Python Dependency Manager Companion

===================== Managing environments ===================== With conda, you can create, export, list, remove, and update environments that have different versions of Python and/or packages installed in them. Switching or moving between environments is called activating the environment. You can also share an environment file. There are many options available for the commands described on this page. For a detailed reference on all available commands, see :doc:`commands <../../commands/index>`. Creating an environment with commands ===================================== Use the terminal for the following steps: #. To create an environment: .. code:: conda create --name <my-env> Replace ``<my-env>`` with the name of your environment. #. When conda asks you to proceed, type ``y``: .. code:: 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: .. code-block:: bash conda create -n myenv python=3.9 #. To create an environment with a specific package: .. code-block:: bash conda create -n myenv scipy or: .. code-block:: bash conda create -n myenv python conda install -n myenv scipy #. To create an environment with a specific version of a package: .. code-block:: bash conda create -n myenv scipy=0.17.3 or: .. code-block:: bash 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: .. code-block:: bash conda create -n myenv python=3.9 scipy=0.17.3 astroid babel .. tip:: 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 :ref:`create_default_packages <config-add-default-pkgs>` 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: .. code-block:: bash conda create --no-default-packages -n myenv python .. tip:: You can add much more to the ``conda create`` command. For details, run ``conda create --help``. .. _create-env-from-file: Creating an environment from an environment.yml file ==================================================== Use the terminal for the following steps: #. Create the environment from the ``environment.yml`` file: .. code:: conda env create -f environment.yml The first line of the ``yml`` file sets the new environment's name. For details see :ref:`Creating an environment file manually <create-env-file-manually>`. #. Activate the new environment: ``conda activate myenv`` #. Verify that the new environment was installed correctly: .. code:: conda env list You can also use ``conda info --envs``. .. _specifying-environment-platform: 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 :doc:`/commands/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: .. code:: conda create --platform osx-64 --name python-x64 python .. note:: 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 :ref:`dry-run-explicit` for more details. .. _specifying-location: 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: .. code-block:: $ cd project-directory $ conda activate ./env (env) project-directory $ .. _update-env: 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: .. code:: conda env update --file environment.yml --prune .. note:: The ``--prune`` option causes conda to remove any dependencies that are no longer required from the environment. .. _frozen-env: Freezing or locking an environment ================================== `CEP 22 <https://conda.org/learn/ceps/cep-0022>`__ introduced an environment marker file that will instruct ``conda`` not to allow modifications in the given environment. When attempting to add, update or remove a package, users will receive an error by default:: EnvironmentIsFrozenError: Cannot not modify '~/.conda/envs/my-env'. The environment is marked as frozen. You can ignore this error with the `--override-frozen` flag, at your own risk. As mentioned above, users can pass the ``--override-frozen`` flag, but this is really not recommended and should only be done by advanced users who are aware of the risks and would have the knowledge to fix potential complications derived from that operation. 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: .. code:: conda create --name myclone --clone myenv .. note:: 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: .. code:: conda info --envs In the environments list that displays, you should see both the source environment and the new copy. .. _identical-conda-envs: 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: .. code:: # 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 .. note:: 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. .. _activate-env: 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 :ref:`use the config API to set environment variables <set-env-vars>`. Activation prepends to PATH. This only takes effect when you have the environment active so it is local to a terminal session, not global. .. note:: When `installing Anaconda <http://docs.anaconda.com/anaconda/install.html>`_, 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. .. note:: 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 <https://docs.anaconda.com/anaconda/install/multi-user/>`__. To activate an environment: ``conda activate myenv`` .. note:: 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: .. code-block:: Python 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`` 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 <https://docs.microsoft.com/en-us/windows/win32/dlls/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 :ref:`troubleshooting <path-error>`. 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. Alternatively, ``conda init --condabin`` will not install a shell function in your profile. Instead, it will only add the ``$CONDA_PREFIX/condabin/`` directory to ``PATH``. This directory only contains the ``conda`` executable, so it should be minimally invasive. For more information, read the output from ``conda init --help``. One setting may be useful to you when using ``conda init`` is:: auto_activate: bool This setting controls whether or not conda activates the given default 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 default environment will be available until the environment is activated with ``conda activate``. The environment to be activated by default can be configured with:: default_activation_env: str 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 default 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 default 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 :ref:`troubleshooting directions <mkl_library>`. .. 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. .. note:: To simply return to the default 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``. .. _determine-current-env: 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: .. code:: 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: .. code:: conda info --envs OR .. code:: conda env list A list similar to the following is displayed: .. code:: 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: .. code-block:: bash conda list -n myenv * If the environment is activated, in your terminal window, run: .. code-block:: bash conda list * To see if a specific package is installed in an environment, in your terminal window, run: .. code-block:: bash conda list -n myenv scipy .. _pip-in-env: Using pip in an environment =========================== To use pip in your environment, in your terminal window, run: .. code-block:: bash 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. .. _set-env-vars: 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 :ref:`Windows <win-save-env-variables>` and :ref:`macOS or Linux <macos-linux-save-env-variables>`. 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``. .. _win-save-env-variables: 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-linux-save-env-variables: 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 file. The recommended way to export conda environments is using the ``conda export`` command, which supports multiple formats and provides enhanced functionality: Exporting environments with conda export ----------------------------------------- The ``conda export`` command provides a modern, plugin-based approach to environment export with support for multiple output formats. .. note:: The ``conda export`` command has been significantly enhanced in conda 25.7.x with a new plugin-based architecture, multiple export formats, and improved functionality. **Available Export Formats:** * ``environment-yaml`` - Cross-platform YAML format (default) * ``environment-json`` - Cross-platform JSON format * ``explicit`` - Platform-specific explicit URLs (CEP 23 compliant) * ``requirements`` - Platform-specific requirements format Basic Usage ~~~~~~~~~~~ Export the current environment to YAML format (default): .. code-block:: bash conda export > environment.yaml Export a specific environment by name: .. code-block:: bash conda export --name myenv --format=environment-yaml Export using automatic format detection: .. code-block:: bash conda export --file=environment.yaml # Auto-detects YAML format conda export --file=environment.json # Auto-detects JSON format conda export --file=explicit.txt # Auto-detects explicit format conda export --file=requirements.txt # Auto-detects requirements format Export Formats in Detail ~~~~~~~~~~~~~~~~~~~~~~~~~ **Environment YAML Format (Recommended for sharing)** Best for cross-platform environment sharing: .. code-block:: bash conda export --format=environment-yaml --file=environment.yaml Creates a file like: .. code-block:: yaml name: myenv channels: - conda-forge - defaults dependencies: - python=3.9 - numpy=1.21.0 - pandas=1.3.0 **Environment JSON Format** For programmatic processing or integration with tools: .. code-block:: bash conda export --format=environment-json --file=environment.json **Explicit Format** For exact environment reproduction on the same platform: .. code-block:: bash conda export --format=explicit --file=explicit.txt Creates a file with full package URLs: .. code-block:: text @EXPLICIT https://repo.anaconda.com/pkgs/main/osx-64/python-3.9.7-h88f2d9e_0.tar.bz2 https://repo.anaconda.com/pkgs/main/osx-64/numpy-1.21.0-py39h2e5f516_0.tar.bz2 **Requirements Format** For conda-compatible requirements files: .. code-block:: bash conda export --format=requirements --file=requirements.txt Creates a file like: .. code-block:: text python=3.9.7 numpy=1.21.0 pandas=1.3.0 Cross-Platform Compatibility ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ For maximum cross-platform compatibility, use the ``--from-history`` flag: .. code-block:: bash conda export --from-history --format=environment-yaml This exports only explicitly installed packages, excluding platform-specific dependencies. .. note:: The ``--from-history`` flag only works with structured formats (``environment-yaml``, ``environment-json``). It's not compatible with text formats (``explicit``, ``requirements``). Alternative: Traditional conda env export ------------------------------------------ You can also use the traditional ``conda env export`` command for YAML-only export: .. note:: 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`` .. note:: Replace ``myenv`` with the name of the environment. #. Export your active environment to a new file:: conda env export > environment.yml .. note:: This file handles both the environment's pip packages and conda packages. #. Email or copy the exported ``environment.yml`` file to the other person. .. _export-platform: Exporting an environment file across platforms ---------------------------------------------- If you want to make your environment file work across platforms, you can use the ``--from-history`` flag with either command: .. code-block:: bash # Enhanced export command (recommended) conda export --from-history --format=environment-yaml # Traditional command conda env export --from-history For example, if you create an environment and install Python and a package:: conda install python=3.7 codecov This will download and install numerous additional packages to solve for dependencies. This will introduce packages that may not be compatible across platforms. Both export commands with ``--from-history`` will export only the packages you specifically chose: .. code-block:: yaml name: env-name channels: - conda-forge - defaults dependencies: - python=3.7 - codecov prefix: /Users/username/anaconda3/envs/env-name .. note:: If you installed Anaconda 2019.10 on macOS, your prefix may be ``/Users/username/opt/envs/env-name``. .. _create-env-file-manually: Creating an environment file manually ------------------------------------- You can create an environment file (``environment.yml``) manually to share with others. EXAMPLE: A simple environment file: .. code:: name: stats dependencies: - numpy - pandas EXAMPLE: A more complex environment file: .. code:: name: stats2 channels: - javascript dependencies: - python=3.9 - bokeh=2.4.2 - conda-forge::numpy=1.21.* - nodejs=16.13.* - flask - pip - pip: - Flask-Testing .. note:: **Using wildcards** Note the use of the wildcard ``*`` when defining a few of the versions in the complex environment file. Keeping the major and minor versions fixed while allowing the patch to be any number allows you to use your environment file to get any bug fixes while still maintaining consistency in your environment. For more information on package installation values, see :doc:`../concepts/pkg-search`. **Specifying channels outside of "channels"** You may occasionally want to specify which channel conda will use to install a specific package. To accomplish this, use the `channel::package` syntax in `dependencies:`, as demonstrated above with `conda-forge::numpy` (version numbers optional). The specified channel does not need to be present in the `channels:` list, which is useful if you want some—but not *all*—packages installed from a community channel such as `conda-forge`. You can exclude the default channels by adding ``nodefaults`` to the channels list. .. code:: channels: - javascript - nodefaults This is equivalent to passing the ``--override-channels`` option to most ``conda`` commands. Adding ``nodefaults`` to the channels list in ``environment.yml`` is similar to removing ``defaults`` from the :ref:`channels list <config-channels>` in the ``.condarc`` file. However, changing ``environment.yml`` affects only one of your conda environments while changing ``.condarc`` affects them all. For details on creating an environment from this ``environment.yml`` file, see :ref:`create-env-from-file`. Restoring an environment ======================== Conda keeps a history of all the changes made to your environment, so you can easily "roll back" to a previous version. To list the history of each change to the current environment: ``conda list --revisions`` To restore environment to a previous revision: ``conda install --revision=REVNUM`` or ``conda install --rev REVNUM``. .. note:: Replace REVNUM with the revision number. Example: If you want to restore your environment to revision 8, run ``conda install --rev 8``. Removing an environment ======================= To remove an environment, in your terminal window, run: .. code:: conda remove --name myenv --all You may instead use ``conda env remove --name myenv``. To verify that the environment was removed, in your terminal window, run: .. code:: conda info --envs The environments list that displays should not show the removed environment. .. _dry-run-explicit: Create explicit lockfiles without creating an environment ========================================================= ``@EXPLICIT`` lockfiles allow you to (re)create environments without invoking the solver. They consist of an ``@EXPLICIT`` header plus a list of conda package URLs, optionally followed by their MD5 or SHA256 hash. They can be obtained from existing environments via ``conda list --explicit``, as seen in :ref:`identical-conda-envs`. But what if you only need the lockfile? Would you need create to a temporary environment first just to delete it later? Fortunately, there's a way: you can invoke ``conda`` in JSON mode and then process the output with ``jq``. .. tip:: You'll need ``jq`` in your system. If you don't have it yet, you can install it via ``conda`` (e.g. ``conda create -n jq jq``) or via your system package manager. The command looks like this for Linux and macOS (replace ``MATCHSPECS_GO_HERE`` with the relevant packages you want): .. code-block:: shell echo "@EXPLICIT" > explicit.txt CONDA_PKGS_DIRS=$(mktemp -d) conda create --dry-run MATCHSPECS_GO_HERE --json | jq -r '.actions.FETCH[] | .url + "#" + .md5' >> explicit.txt The syntax in Windows only needs some small changes: .. code-block:: shell echo "@EXPLICIT" > explicit.txt set "CONDA_PKGS_DIRS=%TMP%\conda-%RANDOM%" conda create --dry-run MATCHSPECS_GO_HERE --json | jq -r '.actions.FETCH[] | .url + "#" + .md5' >> explicit.txt set "CONDA_PKGS_DIRS=" The resulting ``explicit.txt`` can be used to create a new environment with: .. code:: conda create -n new-environment --file explicit.txt