conda create --name <my-env>
Replace <my-env> with the name of your environment.
When conda asks you to proceed, type y:
proceed ([y]/n)?
This creates the myenv environment in /envs/. No
packages will be installed in this environment.
To create an environment with a specific version of Python:
conda create -n myenv python=3.9
To create an environment with a specific package:
conda create -n myenv scipy
conda create -n myenv python
conda install -n myenv scipy
To create an environment with a specific version of a package:
conda create -n myenv scipy=0.17.3
conda create -n myenv python
conda install -n myenv scipy=0.17.3
To create an environment with a specific version of Python and
multiple packages:
conda create -n myenv python=3.9 scipy=0.17.3 astroid babel
Install all the programs that you want in this environment
at the same time. Installing one program at a time can lead to
dependency conflicts.
To automatically install pip or another program every time a new
environment is created, add the default programs to the
create_default_packages section
of your .condarc configuration file. The default packages are
installed every time you create a new environment. If you do not
want the default packages installed in a particular environment,
use the --no-default-packages flag:
conda create --no-default-packages -n myenv python
You can add much more to the conda create command.
For details, run conda create --help.
Creating an environment from an environment.yml file
Use the terminal for the following steps:
Create the environment from the environment.yml file:
conda env create -f environment.yml
The first line of the yml file sets the new environment's
name. For details see Creating an environment file manually.
Activate the new environment: conda activate myenv
Verify that the new environment was installed correctly:
conda env list
You can also use conda info --envs.
Specifying a different target platform for an environment
By default, conda
will create environments targeting the platform it's
currently running on. You can check which platform you are currently on by running
conda info and checking the platform entry.
However, in some cases you might want to create an environment for a
different target platform or architecture. To do so, use the
--platform flag available in the conda create and
conda env create commands. See --subdir, --platform
in conda create for more information about allowed values.
For example, a user running macOS on the Apple Silicon platform
might want to create a python environment for Intel processors
and emulate the executables with Rosetta. The command would be:
conda create --platform osx-64 --name python-x64 python
You can't specify the --platform flag for existing environments.
When created, the environment will be annotated with the custom configuration and
subsequent operations on it will remember the target platform.
This flag also allows specifying a different OS (e.g. creating a Linux
environment on macOS), but we don't recommend its usage outside of
--dry-run operations. Common problems with mismatched OSes include:
The environment cannot be solved because virtual packages are missing.
You can workaround this issue by exporting the necessary
CONDA_OVERRIDE_**** environment variables. For example, solving
for Linux from macOS, you will probably need CONDA_OVERRIDE_LINUX=1
and CONDA_OVERRIDE_GLIBC=2.17.
The environment can be solved, but extraction and linking fails due
filesystem limitations (case insensitive systems, incompatible paths,
etc). The only workaround here is to use --dry-run --json to obtain
the solution and process the payload into a lockfile that can be shared
with the target machine. See Create explicit lockfiles without creating an environment for more details.
Specifying a location for an environment
You can control where a conda environment lives by providing a path
to a target directory when creating the environment. For example,
the following command will create a new environment in a subdirectory
of the current working directory called envs:
conda create --prefix ./envs jupyterlab=3.2 matplotlib=3.5 numpy=1.21
You then activate an environment created with a prefix using the same
command used to activate environments created by name:
conda activate ./envs
Specifying a path to a subdirectory of your project directory when
creating an environment has the following benefits:
It makes it easy to tell if your project uses an isolated environment
by including the environment as a subdirectory.
It makes your project more self-contained as everything, including
the required software, is contained in a single project directory.
An additional benefit of creating your project’s environment inside a
subdirectory is that you can then use the same name for all your
environments. If you keep all of your environments in your envs
folder, you’ll have to give each environment a different name.
There are a few things to be aware of when placing conda environments
outside of the default envs folder.
Conda can no longer find your environment with the --name flag.
You’ll generally need to pass the --prefix flag along with the
environment’s full path to find the environment.
Specifying an install path when creating your conda environments
makes it so that your command prompt is now prefixed with the active
environment’s absolute path rather than the environment’s name.
After activating an environment using its prefix, your prompt will
look similar to the following:
(/absolute/path/to/envs) $
This can result in long prefixes:
(/Users/USER_NAME/research/data-science/PROJECT_NAME/envs) $
To remove this long prefix in your shell prompt, modify the env_prompt
setting in your .condarc file:
conda config --set env_prompt '({name})'
This will edit your .condarc file if you already have one
or create a .condarc file if you do not.
Now your command prompt will display the active environment’s
generic name, which is the name of the environment's root folder:
$ cd project-directory
$ conda activate ./env
(env) project-directory $
Updating an environment
You may need to update your environment for a variety of reasons.
For example, it may be the case that:
one of your core dependencies just released a new version
(dependency version number update).
you need an additional package for data analysis
(add a new dependency).
you have found a better package and no longer need the older
package (add new dependency and remove old dependency).
If any of these occur, all you need to do is update the contents of
your environment.yml file accordingly and then run the following
command:
conda env update --file environment.yml --prune
The --prune option causes conda to remove any dependencies
that are no longer required from the environment.
Cloning an environment
Use the terminal for the following steps:
You can make an exact copy of an environment by creating a clone
of it:
conda create --name myclone --clone myenv
Replace myclone with the name of the new environment.
Replace myenv with the name of the existing environment that
you want to copy.
To verify that the copy was made:
conda info --envs
In the environments list that displays, you should see both the
source environment and the new copy.
Building identical conda environments
You can use explicit specification files to build an identical
conda environment on the same operating system platform, either
on the same machine or on a different machine.
Use the terminal for the following steps:
Run conda list --explicit to produce a spec list such as:
# This file may be used to create an environment using:
# $ conda create --name <env> --file <this file>
# platform: osx-64
@EXPLICIT
https://repo.anaconda.com/pkgs/free/osx-64/mkl-11.3.3-0.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/numpy-1.11.1-py35_0.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/openssl-1.0.2h-1.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/pip-8.1.2-py35_0.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/python-3.5.2-0.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/readline-6.2-2.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/setuptools-25.1.6-py35_0.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/sqlite-3.13.0-0.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/tk-8.5.18-0.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/wheel-0.29.0-py35_0.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/xz-5.2.2-0.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/zlib-1.2.8-3.tar.bz2
To create this spec list as a file in the current working
directory, run:
conda list
--explicit > spec-file.txt
You can use spec-file.txt as the filename or replace
it with a filename of your choice.
An explicit spec file is not usually cross platform, and
therefore has a comment at the top such as # platform: osx-64
showing the platform where it was created. This platform is the
one where this spec file is known to work. On other platforms,
the packages specified might not be available or dependencies
might be missing for some of the key packages already in the
spec.
To use the spec file to create an identical environment on the
same machine or another machine:
conda create --name myenv --file spec-file.txt
To use the spec file to install its listed packages into an
existing environment:
conda install --name myenv --file spec-file.txt
Conda does not check architecture or dependencies when installing
from a spec file. To ensure that the packages work correctly,
make sure that the file was created from a working environment,
and use it on the same architecture, operating system, and
platform, such as linux-64 or osx-64.
Activating an environment
Activating environments is essential to making the software in the environments
work well. Activation entails two primary functions: adding entries to PATH for
the environment and running any activation scripts that the environment may
contain. These activation scripts are how packages can set arbitrary
environment variables that may be necessary for their operation. You can also
use the config API to set environment variables.
Activation prepends to PATH. This only takes effect
when you have the environment active so it is local to a terminal session,
not global.
When installing Anaconda,
you have the option to “Add Anaconda to my PATH environment variable.”
This is not recommended because it appends Anaconda to PATH.
When the installer appends to PATH, it does not call the activation scripts.
On Windows, PATH is composed of two parts, the system PATH and the
user PATH. The system PATH always comes first. When you install
Anaconda for "Just Me", we add it to the user PATH. When you install
for "All Users", we add it to the system PATH. In the former case,
you can end up with system PATH values taking precedence over
your entries. In the latter case, you do not. We do not recommend
multi-user installs.
To activate an environment: conda activate myenv
Replace myenv with the environment name or directory path.
Conda prepends the path name myenv onto your system command.
You may receive a warning message if you have not activated your environment:
Warning:
This Python interpreter is in a conda environment, but the environment has
not been activated. Libraries may fail to load. To activate this environment
please see https://conda.io/activation.
If you receive this warning, you need to activate your environment. To do
so on Windows, run: c:\Anaconda3\Scripts\activate base in a terminal window.
Windows is extremely sensitive to proper activation. This is because
the Windows library loader does not support the concept of libraries
and executables that know where to search for their dependencies
(RPATH). Instead, Windows relies on a dynamic-link library search order.
If environments are not active, libraries won't be found and there
will be lots of errors. HTTP or SSL errors are common errors when the
Python in a child environment can't find the necessary OpenSSL library.
Conda itself includes some special workarounds to add its necessary PATH
entries. This makes it so that it can be called without activation or
with any child environment active. In general, calling any executable in
an environment without first activating that environment will likely not work.
For the ability to run executables in activated environments, you may be
interested in the conda run command.
If you experience errors with PATH, review our troubleshooting.
Conda init
Earlier versions of conda introduced scripts to make activation
behavior uniform across operating systems. Conda 4.4 allowed
conda activate myenv. Conda 4.6 added extensive initialization
support so that conda works faster and less disruptively on
a wide variety of shells (bash, zsh, csh, fish, xonsh, and more).
Now these shells can use the conda activate command.
Removing the need to modify PATH makes conda less disruptive to
other software on your system. For more information, read the
output from conda init --help.
One setting may be useful to you when using conda init is:
auto_activate_base: bool
This setting controls whether or not conda activates your base
environment when it first starts up. You'll have the conda
command available either way, but without activating the environment,
none of the other programs in the environment will be available until
the environment is activated with conda activate base. People
sometimes choose this setting to speed up the time their shell takes
to start up or to keep conda-installed software from automatically
hiding their other software.
Nested activation
By default, conda activate will deactivate the current environment
before activating the new environment and reactivate it when
deactivating the new environment. Sometimes you may want to leave
the current environment PATH entries in place so that you can continue
to easily access command-line programs from the first environment.
This is most commonly encountered when common command-line utilities
are installed in the base environment. To retain the current environment
in the PATH, you can activate the new environment using:
conda activate --stack myenv
If you wish to always stack when going from the outermost environment,
which is typically the base environment, you can set the auto_stack
configuration option:
conda config --set auto_stack 1
You may specify a larger number for a deeper level of automatic stacking,
but this is not recommended since deeper levels of stacking are more likely
to lead to confusion.
Environment variable for DLL loading verification
If you don't want to activate your environment and you want Python
to work for DLL loading verification, then follow the
troubleshooting directions.
Warning
If you choose not to activate your environment, then
loading and setting environment variables to activate
scripts will not happen. We only support activation.
Deactivating an environment
To deactivate an environment, type: conda deactivate
Conda removes the path name for the currently active environment from
your system command.
To simply return to the base environment, it's better to call conda
activate with no environment specified, rather than to try to deactivate. If
you run conda deactivate from your base environment, you may lose the
ability to run conda at all. Don't worry, that's local to this shell - you can
start a new one. However, if the environment was activated using --stack
(or was automatically stacked) then it is better to use conda deactivate.
Determining your current environment
Use the terminal for the following steps.
By default, the active environment---the one you are currently
using---is shown in parentheses () or brackets [] at the
beginning of your command prompt:
(myenv) $
If you do not see this, run:
conda info --envs
In the environments list that displays, your current environment
is highlighted with an asterisk (*).
By default, the command prompt is set to show the name of the
active environment. To disable this option:
conda config --set changeps1 false
To re-enable this option:
conda config --set changeps1 true
Viewing a list of your environments
To see a list of all of your environments, in your terminal window, run:
conda info --envs
conda env list
A list similar to the following is displayed:
conda environments:
myenv /home/username/miniconda/envs/myenv
snowflakes /home/username/miniconda/envs/snowflakes
bunnies /home/username/miniconda/envs/bunnies
If this command is run by an administrator, a list of all environments
belonging to all users will be displayed.
Viewing a list of the packages in an environment
To see a list of all packages installed in a specific environment:
If the environment is not activated, in your terminal window, run:
conda list -n myenv
If the environment is activated, in your terminal window, run:
conda list
To see if a specific package is installed in an environment, in your
terminal window, run:
conda list -n myenv scipy
Using pip in an environment
To use pip in your environment, in your terminal window, run:
conda install -n myenv pip
conda activate myenv
pip <pip_subcommand>
Issues may arise when using pip and conda together. When combining conda and pip,
it is best to use an isolated conda environment. Only after conda has been used to
install as many packages as possible should pip be used to install any remaining
software. If modifications are needed to the environment, it is best to create a
new environment rather than running conda after pip. When appropriate, conda and
pip requirements should be stored in text files.
We recommend that you:
Use pip only after conda
Install as many requirements as possible with conda then use pip.
Pip should be run with --upgrade-strategy only-if-needed (the default).
Do not use pip with the --user argument, avoid all users installs.
- Use conda environments for isolation
Create a conda environment to isolate any changes pip makes.
Environments take up little space thanks to hard links.
Care should be taken to avoid running pip in the root environment.
- Recreate the environment if changes are needed
Once pip has been used, conda will be unaware of the changes.
To install additional conda packages, it is best to recreate
the environment.
- Store conda and pip requirements in text files
Package requirements can be passed to conda via the --file argument.
Pip accepts a list of Python packages with -r or --requirements.
Conda env will export or create environments based on a file with
conda and pip requirements.
Setting environment variables
If you want to associate environment variables with an environment,
you can use the config API. This is recommended as an alternative to
using activate and deactivate scripts since those are an execution of
arbitrary code that may not be safe.
First, create your environment and activate it:
conda create -n test-env
conda activate test-env
To list any variables you may have, run conda env config vars list.
To set environment variables, run conda env config vars set my_var=value.
Once you have set an environment variable, you have to reactivate your environment:
conda activate test-env.
To check if the environment variable has been set, run
echo $my_var (echo %my_var% on Windows) or conda env config vars list.
When you deactivate your environment, you can use those same commands to see that
the environment variable goes away.
You can specify the environment you want to affect using the -n and -p flags. The -n flag allows you to name the environment and -p allows you to specify the path to the environment.
To unset the environment variable, run conda env config vars unset my_var -n test-env.
When you deactivate your environment, you can see that environment variable goes away by rerunning
echo my_var or conda env config vars list to show that the variable name
is no longer present.
Environment variables set using conda env config vars will be retained in the output of
conda env export. Further, you can declare environment variables in the environment.yml file
as shown here:
name: env-name
channels:
- conda-forge
- defaults
dependencies:
- python=3.7
- codecov
variables:
VAR1: valueA
VAR2: valueB
Saving environment variables
Conda environments can include saved environment variables.
Suppose you want an environment "analytics" to store both a
secret key needed to log in to a server and a path to a
configuration file. The sections below explain how to write a
script named env_vars to do this on Windows and macOS or Linux.
This type of script file can be part of a conda package, in
which case these environment variables become active when an
environment containing that package is activated.
You can name these scripts anything you like. However, multiple
packages may create script files, so be sure to use descriptive
names that are not used by other packages. One popular option is
to give the script a name in the form
packagename-scriptname.sh, or on Windows,
packagename-scriptname.bat.
Windows
Locate the directory for the conda environment in your
terminal window by running in the command shell %CONDA_PREFIX%.
Enter that directory and create these subdirectories and
files:
cd %CONDA_PREFIX%
mkdir .\etc\conda\activate.d
mkdir .\etc\conda\deactivate.d
type NUL > .\etc\conda\activate.d\env_vars.bat
type NUL > .\etc\conda\deactivate.d\env_vars.bat
Edit .\etc\conda\activate.d\env_vars.bat as follows:
set MY_KEY='secret-key-value'
set MY_FILE=C:\path\to\my\file
Edit .\etc\conda\deactivate.d\env_vars.bat as follows:
set MY_KEY=
set MY_FILE=
When you run conda activate analytics, the environment variables
MY_KEY and MY_FILE are set to the values you wrote into the file.
When you run conda deactivate, those variables are erased.
macOS and Linux
Locate the directory for the conda environment in your terminal window by running in the terminal echo $CONDA_PREFIX.
Enter that directory and create these subdirectories and
files:
cd $CONDA_PREFIX
mkdir -p ./etc/conda/activate.d
mkdir -p ./etc/conda/deactivate.d
touch ./etc/conda/activate.d/env_vars.sh
touch ./etc/conda/deactivate.d/env_vars.sh
Edit ./etc/conda/activate.d/env_vars.sh as follows:
#!/bin/sh
export MY_KEY='secret-key-value'
export MY_FILE=/path/to/my/file/
Edit ./etc/conda/deactivate.d/env_vars.sh as follows:
#!/bin/sh
unset MY_KEY
unset MY_FILE
When you run conda activate analytics, the environment
variables MY_KEY and MY_FILE are set to the values you wrote into
the file. When you run conda deactivate, those variables are
erased.
Sharing an environment
You may want to share your environment with someone else---for
example, so they can re-create a test that you have done. To
allow them to quickly reproduce your environment, with all of its
packages and versions, give them a copy of your
environment.yml file.
Exporting the environment.yml file
If you already have an environment.yml file in your
current directory, it will be overwritten during this task.
Activate the environment to export: conda activate myenv
Replace myenv with the name of the environment.
Export your active environment to a new file:
conda env export > environment.yml
This file handles both the environment's pip packages
and conda packages.
