# pip: PyPI Package Manager
pip is the most widely-used package manager for the Python Package Index, installed by default with recent versions of Python.
# Install Packages
To install the latest version of a package named SomePackage :
To install a specific version of a package:
To specify a minimum version to install for a package:
If commands shows permission denied error on Linux/Unix then use sudo with the commands
# Install from requirements files
Each line of the requirements file indicates something to be installed, and like arguments to pip install, Details on the format of the files are here: Requirements File Format
After install the package you can check it using freeze command:
# To list all packages installed using pip
To list installed packages:
To list outdated packages, and show the latest version available:
# Upgrade Packages
will upgrade package SomePackage and all its dependencies. Also, pip automatically removes older version of the package before upgrade.
To upgrade pip itself, do
on Windows machines.
# Uninstall Packages
To uninstall a package:
# Updating all outdated packages on Linux
pip doesn’t current contain a flag to allow a user to update all outdated packages in one shot. However, this can be accomplished by piping commands together in a Linux environment:
This command takes all packages in the local virtualenv and checks if they are outdated. From that list, it gets the package name and then pipes that to a pip install -U command. At the end of this process, all local packages should be updated.
# Updating all outdated packages on Windows
pip doesn’t current contain a flag to allow a user to update all outdated packages in one shot. However, this can be accomplished by piping commands together in a Windows environment:
This command takes all packages in the local virtualenv and checks if they are outdated. From that list, it gets the package name and then pipes that to a pip install -U command. At the end of this process, all local packages should be updated.
# Create a requirements.txt file of all packages on the system
pip assists in creating requirements.txt files by providing the freeze
This will save a list of all packages and their version installed on the system to a file named requirements.txt in the current folder.
# Create a requirements.txt file of packages only in the current virtualenv
pip assists in creating requirements.txt files by providing the freeze
(opens new window) parameter will only output a list of packages and versions that are installed locally to a virtualenv. Global packages will not be listed.
# Using a certain Python version with pip
If you have both Python 3 and Python 2 installed, you can specify which version of Python you would like pip to use. This is useful when packages only support Python 2 or 3 or when you wish to test with both.
If you want to install packages for Python 2, run either:
If you would like to install packages for Python 3, do:
You can also invoke installation of a package to a specific python installation with:
On OS-X/Linux/Unix platforms it is important to be aware of the distinction between the system version of python, (which upgrading make render your system inoperable), and the user version(s) of python. You may, depending on which you are trying to upgrade, need to prefix these commands with sudo and input a password.
Likewise on Windows some python installations, especially those that are a part of another package, can end up installed in system directories — those you will have to upgrade from a command window running in Admin mode — if you find that it looks like you need to do this it is a very good idea to check which python installation you are trying to upgrade with a command such as python -c"import sys;print(sys.path);" or py -3.5 -c"import sys;print(sys.path);" you can also check which pip you are trying to run with pip —version
On Windows, if you have both python 2 and python 3 installed, and on your path and your python 3 is greater than 3.4 then you will probably also have the python launcher py on your system path. You can then do tricks like:
If you are running & maintaining multiple versions of python I would strongly recommend reading up about the python virtualenv or venv virtual enviroments
(opens new window) which allow you to isolate both the version of python and which packages are present.
# Installing packages not yet on pip as wheels
Many, pure python, packages are not yet available on the Python Package Index as wheels but still install fine. However, some packages on Windows give the dreaded vcvarsall.bat not found error.
The problem is that the package that you are trying to install contains a C or C++ extension and is not currently available as a pre-built wheel from the python package index, pypi, and on windows you do not have the tool chain needed to build such items.
The simplest answer is to go to Christoph Gohlke’s
(opens new window) excellent site and locate the appropriate version of the libraries that you need. By appropriate in the package name a -cp**NN******- has to match your version of python, i.e. if you are using windows 32 bit python even on win64 the name must include -win32- and if using the 64 bit python it must include -win_amd64- and then the python version must match, i.e. for Python 34 the filename must include -cp34-, etc. this is basically the magic that pip does for you on the pypi site.
Alternatively, you need to get the appropriate windows development kit for the version of python that you are using, the headers for any library that the package you are trying to build interfaces to, possibly the python headers for the version of python, etc.
Python 2.7 used Visual Studio 2008, Python 3.3 and 3.4 used Visual Studio 2010, and Python 3.5+ uses Visual Studio 2015.
Then you may need to locate the header files, at the matching revision for any libraries that your desired package links to and download those to an appropriate locations.
Finally you can let pip do your build — of course if the package has dependencies that you don’t yet have you may also need to find the header files for them as well.
Alternatives: It is also worth looking out, both on pypi or Christop’s site, for any slightly earlier version of the package that you are looking for that is either pure python or pre-built for your platform and python version and possibly using those, if found, until your package does become available. Likewise if you are using the very latest version of python you may find that it takes the package maintainers a little time to catch up so for projects that really need a specific package you may have to use a slightly older python for the moment. You can also check the packages source site to see if there is a forked version that is available pre-built or as pure python and searching for alternative packages that provide the functionality that you require but are available — one example that springs to mind is the Pillow
(opens new window) , actively maintained, drop in replacement for PIL
(opens new window) currently not updated in 6 years and not available for python 3.
Afterword, I would encourage anybody who is having this problem to go to the bug tracker for the package and add to, or raise if there isn’t one already, a ticket politely requesting that the package maintainers provide a wheel on pypi for your specific combination of platform and python, if this is done then normally things will get better with time, some package maintainers don’t realise that they have missed a given combination that people may be using.
# Note on Installing Pre-Releases
Pip follows the rules of Semantic Versioning
(opens new window) and by default prefers released packages over pre-releases. So if a given package has been released as V0.98 and there is also a release candidate V1.0-rc1 the default behaviour of pip install will be to install V0.98 — if you wish to install the release candidate, you are advised to test in a virtual environment first, you can enable do so with —pip install —pre package-name or —pip install —pre —upgrade package-name. In many cases pre-releases or release candidates may not have wheels built for all platform & version combinations so you are more likely to encounter the issues above.
# Note on Installing Development Versions
You can also use pip to install development versions of packages from github and other locations, since such code is in flux it is very unlikely to have wheels built for it, so any impure packages will require the presence of the build tools, and they may be broken at any time so the user is strongly encouraged to only install such packages in a virtual environment.
Three options exist for such installations:
- Download compressed snapshot, most online version control systems have the option to download a compressed snapshot of the code. This can be downloaded manually and then installed with pip install path/to/downloaded/file note that for most compression formats pip will handle unpacking to a cache area, etc.
- Let pip handle the download & install for you with: pip install URL/of/package/repository — you may also need to use the —trusted-host , —client-cert and/or —proxy flags for this to work correctly, especially in a corporate environment. e.g:
Note the git+ prefix to the URL.
- Clone the repository using git , mercurial or other acceptable tool, preferably a DVCS tool, and use pip install path/to/cloned/repo — this will both process any requires.text file and perform the build and setup steps, you can manually change directory to your cloned repository and run pip install -r requires.txt and then python setup.py install to get the same effect. The big advantages of this approach is that while the initial clone operation may take longer than the snapshot download you can update to the latest with, in the case of git: git pull origin master and if the current version contains errors you can use pip uninstall package-name then use git checkout commands to move back through the repository history to earlier version(s) and re-try.
# Syntax
-
install
- Go to file T
- Go to line L
- Copy path
- Copy permalink
- Open with Desktop
- View raw
- Copy raw contents Copy raw contents
- using the —proxy command-line option to specify a proxy in the form scheme://[user:passwd@]proxy.server:port
- using proxy in a :ref:`config-file`
- by setting the standard environment-variables http_proxy , https_proxy and no_proxy .
- using the environment variable PIP_USER_AGENT_USER_DATA to include a JSON-encoded string in the user-agent variable used in pip’s requests.
- eager : upgrades all dependencies regardless of whether they still satisfy the new parent requirements
- only-if-needed : upgrades a dependency only if it does not satisfy the new parent requirements
- pip install SomePackage : will not upgrade the existing SomePackage or SomeDependency .
- pip install —upgrade SomePackage : will upgrade SomePackage , but not SomeDependency (unless a minimum requirement is not met).
- pip install —upgrade SomePackage —upgrade-strategy=eager : upgrades both SomePackage and SomeDependency .
- When globally installed packages are on the python path, and they conflict with the installation requirements, they are ignored, and not uninstalled.
- When globally installed packages are on the python path, and they satisfy the installation requirements, pip does nothing, and reports that requirement is satisfied (similar to how global packages can satisfy requirements when installing packages in a —system-site-packages virtualenv).
- pip will not perform a —user install in a —no-site-packages virtualenv (i.e. the default kind of virtualenv), due to the user site not being on the python path. The installation would be pointless.
- In a —system-site-packages virtualenv, pip will not install a package that conflicts with a package in the virtualenv site-packages. The —user installation would lack sys.path precedence and be pointless.
- The pip code assumes that it is in sole control of the global state of the program. pip manages things like the logging system configuration, or the values of the standard IO streams, without considering the possibility that user code might be affected.
- pip’s code is not thread safe. If you were to run pip in a thread, there is no guarantee that either your code or pip’s would work as you expect.
- pip assumes that once it has finished its work, the process will terminate. It doesn’t need to handle the possibility that other code will continue to run after that point, so (for example) calling pip twice in the same process is likely to have issues.
- packaging — Utilities to work with standard package metadata (versions, requirements, etc.)
- setuptools (specifically pkg_resources ) — Functions for querying what packages the user has installed on their system.
- distlib — Packaging and distribution utilities (including functions for interacting with PyPI).
- It will reduce inconsistency: it will no longer install a combination of packages that is mutually inconsistent. In older versions of pip, it is possible for pip to install a package which does not satisfy the declared requirements of another installed package. For example, in pip 20.0, pip install «six<1.12» «virtualenv==20.0.2» does the wrong thing, “successfully” installing six==1.11 , even though virtualenv==20.0.2 requires six>=1.12.0,<2 (defined here). The new resolver, instead, outright rejects installing anything if it gets that input.
- It will be stricter — if you ask pip to install two packages with incompatible requirements, it will refuse (rather than installing a broken combination, like it did in previous versions).
- Constraints don’t override the existing requirements; they simply constrain what versions are visible as input to the resolver (see :issue:`9020` )
- Providing an editable requirement ( -e . ) does not cause pip to ignore version specifiers or constraints (see :issue:`8076` ), and if you have a conflict between a pinned requirement and a local directory then pip will indicate that it cannot find a version satisfying both (see :issue:`8307` )
- Hash-checking mode requires that all requirements are specified as a == match on a version and may not work well in combination with constraints (see :issue:`9020` and :issue:`8792` )
- If necessary to satisfy constraints, pip will happily reinstall packages, upgrading or downgrading, without needing any additional command-line options (see :issue:`8115` and :doc:`development/architecture/upgrade-options` )
- Unnamed requirements are not allowed as constraints (see :issue:`6628` and :issue:`8210` )
- Links are not allowed as constraints (see :issue:`8253` )
- Constraints cannot have extras (see :issue:`6628` )
- If you use pip to install your software, try out the new resolver and let us know if it works for you with pip install . Try:
- installing several packages simultaneously
- re-creating an environment using a requirements.txt file
- using pip install —force-reinstall to check whether it does what you think it should
- using constraints files
- the «Setups to test with special attention» and «Examples to try» below
Troubleshoot and try these workarounds if necessary.
- If pip is taking longer to install packages, read :doc:`Dependency resolution backtracking <topics/dependency-resolution>` for ways to reduce the time pip spends backtracking due to dependency conflicts.
- If you don’t want pip to actually resolve dependencies, use the —no-deps option. This is useful when you have a set of package versions that work together in reality, even though their metadata says that they conflict. For guidance on a long-term fix, read :ref:`Fixing conflicting dependencies` .
- If you run into resolution errors and need a workaround while you’re fixing their root causes, you can choose the old resolver behavior using the flag —use-deprecated=legacy-resolver . This will work until we release pip 21.0 (see :ref:`Deprecation timeline for 2020 resolver changes` ).
Please report bugs through the resolver testing survey.
Setups to test with special attention
- Requirements files with 100+ packages
- Installation workflows that involve multiple requirements files
- Requirements files that include hashes ( :ref:`hash-checking mode` ) or pinned dependencies (perhaps as output from pip-compile within pip-tools )
- Using :ref:`Constraints Files`
- Continuous integration/continuous deployment setups
- Installing from any kind of version control systems (i.e., Git, Subversion, Mercurial, or CVS), per :doc:`topics/vcs-support`
- Installing from source code held in local directories
Examples to try
- pip install
- pip uninstall
- pip check
- pip cache
Specific things we’d love to get feedback on:
- Cases where the new resolver produces the wrong result, obviously. We hope there won’t be too many of these, but we’d like to trap such bugs before we remove the legacy resolver.
- Cases where the resolver produced an error when you believe it should have been able to work out what to do.
- Cases where the resolver gives an error because there’s a problem with your requirements, but you need better information to work out what’s wrong.
- If you have workarounds to address issues with the current resolver, does the new resolver let you remove those workarounds? Tell us!
Please let us know through the resolver testing survey.
We plan for the resolver changeover to proceed as follows, using :ref:`Feature Flags` and following our :ref:`Release Cadence` :
- pip 20.1: an alpha version of the new resolver was available, opt-in, using the optional flag —unstable-feature=resolver . pip defaulted to legacy behavior.
- pip 20.2: a beta of the new resolver was available, opt-in, using the flag —use-feature=2020-resolver . pip defaulted to legacy behavior. Users of pip 20.2 who want pip to default to using the new resolver can run pip config set global.use-feature 2020-resolver (for more on that and the alternate PIP_USE_FEATURE environment variable option, see issue 8661).
- pip 20.3: pip defaults to the new resolver in Python 3 environments, but a user can opt-out and choose the old resolver behavior, using the flag —use-deprecated=legacy-resolver . In Python 2 environments, pip defaults to the old resolver, and the new one is available using the flag —use-feature=2020-resolver .
- pip 21.0: pip uses new resolver by default, and the old resolver is no longer supported. It will be removed after a currently undecided amount of time, as the removal is dependent on pip’s volunteer maintainers’ availability. Python 2 support is removed per our :ref:`Python 2 Support` policy.
Since this work will not change user-visible behavior described in the pip documentation, this change is not covered by the :ref:`Deprecation Policy` .
Context and followup
As discussed in our announcement on the PSF blog, the pip team are in the process of developing a new «dependency resolver» (the part of pip that works out what to install based on your requirements).
We’re tracking our rollout in :issue:`6536` and you can watch for announcements on the low-traffic packaging announcements list and the official Python blog.
Менеджер пакетов pip: разбираемся с установкой дополнительных библиотек в Python
Ведь не все пакеты нужны в повседневной практике или отдельном проекте, да и места они занимают не мало. Для этих целей создан удаленный репозиторий модулей https://pypi.org/ , в котором на сегодня имеется более 260 тыс. проектов на все случаи практики программирования. Вам не обязательно создавать код с нуля, так как под многие задачи уже имеется соответствующий пакет.
Работа с этим хранилищем расширений осуществляется через команду pip . Имеется и другой установщик easy_install , но он применяется существенно реже. Таким образом, пакетный менеджер pip необходим для установки, обновления, удаления и управления модулями языка Python.
2. Подготовительные мероприятия
Как видно из ответа, на данном ПК используется python версии 3.8 и pip версии 20.2.3 .
В некоторых случаях (актуально для пользователей Linux или macOS ) требуется применять команду pip3 (если в результате выполнения pip определяет, что у вас установлен python версии 2 по умолчанию). Это связано с тем, что на *nix системах присутствуют сразу обе версии языка.
Также если на вашем компьютере имеется несколько версий языка Python (например, 3.6 , 3.8 , 3.9 ), то менеджер пакетов может применяться отдельно для каждой из них:
3. Установка и удаление пакетов
При разработке сложных проектов может понадобиться установка большого количества модулей. Постоянно их скачивать из репозитория PyPi трудоемко. Для этого разработан способ загрузки пакетов локально. Они могут находиться в архивах ( *.tar.gz ) или специальных файлах с расширением .whl . Это удобно и в том случае, если нет доступа в интернет у выбранной машины, и вы заранее создали пакет со всеми необходимыми библиотеками.
Для примера запакуем модуль numpy в «колесо» ( wheel ) и установим его оттуда.
Вначале мы создали специальный локальный пакет NumPy и поместили его в текущую папку (о чем свидетельствует точка). В директории создался файл numpy-1.19.2-cp38-cp38-win32.whl . На его основании даже без интернета мы легко сможем установить данную библиотеку. Команда «—no-index» говорит о том, чтобы мы не искали модуль в репозитории PyPi , а —find-links принудительно указывает место расположения пакета. Когда речь идет о сотне пакетов, это очень удобно. Правда для этого необходимо освоить еще один инструмент: набор зависимостей (о нем – следующий раздел).
Рассмотрим вопрос удаления модулей. Если требуется удалить один пакет, то делается это по аналогии с установкой:
Читайте также
4. Файлы требований для управления пакетами
Серьезные и многоуровневые приложения никогда не обходятся одной библиотекой. Даже когда вы устанавливали тот же NumPy , вы могли заметить, что помимо самого модуля скачивались дополнительные пакеты, которые мы не запрашивали. Естественно они необходимы для правильной работы NumPy . Но откуда известно, что они нужны?
Pip — The complete reference guide
pip is the package manager for python.pip can be used to install python libraries from PyPI. In other words, pip is the npm of python . We use pip to install and manage python libraries that are not part of the python standard library.
Motivation:
Any python developer predeminantly uses pip day in and out.However, the usage is limited to just install and occasionally upgrade.
This article is a consolidated non-exhaustive list of all the pip commands every python developer should know. This could be a reference for any future pip commands.
Commands:
Install — plain install:
The install command is used to install the specified library from the pypi package. I am not giving the output of pip commands here as they are well known.
Install — per-user:
This may come in handy in the following scenarios
- You are not using a virtual environment
- You are using a shared PC
- You don’t have admin previleges to install your packages at system level
pip packages are installed to the system directories by default.In case of linux it is(/usr/local/lib/python3.8/dist-packages). When installed with —user flag, it is installed for a specific user.
Here is the code snippet to get sitepackages and usersitepackages.
Install — with proxy:
If your system is located behind a proxy and you are unable to download from PyPI directly, you could use a proxy provided by your organization.
Install — upgrade:
This command upgrades the existing pip library.
Install — from a different host:
Install from a different host apart from PyPI package.
Install — from requirements.txt:
Install from requirements.txt file.
Install — editable mode:
Install a local package in editable mode. This is useful if you have a local package and you would like to use it. The local package is still under development and any changes to the package will reflect.
Install —to a target location:
Install package to a specific location
Installs matplotlib to the current directory. This could be useful if you are uploading your project to AWS Lambda .
Install — from a local directory:
Install from a local directory and do not scan PyPI.
Here, the find links points to current directory as it has the wheel file for certifi library.The —no-index flag specifies not to look in the PyPI package.
Install — from VCS:
The libraries can be installed directly from a version control system like git.This is useful for huge organizations who have their projects as dependencies. If the access to the repository is restricted, this can be installed directly from git.
Uninstall
To uninstall a library..
Version:
Check pip version
Get information about an installed package. This includes the version, the location where the package is installed and its dependencies.
Freeze:
Predominantly used as an input to requirements.txt file.
This could be very helpful if you are using a virtualenv and want to copy all your dependencies to requirements.txt .
Lists all the installed packages. If executed inside a virtualenv, it will list all the packages installed in the virtual env.
Download:
Download the python libraries but don’t install them
The download command downloads the specified library’s wheel files in addition to their dependecies. The above command should give the following output.By default, the files are downloaded to the current directory.
Search:
pip search searches for python packages. The default location it searches is the PyPI package (https://pypi.org/pypi).
This does not work now.
However, this could be useful if you have libraries hosted internally in your organization like artifcatory .
The default URL could be overridden by the -i flag.
Check:
Checks compatibility for installed packages
Cache:
pip usually stores all the libraries installed in cache.
The wheel files are cached inside dir directory. Whenever a pip install is triggered, it checks the local cache and then connects to PyPI.
The idea behind the pip cache is simple ,when you install a Python package using pip for the first time ,it gets saved on the cache .If you try to download/install the same version of the package on a second time ,pip will just use the local cached copy
Please note that this will not work in a virtual environment as there may not be a need to cache libraries .
Disable cache :
Install package without saving to cache.
Displays help for pip commands.
Verbose:
Run pip in verbose mode for additional information.
This produces a bunch of output with overwhelming information.
Disable pip version check:
Disables the periodic check to PyPI if a new version of pip is available.
I would recommend not disabling this as you may miss important updates from PyPI.
-
— Install packages
Output installed packages in requirements format
List installed packages
Show information about installed packages
Search PyPI for packages
Build wheels from your requirements
Zip individual packages (deprecated)
Unzip individual packages (deprecated)
Create pybundles (deprecated)
Show help for commands
# Remarks
Sometimes, pip will perfom a manual compilation of native code. On Linux python will automatically choose an available C compiler on your system. Refer to the table below for the required Visual Studio/Visual C++ version on Windows (newer versions will not work.).
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pip is a command line program. When you install pip, a pip command is added to your system, which can be run from the command prompt as follows:
pip supports installing from PyPI, version control, local projects, and directly from distribution files.
The most common scenario is to install from PyPI using :ref:`Requirement Specifiers`
For more information and examples, see the :ref:`pip install` reference.
Basic Authentication Credentials
Using a Proxy Server
When installing packages from PyPI, pip requires internet access, which in many corporate environments requires an outbound HTTP proxy server.
pip can be configured to connect through a proxy server in various ways:
«Requirements files» are files containing a list of items to be installed using :ref:`pip install` like so:
Details on the format of the files are here: :ref:`requirements-file-format` .
Logically, a Requirements file is just a list of :ref:`pip install` arguments placed in a file. Note that you should not rely on the items in the file being installed by pip in any particular order.
Requirements files can also be served via a URL, e.g. http://example.com/requirements.txt besides as local files, so that they can be stored and served in a centralized place.
In practice, there are 4 common uses of Requirements files:
Requirements files are used to hold the result from :ref:`pip freeze` for the purpose of achieving :doc:`topics/repeatable-installs` . In this case, your requirement file contains a pinned version of everything that was installed when pip freeze was run.
Requirements files are used to force pip to properly resolve dependencies. pip 20.2 and earlier doesn’t have true dependency resolution, but instead simply uses the first specification it finds for a project. E.g. if pkg1 requires pkg3>=1.0 and pkg2 requires pkg3>=1.0,<=2.0 , and if pkg1 is resolved first, pip will only use pkg3>=1.0 , and could easily end up installing a version of pkg3 that conflicts with the needs of pkg2 . To solve this problem, you can place pkg3>=1.0,<=2.0 (i.e. the correct specification) into your requirements file directly along with the other top level requirements. Like so:
Requirements files are used to force pip to install an alternate version of a sub-dependency. For example, suppose ProjectA in your requirements file requires ProjectB , but the latest version (v1.3) has a bug, you can force pip to accept earlier versions like so:
Requirements files are used to override a dependency with a local patch that lives in version control. For example, suppose a dependency SomeDependency from PyPI has a bug, and you can’t wait for an upstream fix. You could clone/copy the src, make the fix, and place it in VCS with the tag sometag . You’d reference it in your requirements file with a line like so:
If SomeDependency was previously a top-level requirement in your requirements file, then replace that line with the new line. If SomeDependency is a sub-dependency, then add the new line.
It’s important to be clear that pip determines package dependencies using install_requires metadata, not by discovering requirements.txt files embedded in projects.
Constraints files are requirements files that only control which version of a requirement is installed, not whether it is installed or not. Their syntax and contents is a subset of :ref:`Requirements Files` , with several kinds of syntax not allowed: constraints must have a name, they cannot be editable, and they cannot specify extras. In terms of semantics, there is one key difference: Including a package in a constraints file does not trigger installation of the package.
Use a constraints file like so:
Constraints files are used for exactly the same reason as requirements files when you don’t know exactly what things you want to install. For instance, say that the «helloworld» package doesn’t work in your environment, so you have a local patched version. Some things you install depend on «helloworld», and some don’t.
One way to ensure that the patched version is used consistently is to manually audit the dependencies of everything you install, and if «helloworld» is present, write a requirements file to use when installing that thing.
Constraints files offer a better way: write a single constraints file for your organisation and use that everywhere. If the thing being installed requires «helloworld» to be installed, your fixed version specified in your constraints file will be used.
Constraints file support was added in pip 7.1. In :ref:`Resolver changes 2020` we did a fairly comprehensive overhaul, removing several undocumented and unsupported quirks from the previous implementation, and stripped constraints files down to being purely a way to specify global (version) limits for packages.
Same as requirements files, constraints files can also be served via a URL, e.g. http://example.com/constraints.txt, so that your organization can store and serve them in a centralized place.
Installing from Wheels
«Wheel» is a built, archive format that can greatly speed installation compared to building and installing from source archives. For more information, see the Wheel docs , PEP 427, and PEP 425.
pip prefers Wheels where they are available. To disable this, use the :ref:`—no-binary <install_—no-binary>` flag for :ref:`pip install` .
If no satisfactory wheels are found, pip will default to finding source archives.
To install directly from a wheel archive:
To include optional dependencies provided in the provides_extras metadata in the wheel, you must add quotes around the install target name:
In the future, the path[extras] syntax may become deprecated. It is recommended to use PEP 508 syntax wherever possible.
For the cases where wheels are not available, pip offers :ref:`pip wheel` as a convenience, to build wheels for all your requirements and dependencies.
:ref:`pip wheel` requires the wheel package to be installed, which provides the «bdist_wheel» setuptools extension that it uses.
To build wheels for your requirements and all their dependencies to a local directory:
And then to install those requirements just using your local directory of wheels (and not from PyPI):
pip is able to uninstall most packages like so:
pip also performs an automatic uninstall of an old version of a package before upgrading to a newer version.
For more information and examples, see the :ref:`pip uninstall` reference.
To list installed packages:
To list outdated packages, and show the latest version available:
To show details about an installed package:
For more information and examples, see the :ref:`pip list` and :ref:`pip show` reference pages.
Searching for Packages
pip can search PyPI for packages using the pip search command:
The query will be used to search the names and summaries of all packages.
For more information and examples, see the :ref:`pip search` reference.
pip comes with support for command line completion in bash, zsh and fish.
To setup for bash:
To setup for zsh:
To setup for fish:
To setup for powershell:
Alternatively, you can use the result of the completion command directly with the eval function of your shell, e.g. by adding the following to your startup file:
Installing from local packages
In some cases, you may want to install from local packages only, with no traffic to PyPI.
First, download the archives that fulfill your requirements:
Note that pip download will look in your wheel cache first, before trying to download from PyPI. If you’ve never installed your requirements before, you won’t have a wheel cache for those items. In that case, if some of your requirements don’t come as wheels from PyPI, and you want wheels, then run this instead:
«Only if needed» Recursive Upgrade
pip install —upgrade now has a —upgrade-strategy option which controls how pip handles upgrading of dependencies. There are 2 upgrade strategies supported:
The default strategy is only-if-needed . This was changed in pip 10.0 due to the breaking nature of eager when upgrading conflicting dependencies.
It is important to note that —upgrade affects direct requirements (e.g. those specified on the command-line or via a requirements file) while —upgrade-strategy affects indirect requirements (dependencies of direct requirements).
As an example, say SomePackage has a dependency, SomeDependency , and both of them are already installed but are not the latest available versions:
As an historic note, an earlier «fix» for getting the only-if-needed behaviour was:
A proposal for an upgrade-all command is being considered as a safer alternative to the behaviour of eager upgrading.
With Python 2.6 came the «user scheme» for installation, which means that all Python distributions support an alternative install location that is specific to a user. The default location for each OS is explained in the python documentation for the site.USER_BASE variable. This mode of installation can be turned on by specifying the :ref:`—user <install_—user>` option to pip install .
Moreover, the «user scheme» can be customized by setting the PYTHONUSERBASE environment variable, which updates the value of site.USER_BASE .
To install «SomePackage» into an environment with site.USER_BASE customized to ‘/myappenv’, do the following:
pip install —user follows four rules:
To make the rules clearer, here are some examples:
From within a —no-site-packages virtualenv (i.e. the default kind):
From within a —system-site-packages virtualenv where SomePackage==0.3 is already installed in the virtualenv:
From within a real python, where SomePackage is not installed globally:
From within a real python, where SomePackage is installed globally, but is not the latest version:
From within a real python, where SomePackage is installed globally, and is the latest version:
Fixing conflicting dependencies
Using pip from your program
As noted previously, pip is a command line program. While it is implemented in Python, and so is available from your Python code via import pip , you must not use pip’s internal APIs in this way. There are a number of reasons for this:
This does not mean that the pip developers are opposed in principle to the idea that pip could be used as a library — it’s just that this isn’t how it was written, and it would be a lot of work to redesign the internals for use as a library, handling all of the above issues, and designing a usable, robust and stable API that we could guarantee would remain available across multiple releases of pip. And we simply don’t currently have the resources to even consider such a task.
What this means in practice is that everything inside of pip is considered an implementation detail. Even the fact that the import name is pip is subject to change without notice. While we do try not to break things as much as possible, all the internal APIs can change at any time, for any reason. It also means that we generally won’t fix issues that are a result of using pip in an unsupported way.
It should also be noted that installing packages into sys.path in a running Python process is something that should only be done with care. The import system caches certain data, and installing new packages while a program is running may not always behave as expected. In practice, there is rarely an issue, but it is something to be aware of.
Having said all of the above, it is worth covering the options available if you decide that you do want to run pip from within your program. The most reliable approach, and the one that is fully supported, is to run pip in a subprocess. This is easily done using the standard subprocess module:
If you want to process the output further, use one of the other APIs in the module. We are using freeze here which outputs installed packages in requirements format.:
If you don’t want to use pip’s command line functionality, but are rather trying to implement code that works with Python packages, their metadata, or PyPI, then you should consider other, supported, packages that offer this type of ability. Some examples that you could consider include:
Changes to the pip dependency resolver in 20.3 (2020)
pip 20.3 has a new dependency resolver, on by default for Python 3 users. (pip 20.1 and 20.2 included pre-release versions of the new dependency resolver, hidden behind optional user flags.) Read below for a migration guide, how to invoke the legacy resolver, and the deprecation timeline. We also made a two-minute video explanation you can watch.
We will continue to improve the pip dependency resolver in response to testers’ feedback. Please give us feedback through the resolver testing survey.
The big change in this release is to the pip dependency resolver within pip.
Computers need to know the right order to install pieces of software («to install x , you need to install y first»). So, when Python programmers share software as packages, they have to precisely describe those installation prerequisites, and pip needs to navigate tricky situations where it’s getting conflicting instructions. This new dependency resolver will make pip better at handling that tricky logic, and make pip easier for you to use and troubleshoot.
The most significant changes to the resolver are:
So, if you have been using workarounds to force pip to deal with incompatible or inconsistent requirements combinations, now’s a good time to fix the underlying problem in the packages, because pip will be stricter from here on out.
This also means that, when you run a pip install command, pip only considers the packages you are installing in that command, and may break already-installed packages. It will not guarantee that your environment will be consistent all the time. If you pip install x and then pip install y , it’s possible that the version of y you get will be different than it would be if you had run pip install x y in a single command. We are considering changing this behavior (per :issue:`7744` ) and would like your thoughts on what pip’s behavior should be; please answer our survey on upgrades that create conflicts.
We are also changing our support for :ref:`Constraints Files` , editable installs, and related functionality. We did a fairly comprehensive overhaul and stripped constraints files down to being purely a way to specify global (version) limits for packages, and so some combinations that used to be allowed will now cause errors. Specifically:
Per our :ref:`Python 2 Support` policy, pip 20.3 users who are using Python 2 will use the legacy resolver by default. Python 2 users should upgrade to Python 3 as soon as possible, since in pip 21.0 in January 2021, pip dropped support for Python 2 altogether.
How to upgrade and migrate
Install pip 20.3 with python -m pip install —upgrade pip .
Validate your current environment by running pip check . This will report if you have any inconsistencies in your set of installed packages. Having a clean installation will make it much less likely that you will hit issues with the new resolver (and may address hidden problems in your current environment!). If you run pip check and run into stuff you can’t figure out, please ask for help in our issue tracker or chat.
Test the new version of pip.
While we have tried to make sure that pip’s test suite covers as many cases as we can, we are very aware that there are people using pip with many different workflows and build processes, and we will not be able to cover all of those without your help.