—under
Verify that you are using the Python from the correct environment by running:
import sys print(sys.prefix)
For Python packages, you have set the PYTHONPATH or PYTHONHOME variable. These environment variables cause Python to load files from locations other than the standard ones. Conda works best when these environment variables are not set, as their typical use cases are obviated by conda environments and a common issue is that they cause Python to pick up the wrong versions or broken versions of a library.
For Python packages, make sure you have not set the PYTHONPATH
or PYTHONHOME variables. The command
conda info -a displays
the values of these environment variables.
- To unset these environment variables temporarily for the
current Terminal session, run
- To unset them permanently, check for lines in the files:
- If you use bash—
- If you use zsh—~/.zshrc`.
- If you use PowerShell on Windows, the file output by
- If you use bash—
You have site-specific directories or, for Python, you have
so-called site-specific files. These are typically located in
~/.local on Linux and macOS. For a full description of the locations of
site-specific packages, see PEP 370. As with
PYTHONPATH, Python may try importing packages from this
directory, which can cause issues.
For Python packages, remove site-specific directories and site-specific files.
For C libraries, the following environment variables have been set:
These act similarly to
PYTHONPATH for Python. If they are
set, they can cause libraries to be loaded from locations other
than the conda environment. Conda environments obviate most use
cases for these variables. The command
conda info -a shows
what these are set to.
Unset DYLD_LIBRARY_PATH or LD_LIBRARY_PATH.
Occasionally, an installed package becomes corrupted. Conda works
by unpacking the packages in the
pkgs directory and then
hard-linking them to the environment. Sometimes these get
corrupted, breaking all environments that use them, and also any
additional environments, since the same files are hard-linked
Run the command
conda install -f to unarchive the package
again and relink it. It also does an md5 verification on the
package. Usually if this is different, it is because your
channels have changed and there is a different package with the
same name, version, and build number.
NOTE: This breaks the links to any other environments that
already had this package installed, so you have to reinstall it
there, too. It also means that running
conda install -f a lot
can use up a lot of disk space if you have a lot of environments.
-f flag to
conda install (
conda install -f package does not reinstall
any of the dependencies of
The local version of conda needs updating.
Force reinstall conda. A useful way to work off the development
version of conda is to run
python setup.py develop on a
checkout of the conda git repository. However, if you are not
git pull, it is a good idea to un-develop,
as you will otherwise not get any regular updates to conda. The
normal way to do this is to run
python setup.py develop -u.
However, this command does not replace the
itself. With other packages, this is not an issue, as you can
just reinstall them with
conda, but conda cannot be used if
conda is installed.
The fix is to use the
./bin/conda executable in the conda
git repository to force reinstall conda, that is, run
./bin/conda install -f conda. You can then verify with
conda info that you have the latest version of conda, and not
a git checkout—the version should not include any hashes.
This is a bug in the macOS Terminal app that shows up only in certain locales. Locales are country-language combinations.
Open Terminal in
Clear the Set locale environment variables on startup checkbox.
This sets your LANG environment variable to be empty. This may
cause Terminal use to incorrect settings for your locale. The
locale command in Terminal tells you what settings are used.
To use the correct language, add a line to your bash profile,
which is typically
your-lang with the correct locale specifier for
locale -a displays all the specifiers. For
example, the language code for US English is
locale affects what translations are used when they are available
and also how dates, currencies and decimals are formatted.
When running a command such as
conda update ipython, you may
AttributeError: 'module' object has no attribute
This can be caused by an old version of
requests or by having
PYTHONPATH environment variable set.
requests and be sure
PYTHONPATH is not set:
conda info -ato show the
requestsversion and various environment variables such as
- Update the
pip install -U requests.
- On Windows, clear it the environment variable settings.
- On macOS and Linux, clear it by removing it from the bash profile and restarting the shell.
When you run a command within a conda environment, conda does not access the correct package executable.
In both bash and zsh, when you enter a command, the shell searches the paths in PATH one by one until it finds the command. The shell then caches the location, which is called hashing in shell terminology. When you run command again, the shell does not have to search the PATH again.
The problem is that before you installed the program, you ran a command which
loaded and hashed another version of that program in some other location on
the PATH, such as
/usr/bin. Then you installed the program
conda install, but the shell still had the old instance
Reactivate the environment or run
hash -r (in bash) or
rehash (in zsh).
When you run
source activate, conda automatically runs
hash -r in bash and
rehash in zsh to clear the hashed
commands, so conda finds things in the new path on the PATH. But
there is no way to do this when
conda install is run because
the command must be run inside the shell itself, meaning either
you have to run the command yourself or use source a file that
contains the command.
This is a relatively rare problem, since this happens only in the following circumstances:
- You activate an environment or use the root environment, and then run a command from somewhere else.
- Then you conda install a program, and then try to run the
program again without running
type command_name always tells you exactly what
is being run. This is better than
which command_name, which
ignores hashed commands and searches the PATH directly.
The hash is reset by
source activate, or by
hash -r in bash or
rehash in zsh.
After installing Anaconda or Miniconda, programs that run
python switch from invoking the system Python to invoking the
Python in the root conda environment. If these programs rely on
the system Python to have certain configurations or dependencies
that are not in the root conda environment Python, the programs
may crash. For example, some users of the Cinnamon desktop
environment on Linux Mint have reported these crashes.
.bashrc files so that the
conda binary directory, such as
~/miniconda3/bin, is no
longer added to the PATH environment variable. You can still run
deactivate by using their full
path names, such as
You may also create a folder with symbolic links to
deactivate, and then edit your
.bashrc file to add this folder to your
PATH. If you do this, running
python will invoke the system
Python, but running
source activate MyEnv,
source activate root, or
source deactivate will work
source activate to activate any environment,
including after running
source activate root, running
python will invoke the Python in the active conda environment.
Some conda package installation specifications are impossible to
satisfy. For example,
conda create -n tmp python=3 wxpython=3
produces an “Unsatisfiable Specifications” error because wxPython
3 depends on Python 2.7, so the specification to install Python 3
conflicts with the specification to install wxPython 3.
When an unsatisfiable request is made to conda, conda shows a message such as this one:
The following specifications were found to be in conflict: - python 3* - wxpython 3* -> python 2.7* Use "conda info <package>" to see the dependencies for each package.
This indicates that the specification to install wxpython 3 depends on installing Python 2.7, which conflicts with the specification to install python 3.
Use “conda info wxpython” or “conda info wxpython=3” to show information about this package and its dependencies:
wxpython 3.0 py27_0 ------------------- file name : wxpython-3.0-py27_0.tar.bz2 name : wxpython version : 3.0 build number: 0 build string: py27_0 channel : defaults size : 34.1 MB date : 2014-01-10 fn : wxpython-3.0-py27_0.tar.bz2 license_family: Other md5 : adc6285edfd29a28224c410a39d4bdad priority : 2 schannel : defaults url : https://repo.continuum.io/pkgs/free/osx-64/wxpython-3.0-py27_0.tar.bz2 dependencies: python 2.7* python.app
By examining the dependencies of each package, you should be able to determine why the installation request produced a conflict and modify the request so it can be satisfied without conflicts. In this example, you could install wxPython with Python 2.7:
conda create -n tmp python=2.7 wxpython=3
Sometimes it is necessary to install a specific version from a specific channel because that version is not available from the default channel.
The following example describes the problem in detail and its solution.
Suppose you have a specific need to install the Python
cx_freeze module with Python 3.4. A first step is to create a
Python 3.4 environment:
conda create -n py34 python=3.4
Using this environment you should first attempt:
conda install -n py34 cx_freeze
However, when you do this you get the following error:
Using Anaconda Cloud api site https://api.anaconda.org Fetching package metadata ......... Solving package specifications: . Error: Package missing in current osx-64 channels: - cx_freeze You can search for packages on anaconda.org with anaconda search -t conda cx_freeze
The message indicates that
cx_freeze cannot be found in the
default package channels. However, there may be a
community-created version available and you can search for it by
running the following command:
$ anaconda search -t conda cx_freeze Using Anaconda Cloud api site https://api.anaconda.org Run 'anaconda show <USER/PACKAGE>' to get more details: Packages: Name | Version | Package Types | Platforms ------------------------- | ------ | --------------- | --------------- inso/cx_freeze | 4.3.3 | conda | linux-64 pyzo/cx_freeze | 4.3.3 | conda | linux-64, win-32, win-64, linux-32, osx-64 : http://cx-freeze.sourceforge.net/ silg2/cx_freeze | 4.3.4 | conda | linux-64 : create standalone executables from Python scripts takluyver/cx_freeze | 4.3.3 | conda | linux-64 Found 4 packages
In this example, there are 4 different places that you could try to get the package. None of them are officially supported or endorsed by Anaconda, but members of the conda community have provided many valuable packages. If you want to go with public opinion, then the web interface provides more information:
Notice that the
pyzo organization has by far the most
downloads, so you might choose to use their package. If so, you
can add their organization’s channel by specifying it on the
$ conda create -c pyzo -n cxfreeze_py34 cx_freeze python=3.4 Using Anaconda Cloud api site https://api.anaconda.org Fetching package metadata: .......... Solving package specifications: ......... Package plan for installation in environment /Users/ijstokes/anaconda/envs/cxfreeze_py34: The following packages will be downloaded: package | build ---------------------------|----------------- cx_freeze-4.3.3 | py34_4 1.8 MB setuptools-20.7.0 | py34_0 459 KB ------------------------------------------------------------ Total: 2.3 MB The following NEW packages will be INSTALLED: cx_freeze: 4.3.3-py34_4 openssl: 1.0.2h-0 pip: 8.1.1-py34_1 python: 3.4.4-0 readline: 6.2-2 setuptools: 20.7.0-py34_0 sqlite: 3.9.2-0 tk: 8.5.18-0 wheel: 0.29.0-py34_0 xz: 5.0.5-1 zlib: 1.2.8-0
Now you have a software environment sandbox created with Python
When making a python package for an app, you create an
environment for the app from a file
req.txt that sets a
certain version, such as
python=2.7.9. However, when you
conda install your package, it automatically upgrades to a
later version, such as
If you make a conda package for the app using conda build, you
can set dependencies with specific version numbers. In this
requirements lines that say
- python could be
- python ==2.7.9 instead. It is important to have 1 space
before the == operator and no space after.
Exercise caution when coding version requirements.
This happens when certain packages are installed with conda 4.3.28, and then conda is downgraded to 4.3.27 or earlier.
Example: UnicodeDecodeError: ‘ascii’ codec can’t decode byte 0xd3 in position 1: ordinal not in range(128)
Python 2 is incapable of handling unicode properly, especially on Windows. In this case, if any character in your PATH env. var contains anything that is not ASCII then you see this exception.
Remove all non-ASCII from PATH or switch to Python 3.