Linux virtual packages show

Installing packages using pip and virtual environments¶

This guide discusses how to install packages using pip and a virtual environment manager: either venv for Python 3 or virtualenv for Python 2. These are the lowest-level tools for managing Python packages and are recommended if higher-level tools do not suit your needs.

This doc uses the term package to refer to a Distribution Package which is different from an Import Package that which is used to import modules in your Python source code.

Installing pip¶

pip is the reference Python package manager. It’s used to install and update packages. You’ll need to make sure you have the latest version of pip installed.

Debian and most other distributions include a python-pip package; if you want to use the Linux distribution-provided versions of pip, see Installing pip/setuptools/wheel with Linux Package Managers .

You can also install pip yourself to ensure you have the latest version. It’s recommended to use the system pip to bootstrap a user installation of pip:

Afterwards, you should have the latest version of pip installed in your user site:

The Python installers for Windows include pip. You can make sure that pip is up-to-date by running:

Afterwards, you should have the latest version of pip:

Installing virtualenv¶

If you are using Python 3.3 or newer, the venv module is the preferred way to create and manage virtual environments. venv is included in the Python standard library and requires no additional installation. If you are using venv, you may skip this section.

virtualenv is used to manage Python packages for different projects. Using virtualenv allows you to avoid installing Python packages globally which could break system tools or other projects. You can install virtualenv using pip.

Creating a virtual environment¶

venv (for Python 3) and virtualenv (for Python 2) allow you to manage separate package installations for different projects. They essentially allow you to create a “virtual” isolated Python installation and install packages into that virtual installation. When you switch projects, you can simply create a new virtual environment and not have to worry about breaking the packages installed in the other environments. It is always recommended to use a virtual environment while developing Python applications.

To create a virtual environment, go to your project’s directory and run venv. If you are using Python 2, replace venv with virtualenv in the below commands.

The second argument is the location to create the virtual environment. Generally, you can just create this in your project and call it env .

venv will create a virtual Python installation in the env folder.

You should exclude your virtual environment directory from your version control system using .gitignore or similar.

Activating a virtual environment¶

Before you can start installing or using packages in your virtual environment you’ll need to activate it. Activating a virtual environment will put the virtual environment-specific python and pip executables into your shell’s PATH .

You can confirm you’re in the virtual environment by checking the location of your Python interpreter:

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Альманах пакетных менеджеров Linux

Иногда может возникнуть вопрос: чьих этот файл, откуда вообще взялась эта библиотека? Удобный менеджер пакетов решает очень многие проблемы ОС. Можно с уверенностью сказать, что если вы подружитесь с МП, то подружитесь и с дистрибутивом как таковым. Причем важно освоить именно набор основных команд, и знать где найти дополнительную информацию.

Далее следует джентльменский набор необходимых для повседневной рутины команд основных Linux дистрибутивов: установить, обновить и удалить пакет, накатить обновления, проверить зависимости, установить принадлежность файла пакету и пр.

Debian и родственные

Популярность и образ дружественного к пользователю Linux дистрибутива сыграли с Ubuntu злую шутку. Некоторым новичкам кажется, что можно на нем делать все, что угодно без помощи командной строки. Это заблуждение и лучше от него поскорее избавиться.

То, что в примерах aptitude не значит, что он правильнее, чем apt-get . Для меня это всего лишь дело привычки.

Некоторые функции доступны с дополнительным МП dpkg .

Есть еще такое чудо — wajig. Несмотря на странное звучание, вполне годный МП с человеко-читабельным выводом информации на экран.

Настройка репозиториев производится правкой файла /etc/apt/sources.list

В целом ПМ Debian один из лучших, с которыми мне доводилось иметь дело.

Redhat и другие RPM дистрибутивы

RPM нельзя назвать образцовым пакетным менеджером, скорее это был кактус, который мыши употребляли в пищу со слезами на глазах. Затем появились более или менее вменяемые МП: yum , dnf , zypper и другие. Только что на сервере RHEL 7.4 yum за раз обновил более 700 пакетов и ничего при этом не сломал, неплохой результат я считаю.

Команды rpm на те случаи, когда использовать yum не с руки.

Чтобы настроить репозитории Yum , откройте файл /etc/yum.repos.d/*.repo , или используйте команду yum-config-manager .

Zypper

На SuSE Linux используется Zypper / YaST для управления пакетами, движок ZYpp крутится поверх RPM.

Можно использовать операторы и регулярные выражения.

Управление репозиториями производится командой zypper mr .

Pacman

Этот МП используется в Арче и Manjaro.

Движок поиска в базе данных поддерживает регулярные выражения.

Настройка репозиториев и зеркал производится из файла /etc/pacman.conf

Gentoo emerge

Конечно же это скорее умозрительный сценарий, чем реальный, так как сложно предположить, что красноглазый пользователь Gentoo Linux не знает необходимых опций emerge . Тем не менее, без этого альманах был бы неполным.

С дополнительными утилитами можно получить больше информации о файлах, ненужных пакетах и т. д.

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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 details, see Command reference .

conda activate and conda deactivate only work on conda 4.6 and later versions. For conda versions prior to 4.6, run:

Windows: activate or deactivate

Linux and macOS: source activate or source deactivate

Creating an environment with commands¶

By default, environments are installed into the envs directory in your conda directory. See Specifying a location for an environment or run conda create —help for information on specifying a different path.

Use the terminal or an Anaconda Prompt for the following steps:

To create an environment:

Replace myenv with the environment name.

When conda asks you to proceed, type y :

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:

To create an environment with a specific package:

To create an environment with a specific version of a package:

To create an environment with a specific version of Python and multiple packages:

Install all the programs that you want in this environment at the same time. Installing 1 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:

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 or an Anaconda Prompt for the following steps:

Create the environment from the environment.yml file:

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:

You can also use conda info —envs .

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 :

You then activate an environment created with a prefix using the same command used to activate environments created by name:

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:

This can result in long prefixes:

To remove this long prefix in your shell prompt, modify the env_prompt setting in your .condarc file:

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:

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:

The —prune option causes conda to remove any dependencies that are no longer required from the environment.

Cloning an environment¶

Use the terminal or an Anaconda Prompt for the following steps:

You can make an exact copy of an environment by creating a clone of it:

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:

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 or an Anaconda Prompt for the following steps:

Run conda list —explicit to produce a spec list such as:

To create this spec list as a file in the current working directory, run:

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:

To use the spec file to install its listed packages into an existing environment:

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 .

When installing Anaconda, you have the option to “Add Anaconda to my PATH environment variable.” This is not recommended because the add to PATH option 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 our entries. In the latter case, you do not. We do not recommend multi-user installs.

Activation prepends to PATH. This only takes effect when you have the environment active so it is local to a terminal session, not global.

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:

If you receive this warning, you need to activate your environment. To do so on Windows, run: c:\Anaconda3\Scripts\activate base in Anaconda Prompt.

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:

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:

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:

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 .

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 or an Anaconda Prompt 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:

If you do not see this, run:

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:

To re-enable this option:

Viewing a list of your environments¶

To see a list of all of your environments, in your terminal window or an Anaconda Prompt, run:

A list similar to the following is displayed:

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 or an Anaconda Prompt, run:

If the environment is activated, in your terminal window or an Anaconda Prompt, run:

To see if a specific package is installed in an environment, in your terminal window or an Anaconda Prompt, run:

Using pip in an environment¶

To use pip in your environment, in your terminal window or an Anaconda Prompt, run:

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.

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.

Once pip has been used, conda will be unaware of the changes.

To install additional conda packages, it is best to recreate the environment.

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:

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 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:

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 Anaconda Prompt by running in the command shell %CONDA_PREFIX% .

Enter that directory and create these subdirectories and files:

Edit .\etc\conda\activate.d\env_vars.bat as follows:

Edit .\etc\conda\deactivate.d\env_vars.bat as follows:

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:

Edit ./etc/conda/activate.d/env_vars.sh as follows:

Edit ./etc/conda/deactivate.d/env_vars.sh as follows:

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:

This file handles both the environment’s pip packages and conda packages.

Email or copy the exported environment.yml file to the other person.

Exporting an environment file across platforms¶

If you want to make your environment file work across platforms, you can use the conda env export —from-history flag. This will only include packages that you’ve explicitly asked for, as opposed to including every package in your environment.

For example, if you create an environment and install Python and a package:

This will download and install numerous additional packages to solve for dependencies. This will introduce packages that may not be compatible across platforms.

If you use conda env export , it will export all of those packages. However, if you use conda env export —from-history , it will only export those you specifically chose:

If you installed Anaconda 2019.10 on macOS, your prefix may be /Users/username/opt/envs/env-name .

Creating an environment file manually¶

You can create an environment file ( environment.yml ) manually to share with others.

EXAMPLE: A simple environment file:

EXAMPLE: A more complex environment file:

Note the use of the wildcard * when defining the patch version number. Defining the version number by fixing the major and minor version numbers while allowing the patch version number to vary allows us to use our environment file to update our environment to get any bug fixes whilst still maintaining consistency of software environment.

You can exclude the default channels by adding nodefaults to the channels list.

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 channels list 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 Creating an environment from an environment.yml 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 .

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 or an Anaconda Prompt, run:

You may instead use conda env remove —name myenv .

To verify that the environment was removed, in your terminal window or an Anaconda Prompt, run:

The environments list that displays should not show the removed environment.

© Copyright 2017, Anaconda, Inc Revision c1579681 .

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