Advanced Usage of Pipenv — pipenv documentation

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Pipenv/docs/v2021.5.29/advanced

Advanced Usage of Pipenv

https://farm4.staticflickr.com/3672/33231486560_bff4124c9a_k_d.jpg This document covers some of Pipenv’s more glorious and advanced features.

☤ Caveats

  • Dependencies of wheels provided in a Pipfile will not be captured by $ pipenv lock.
  • There are some known issues with using private indexes, related to hashing. We’re actively working to solve this problem. You may have great luck with this, however.
  • Installation is intended to be as deterministic as possible — use the --sequential flag to increase this, if experiencing issues.


☤ Specifying Package Indexes

If you’d like a specific package to be installed with a specific package index, you can do the following:

[[../source]]
url = "https://pypi.org/simple"
verify_ssl = true
name = "pypi"

[[../source]]
url = "http://pypi.home.kennethreitz.org/simple"
verify_ssl = false
name = "home"

[dev-packages]

[packages]
requests = {version="*", index="home"}
maya = {version="*", index="pypi"}
records = "*"

Very fancy.


☤ Using a PyPI Mirror

If you would like to override the default PyPI index URLs with the URL for a PyPI mirror, you can use the following:

$ pipenv install --pypi-mirror <mirror_url>

$ pipenv update --pypi-mirror <mirror_url>

$ pipenv sync --pypi-mirror <mirror_url>

$ pipenv lock --pypi-mirror <mirror_url>

$ pipenv uninstall --pypi-mirror <mirror_url>

Alternatively, you can set the PIPENV_PYPI_MIRROR environment variable.


☤ Injecting credentials into Pipfiles via environment variables

Pipenv will expand environment variables (if defined) in your Pipfile. Quite useful if you need to authenticate to a private PyPI:

[[../source]]
url = "https://$USERNAME:${PASSWORD}@mypypi.example.com/simple"
verify_ssl = true
name = "pypi"

Luckily - pipenv will hash your Pipfile before expanding environment variables (and, helpfully, will substitute the environment variables again when you install from the lock file - so no need to commit any secrets! Woo!)

If your credentials contain a special character, surround the references to the environment variables with quotation marks. For example, if your password contain a double quotation mark, surround the password variable with single quotation marks. Otherwise, you may get a ValueError, "No closing quotation" error while installing dependencies.

[[../source]]
url = "https://$USERNAME:'${PASSWORD}'@mypypi.example.com/simple"

Environment variables may be specified as ${MY_ENVAR} or $MY_ENVAR.

On Windows, %MY_ENVAR% is supported in addition to ${MY_ENVAR} or $MY_ENVAR.

Environment variables in the URL part of requirement specifiers can also be expanded, where the variable must be in the form of ${VAR_NAME}. Neither $VAR_NAME nor %VAR_NAME% is acceptable:

[[../package]]
requests = {git = "git://${USERNAME}:${PASSWORD}@private.git.com/psf/requests.git", ref = "2.22.0"}

Keep in mind that environment variables are expanded in runtime, leaving the entries in Pipfile or Pipfile.lock untouched. This is to avoid the accidental leakage of credentials in the source code.


☤ Specifying Basically Anything

If you’d like to specify that a specific package only be installed on certain systems, you can use PEP 508 specifiers to accomplish this.

Here’s an example Pipfile, which will only install pywinusb on Windows systems:

[[../source]]
url = "https://pypi.python.org/simple"
verify_ssl = true
name = "pypi"

[packages]
requests = "*"
pywinusb = {version = "*", sys_platform = "== 'win32'"}

Voilà!

Here’s a more complex example:

[[../source]]
url = "https://pypi.python.org/simple"
verify_ssl = true

[packages]
unittest2 = {version = ">=1.0,<3.0", markers="python_version < '2.7.9' or (python_version >= '3.0' and python_version < '3.4')"}

Magic. Pure, unadulterated magic.


☤ Using pipenv for Deployments

You may want to use pipenv as part of a deployment process.

You can enforce that your Pipfile.lock is up to date using the --deploy flag:

$ pipenv install --deploy

This will fail a build if the Pipfile.lock is out–of–date, instead of generating a new one.

Or you can install packages exactly as specified in Pipfile.lock using the sync command:

$ pipenv sync

Note

pipenv install --ignore-pipfile is nearly equivalent to pipenv sync, but pipenv sync will never attempt to re-lock your dependencies as it is considered an atomic operation. pipenv install by default does attempt to re-lock unless using the --deploy flag.


Deploying System Dependencies

You can tell Pipenv to install a Pipfile’s contents into its parent system with the --system flag:

$ pipenv install --system

This is useful for managing the system Python, and deployment infrastructure (e.g. Heroku does this).


☤ Pipenv and Other Python Distributions

To use Pipenv with a third-party Python distribution (e.g. Anaconda), you simply provide the path to the Python binary:

$ pipenv install --python=/path/to/python

Anaconda uses Conda to manage packages. To reuse Conda–installed Python packages, use the --site-packages flag:

$ pipenv --python=/path/to/python --site-packages

☤ Generating a requirements.txt

You can convert a Pipfile and Pipfile.lock into a requirements.txt file very easily, and get all the benefits of extras and other goodies we have included.

Let’s take this Pipfile:

[[../source]]
url = "https://pypi.python.org/simple"
verify_ssl = true

[packages]
requests = {version="*"}

[dev-packages]
pytest = {version="*"}

And generate a set of requirements out of it with only the default dependencies:

$ pipenv lock -r
chardet==3.0.4
requests==2.18.4
certifi==2017.7.27.1
idna==2.6
urllib3==1.22

As with other commands, passing --dev will include both the default and development dependencies:

$ pipenv lock -r --dev
chardet==3.0.4
requests==2.18.4
certifi==2017.7.27.1
idna==2.6
urllib3==1.22
py==1.4.34
pytest==3.2.3

Finally, if you wish to generate a requirements file with only the development requirements you can do that too, using the --dev-only flag:

$ pipenv lock -r --dev-only
py==1.4.34
pytest==3.2.3

The locked requirements are written to stdout, with shell output redirection used to write them to a file:

$ pipenv lock -r > requirements.txt
$ pipenv lock -r --dev-only > dev-requirements.txt
$ cat requirements.txt
chardet==3.0.4
requests==2.18.4
certifi==2017.7.27.1
idna==2.6
urllib3==1.22
$ cat dev-requirements.txt
py==1.4.34
pytest==3.2.3

☤ Detection of Security Vulnerabilities

Pipenv includes the safety package, and will use it to scan your dependency graph for known security vulnerabilities!

Example:

$ cat Pipfile
[packages]
django = "==1.10.1"

$ pipenv check
Checking PEP 508 requirements...
Passed!
Checking installed package safety...

33075: django >=1.10,<1.10.3 resolved (1.10.1 installed)!
Django before 1.8.x before 1.8.16, 1.9.x before 1.9.11, and 1.10.x before 1.10.3, when settings.DEBUG is True, allow remote attackers to conduct DNS rebinding attacks by leveraging failure to validate the HTTP Host header against settings.ALLOWED_HOSTS.

33076: django >=1.10,<1.10.3 resolved (1.10.1 installed)!
Django 1.8.x before 1.8.16, 1.9.x before 1.9.11, and 1.10.x before 1.10.3 use a hardcoded password for a temporary database user created when running tests with an Oracle database, which makes it easier for remote attackers to obtain access to the database server by leveraging failure to manually specify a password in the database settings TEST dictionary.

33300: django >=1.10,<1.10.7 resolved (1.10.1 installed)!
CVE-2017-7233: Open redirect and possible XSS attack via user-supplied numeric redirect URLs
============================================================================================

Django relies on user input in some cases  (e.g.
:func:`django.contrib.auth.views.login` and :doc:`i18n </topics/i18n/index>`)
to redirect the user to an "on success" URL. The security check for these
redirects (namely ``django.utils.http.is_safe_url()``) considered some numeric
URLs (e.g. ``http:999999999``) "safe" when they shouldn't be.

Also, if a developer relies on ``is_safe_url()`` to provide safe redirect
targets and puts such a URL into a link, they could suffer from an XSS attack.

CVE-2017-7234: Open redirect vulnerability in ``django.views.static.serve()``
=============================================================================

A maliciously crafted URL to a Django site using the
:func:`~django.views.static.serve` view could redirect to any other domain. The
view no longer does any redirects as they don't provide any known, useful
functionality.

Note, however, that this view has always carried a warning that it is not
hardened for production use and should be used only as a development aid.

✨🍰✨

Note

Each month, PyUp.io updates the safety database of insecure Python packages and makes it available to the community for free. Pipenv makes an API call to retrieve those results and use them each time you run pipenv check to show you vulnerable dependencies.

For more up-to-date vulnerability data, you may also use your own safety API key by setting the environment variable PIPENV_PYUP_API_KEY.


☤ Community Integrations

There are a range of community-maintained plugins and extensions available for a range of editors and IDEs, as well as different products which integrate with Pipenv projects:

Works in progress:

  • Sublime Text (Editor Integration)
  • Mysterious upcoming Google Cloud product (Cloud Hosting)


☤ Open a Module in Your Editor

Pipenv allows you to open any Python module that is installed (including ones in your codebase), with the $ pipenv open command:

$ pipenv install -e git+https://github.com/kennethreitz/background.git#egg=background
Installing -e git+https://github.com/kennethreitz/background.git#egg=background...
...
Updated Pipfile.lock!

$ pipenv open background
Opening '/Users/kennethreitz/.local/share/virtualenvs/hmm-mGOawwm_/src/background/background.py' in your EDITOR.

This allows you to easily read the code you’re consuming, instead of looking it up on GitHub.

Note

The standard EDITOR environment variable is used for this. If you’re using VS Code, for example, you’ll want to export EDITOR=code (if you’re on macOS you will want to install the command on to your PATH first).


☤ Automatic Python Installation

If you have pyenv installed and configured, Pipenv will automatically ask you if you want to install a required version of Python if you don’t already have it available.

This is a very fancy feature, and we’re very proud of it:

$ cat Pipfile
[[../source]]
url = "https://pypi.python.org/simple"
verify_ssl = true

[dev-packages]

[packages]
requests = "*"

[requires]
python_version = "3.6"

$ pipenv install
Warning: Python 3.6 was not found on your system...
Would you like us to install latest CPython 3.6 with pyenv? [Y/n]: y
Installing CPython 3.6.2 with pyenv (this may take a few minutes)...
...
Making Python installation global...
Creating a virtualenv for this project...
Using /Users/kennethreitz/.pyenv/shims/python3 to create virtualenv...
...
No package provided, installing all dependencies.
...
Installing dependencies from Pipfile.lock...
🐍   ❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒❒ 5/5 — 00:00:03
To activate this project's virtualenv, run the following:
 $ pipenv shell

Pipenv automatically honors both the python_full_version and python_version PEP 508 specifiers.

💫✨🍰✨💫


☤ Automatic Loading of .env

If a .env file is present in your project, $ pipenv shell and $ pipenv run will automatically load it, for you:

$ cat .env
HELLO=WORLD⏎

$ pipenv run python
Loading .env environment variables...
Python 2.7.13 (default, Jul 18 2017, 09:17:00)
[GCC 4.2.1 Compatible Apple LLVM 8.1.0 (clang-802.0.42)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import os
>>> os.environ['HELLO']
'WORLD'

Shell like variable expansion is available in .env files using ${VARNAME} syntax.:

$ cat .env
CONFIG_PATH=${HOME}/.config/foo

$ pipenv run python
Loading .env environment variables...
Python 3.7.6 (default, Dec 19 2019, 22:52:49)
[GCC 9.2.1 20190827 (Red Hat 9.2.1-1)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import os
>>> os.environ['CONFIG_PATH']
'/home/kennethreitz/.config/foo'

This is very useful for keeping production credentials out of your codebase. We do not recommend committing .env files into source control!

If your .env file is located in a different path or has a different name you may set the PIPENV_DOTENV_LOCATION environment variable:

$ PIPENV_DOTENV_LOCATION=/path/to/.env pipenv shell

To prevent pipenv from loading the .env file, set the PIPENV_DONT_LOAD_ENV environment variable:

$ PIPENV_DONT_LOAD_ENV=1 pipenv shell

See theskumar/python-dotenv for more information on .env files.


☤ Custom Script Shortcuts

Pipenv supports creating custom shortcuts in the (optional) [scripts] section of your Pipfile.

You can then run pipenv run <shortcut name> in your terminal to run the command in the context of your pipenv virtual environment even if you have not activated the pipenv shell first.

For example, in your Pipfile:

[scripts]
printspam = "python -c \"print('I am a silly example, no one would need to do this')\""

And then in your terminal:

$ pipenv run printspam
I am a silly example, no one would need to do this

Commands that expect arguments will also work. For example:

[scripts]
echospam = "echo I am really a very silly example"
$ pipenv run echospam "indeed"
I am really a very silly example indeed

You can then display the names and commands of your shortcuts by running pipenv scripts in your terminal.

$ pipenv scripts
command   script
echospam  echo I am really a very silly example

☤ Configuration With Environment Variables

Pipenv comes with a handful of options that can be enabled via shell environment variables. To activate them, simply create the variable in your shell and pipenv will detect it.

If you’d like to set these environment variables on a per-project basis, I recommend utilizing the fantastic direnv project, in order to do so.

Also note that pip itself supports environment variables, if you need additional customization.

For example:

$ PIP_INSTALL_OPTION="-- -DCMAKE_BUILD_TYPE=Release" pipenv install -e .

☤ Custom Virtual Environment Location

Pipenv automatically honors the WORKON_HOME environment variable, if you have it set — so you can tell pipenv to store your virtual environments wherever you want, e.g.:

export WORKON_HOME=~/.venvs

In addition, you can also have Pipenv stick the virtualenv in project/.venv by setting the PIPENV_VENV_IN_PROJECT environment variable.


☤ Testing Projects

Pipenv is being used in projects like Requests for declaring development dependencies and running the test suite.

We have currently tested deployments with both Travis-CI and tox with success.

Travis CI

An example Travis CI setup can be found in Requests. The project uses a Makefile to define common functions such as its init and tests commands. Here is a stripped down example .travis.yml:

language: python
python:
    - "2.6"
    - "2.7"
    - "3.3"
    - "3.4"
    - "3.5"
    - "3.6"
    - "3.7-dev"

# command to install dependencies
install: "make"

# command to run tests
script:
    - make test

and the corresponding Makefile:

init:
    pip install pipenv
    pipenv install --dev

test:
    pipenv run pytest tests

Tox Automation Project

Alternatively, you can configure a tox.ini like the one below for both local and external testing:

[tox]
envlist = flake8-py3, py26, py27, py33, py34, py35, py36, pypy

[testenv]
deps = pipenv
commands=
    pipenv install --dev
    pipenv run pytest tests

[testenv:flake8-py3]
basepython = python3.4
commands=
    pipenv install --dev
    pipenv run flake8 --version
    pipenv run flake8 setup.py docs project test

Pipenv will automatically use the virtualenv provided by tox. If pipenv install --dev installs e.g. pytest, then installed command pytest will be present in given virtualenv and can be called directly by pytest tests instead of pipenv run pytest tests.

You might also want to add --ignore-pipfile to pipenv install, as to not accidentally modify the lock-file on each test run. This causes Pipenv to ignore changes to the Pipfile and (more importantly) prevents it from adding the current environment to Pipfile.lock. This might be important as the current environment (i.e. the virtualenv provisioned by tox) will usually contain the current project (which may or may not be desired) and additional dependencies from tox’s deps directive. The initial provisioning may alternatively be disabled by adding skip_install = True to tox.ini.

This method requires you to be explicit about updating the lock-file, which is probably a good idea in any case.

A 3rd party plugin, tox-pipenv is also available to use Pipenv natively with tox.


☤ Shell Completion

To enable completion in fish, add this to your configuration:

eval (pipenv --completion)

Alternatively, with bash or zsh, add this to your configuration:

eval "$(pipenv --completion)"

Magic shell completions are now enabled!

✨🍰✨


☤ Working with Platform-Provided Python Components

It’s reasonably common for platform specific Python bindings for operating system interfaces to only be available through the system package manager, and hence unavailable for installation into virtual environments with pip. In these cases, the virtual environment can be created with access to the system site-packages directory:

$ pipenv --three --site-packages

To ensure that all pip-installable components actually are installed into the virtual environment and system packages are only used for interfaces that don’t participate in Python-level dependency resolution at all, use the PIP_IGNORE_INSTALLED setting:

$ PIP_IGNORE_INSTALLED=1 pipenv install --dev

☤ Pipfile vs setup.py

There is a subtle but very important distinction to be made between applications and libraries. This is a very common source of confusion in the Python community.

Libraries provide reusable functionality to other libraries and applications (let’s use the umbrella term projects here). They are required to work alongside other libraries, all with their own set of sub-dependencies. They define abstract dependencies. To avoid version conflicts in sub-dependencies of different libraries within a project, libraries should never ever pin dependency versions. Although they may specify lower or (less frequently) upper bounds, if they rely on some specific feature/fix/bug. Library dependencies are specified via install_requires in setup.py.

Libraries are ultimately meant to be used in some application. Applications are different in that they usually are not depended on by other projects. They are meant to be deployed into some specific environment and only then should the exact versions of all their dependencies and sub-dependencies be made concrete. To make this process easier is currently the main goal of Pipenv.

To summarize:

  • For libraries, define abstract dependencies via install_requires in setup.py. The decision of which version exactly to be installed and where to obtain that dependency is not yours to make!
  • For applications, define dependencies and where to get them in the Pipfile and use this file to update the set of concrete dependencies in Pipfile.lock. This file defines a specific idempotent environment that is known to work for your project. The Pipfile.lock is your source of truth. The Pipfile is a convenience for you to create that lock-file, in that it allows you to still remain somewhat vague about the exact version of a dependency to be used. Pipenv is there to help you define a working conflict-free set of specific dependency-versions, which would otherwise be a very tedious task.
  • Of course, Pipfile and Pipenv are still useful for library developers, as they can be used to define a development or test environment.
  • And, of course, there are projects for which the distinction between library and application isn’t that clear. In that case, use install_requires alongside Pipenv and Pipfile.

You can also do this:

$ pipenv install -e .

This will tell Pipenv to lock all your setup.py–declared dependencies.


☤ Changing Pipenv’s Cache Location

You can force Pipenv to use a different cache location by setting the environment variable PIPENV_CACHE_DIR to the location you wish. This is useful in the same situations that you would change PIP_CACHE_DIR to a different directory.


☤ Changing Default Python Versions

By default, Pipenv will initialize a project using whatever version of python the python3 is. Besides starting a project with the --three or --two flags, you can also use PIPENV_DEFAULT_PYTHON_VERSION to specify what version to use when starting a project when --three or --two aren’t used.