Advanced Usage of Pipenv¶
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.
☤ 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.python.org/simple"
verify_ssl = true
name = "pypi"
[[source]]
url = "http://pypi.home.ken.org/simple"
verify_ssl = false
name = "home"
[dev-packages]
[packages]
requests = {version="*", index="home"}
maya = {version="*", index="pypi"}
records = "*"
Very fancy.
☤ 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.
☤ 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 Docker containers, and deployment infrastructure (e.g. Heroku does this).
Also useful for deployment is the --deploy
flag:
$ pipenv install --system --deploy
This will fail a build if the Pipfile.lock
is out–of–date, instead of generating a new one.
☤ pipenv
and conda
¶
To use Pipenv with a Conda–provided Python, you simply provide the path to the Python binary:
$ pipenv install --python=/path/to/anaconda/python
To reuse Conda–installed Python packages, use the --site-packages
flag:
$ pipenv --python=/path/to/anaconda/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="*"}
And generate a requirements.txt
out of it:
$ pipenv lock -r
chardet==3.0.4
requests==2.18.4
certifi==2017.7.27.1
idna==2.6
urllib3==1.22
If you wish to generate a requirements.txt
with only the development requirements you can do that too! Let’s take the following Pipfile
:
[[source]]
url = "https://pypi.python.org/simple"
verify_ssl = true
[dev-packages]
pytest = {version="*"}
And generate a requirements.txt
out of it:
$ pipenv lock -r --dev
py==1.4.34
pytest==3.2.3
Very fancy.
☤ 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
Commercial redistributors of pipenv should be aware that the public Safety-DB project backing this feature is licensed as CC-BY-NC-SA by pyup.io. While pyup.io have [stated explicitly](https://github.com/pypa/pipenv/issues/1651#issuecomment-372583779) that commercial use of this pipenv feature is fine, commercial redistributors may want to perform their own legal assessment and perhaps chat directly to pyup.io about the specific licensing terms.
☤ 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:
- Heroku (Cloud Hosting)
- Platform.sh (Cloud Hosting)
- PyUp (Security Notification)
- Emacs (Editor Integration)
- Fish Shell (Automatic
$ pipenv shell
!) - VS Code (Editor Integration)
Works in progress:
- Sublime Text (Editor Integration)
- PyCharm (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/ken/background.git#egg=background
Installing -e git+https://github.com/ken/background.git#egg=background…
...
Updated Pipfile.lock!
$ pipenv open background
Opening '/Users/ken/.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/ken/.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'
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
☤ 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.
PIPENV_DEFAULT_PYTHON_VERSION
— Use this version of Python when creating new virtual environments, by default (e.g.3.6
).PIPENV_SHELL_FANCY
— Always use fancy mode when invokingpipenv shell
.PIPENV_VENV_IN_PROJECT
— If set, use.venv
in your project directory instead of the global virtualenv managerpew
.PIPENV_COLORBLIND
— Disable terminal colors, for some reason.PIPENV_NOSPIN
— Disable terminal spinner, for cleaner logs. Automatically set in CI environments.PIPENV_MAX_DEPTH
— Set to an integer for the maximum number of directories to recursively search for a Pipfile.PIPENV_TIMEOUT
— Set to an integer for the max number of seconds Pipenv will wait for virtualenv creation to complete. Defaults to 120 seconds.PIPENV_IGNORE_VIRTUALENVS
— Set to disable automatically using an activated virtualenv over the current project’s own virtual environment.PIPENV_PIPFILE
— When running pipenv from a $PWD other than the same directory where the Pipfile is located, instruct pipenv to find the Pipfile in the location specified by this environment variable.
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’s underlying pew
dependency will automatically honor 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’ve 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 py.test 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]
passenv=HOME
deps = pipenv
commands=
pipenv install --dev
pipenv run py.test tests
[testenv:flake8-py3]
passenv=HOME
basepython = python3.4
commands=
{[testenv]deps}
pipenv install --dev
pipenv run flake8 --version
pipenv run flake8 setup.py docs project test
Note
With Pipenv’s default configuration, you’ll need to use tox’s passenv
parameter
to pass your shell’s HOME
variable.
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 config:
eval (pipenv --completion)
Alternatively, with bash or zsh, add this to your config:
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 subdependencies. They define abstract dependencies. To avoid version conflicts in subdependencies of different libraries within a project, libraries should never ever pin dependency versions. Although they may specifiy 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
.
Libaries 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 subdependencies 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
insetup.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. ThePipfile.lock
is your source of truth. ThePipfile
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
andpipenv
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
alongsidepipenv
andPipfile
.
You can also do this:
$ pipenv install -e .
This will tell Pipenv to lock all your setup.py
–declared dependencies.