Develop Reference

How to install test requirements from setup.py [duplicate]

We've made a library which depends on other libraries. But there are necessary (e.g. for server batch processing) and optional dependencies (e.g. for clients with GUI).
Is something like this possible:
pip install mylib.tar.gz # automatically downloads and installs with the minimal set of dependencies
pip install mylib.tar.gz --install-option="complete" # automatically installs with all dependencies
I've found the extra_require flag, but how can I tell pip to use them? The setup.py looks like this:
from setuptools import setup
# ...
# Hard library depencencies:
requires = [
"numpy>=1.4.1",
"scipy>=0.7.2",
"traits>=3.4.0"
]
# Soft library dependencies:
recommended = {
"mpl": ["matplotlib>=0.99.3"],
"bn": ["bottleneck>=0.6"]
}
# ...
# Installer parameters:
setup(
name = "mylib",
#...
install_requires = requires,
extras_require = recommended
)

You can install the packages in extras_require by appending the name of the recommended dependency in square brackets (i.e. [mpl] or [bn] in your case) to the package name in pip.
So to install 'mylib' with the additional requirements, you would call pip like this:
pip install 'mylib[mpl]'
pip install 'mylib[bn]'
This will first download and install the extra dependencies, and then mylib's core dependencies.
This is anologous to how you declare those dependencies with setuptools: http://pythonhosted.org/setuptools/setuptools.html#declaring-extras-optional-features-with-their-own-dependencies (see the install_requires value in the third example)

So pip is actually quite picky about installing libraries with extra requirements
pip install -e ".[extra,requirements]" # works with file paths
pip install "package[extra,requirements]" # works when downloading packages
pip install ".[extra,requirments]" # DOES NOT WORK
I think this is down to how the RequirementsSpec parser works, and pip does some extra magic with the -e flag. Anyhow after much head banging, here's a mildly ugly workaround
pip install "file:///path/to/your/python_code#egg=SomeName[extra,requirements]"
The egg=SomeName part is basically ignored, but pip correctly picks up the extra requirements
Caveats
Tested with pip 1.5.6 so make sure you're using a current version of pip.
As far as I can tell, the file:/// syntax is undocumented in pip, so I'm not sure if it'll change in the future. It looks a bit like the VCS Support syntax but I was a bit surprised it worked.
You could also get around this by running your own pypi server, but that's a bit out of scope.

pip: uninstalling a disutils installed package

I am trying to install psutil with the command pip install -U psutil and that gives me the error:
Cannot uninstall 'psutil'. It is a distutils installed project and thus we cannot accurately determine which files belong to it which would lead to only a partial uninstall.
It seems like this is a known issue in pip with versions > 10, and I understand that part (I currently have pip 18). But I just found that I can solve it by directly doing a pip install psutil without using the Upgrade flag. I was wondering if there is a reasoning behind that. My initial sense is that in the first case, where pip tries to upgrade, it first tries to remove the package, which it cannot, but in the latter case it tries to install directly, and hence does not get the error. My question is does it still not have to remove the package first and install (when not using the Upgrade flag), or why specifically is it that pip gives an error with an Upgrade flag but no error without it.
EDIT: So, I tried to run pip install -v psutil as hoefling suggested, and I got a whole bunch of text, as opposed to saying that requirements already met, which means that psutil didn't get installed in the first place. I tried to figure this a bit, and this is what I understand so far: I was running inside a python virtualenv and installing it by means of pip -U -r requirements.txt where requirements.txt contains a bunch of packages including psutil. When I remove the -U flag, it skips installing psutil, and jumps over to other packages. Which raises another question, whether this is how pip is supposed to behave when there is no -U flag. Its interesting that the first time, when its installing the packages with the -U flag, it looks inside the main python installation instead of the virtual environment one, and when the -U flag is removed it doesn't do that and skips entirely.

There are some setups where you have a bunch of packages installed somewhere that isn't the normal install location for setuptools, and comes after the normal install location on sys.path.
Probably the most common of these setups is Apple's pre-installed Python 2.7, so I'll use it as an example. Even if that isn't your setup, it will be hopefully still be instructive.
Apple includes an Extras directory (at /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python), with a bunch of third-party packages that either Apple's own tools need, or that Apple thought you might want (back when Apple cared about providing the best Python experience of any platform).
For example, on macOS 10.13, that directory will include NumPy 1.8.0.
These packages are all installed as distribute-style eggs.
(Some linux distros do, or at least used to do, similar things, with Python packages built as RPM/DEB/etc. packages, which go into adistutils directory, unlike things you install via pip or manually, which go into a setuptools directory. The details are a bit different, but the effects, and the workaround, end up being the same.)
If you install pip, and then try to pip install -U numpy or pip uninstall numpy, pip will see the distribute-style numpy-1.8.0rc1-py2.7.egg-info file and refuse to touch it for fear of breaking everything.
If you just pip install numpy, however, it will look only in the standard site-packages installation location used by setuptools, /Library/Python/2.7/site-packages, see nothing there, and happily install a modern version of NumPy for you.
And, because /Library/Python/2.7/site-packages comes before /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python on your sys,path, the new NumPy will hide the ancient NumPy, and everything will just work as intended.
There can be a few problems with this. Most notably, if you try to install something which isn't included in Extras itself, but which has a dependency that is included in Extras, it may fail with mysterious and hard-to-debug errors. For example, on macOS 10.12, pip install pandas will throw a bunch of errors at you about not being able to upgrade dateutil, which you didn't even know you were trying to do. The only thing you can do is look at the dependencies for pandas, see which ones are pre-installed in Extras, and manually pip install shadowing versions of all of them.
But, for the most part, it works.

How to install a Python wheel under an alternative package name? (in my specific case, PyCryptodome under the "Cryptodome" package name)

The installation information page of PyCryptodome says the following under the "Windows (pre-compiled)" section:
Install PyCryptodome as a wheel:
pip install pycryptodomex
To make sure everything works fine, run the test suite:
python -m Cryptodome.SelfTest
There are several problems with this though:
Contrary to what these instructions say, this will not install PyCryptoDome as a wheel, but it will rather download it and try to build it, resulting in an error if you don't have the correct build environment installed for the C components included in this package (and the entire mess related to this is the biggest benefit of using a wheel instead to begin with).
Even if I instead download the correct wheel file from PyCryptoDome's PyPi page, I must (as far as I know?) instead use a command-line as follows to install it:
pip install c:\some\path\name-of-wheel-file.whl
This in turn makes it install under the default "Crypto" package instead of the "Cryptodome" package explicitly mentioned in the instructions (and therefore colliding in a breaking fashion with any pre-existing installations of the PyCrypto package).
So, my question is:
Is there any way to install a wheel file under a different package name than the default one?
PyCryptodome does not seem to provide any specific wheel files for installing under this alternative package name, so if this is impossible, I have a big problem (because I already have PyCrypto installed). :-(
PS.
Some more context regarding the need for the alternative package name can be provided by the following quote from the same installation page that is linked above:
PyCryptodome can be used as:
1.
a drop-in replacement for the old PyCrypto library. You install it with:
pip install pycryptodome
In this case, all modules are installed under the Crypto package. You can test everything is right with:
python -m Crypto.SelfTest
One must avoid having both PyCrypto and PyCryptodome installed at the same time, as they will interfere with each other.
This option is therefore recommended only when you are sure that the whole application is deployed in a virtualenv.
2.
a library independent of the old PyCrypto. You install it with:
pip install pycryptodomex
You can test everything is right with:
python -m Cryptodome.SelfTest
In this case, all modules are installed under the Cryptodome package. PyCrypto and PyCryptodome can coexist.
So, again, all I want is to install it as described under alternative 2 in this quote, from a wheel file, but the problem is that the provided wheel files seem to only default to the package name described under alternative 1 in this quote (i.e. "Crypto").

As far as I know this is not possible. The only way to achieve this by recompiling the wheel yourself after you modified its name in the setup.py.

setuptools and pip: choice of minimal and complete install

We've made a library which depends on other libraries. But there are necessary (e.g. for server batch processing) and optional dependencies (e.g. for clients with GUI).
Is something like this possible:
pip install mylib.tar.gz # automatically downloads and installs with the minimal set of dependencies
pip install mylib.tar.gz --install-option="complete" # automatically installs with all dependencies
I've found the extra_require flag, but how can I tell pip to use them? The setup.py looks like this:
from setuptools import setup
# ...
# Hard library depencencies:
requires = [
"numpy>=1.4.1",
"scipy>=0.7.2",
"traits>=3.4.0"
]
# Soft library dependencies:
recommended = {
"mpl": ["matplotlib>=0.99.3"],
"bn": ["bottleneck>=0.6"]
}
# ...
# Installer parameters:
setup(
name = "mylib",
#...
install_requires = requires,
extras_require = recommended
)

You can install the packages in extras_require by appending the name of the recommended dependency in square brackets (i.e. [mpl] or [bn] in your case) to the package name in pip.
So to install 'mylib' with the additional requirements, you would call pip like this:
pip install 'mylib[mpl]'
pip install 'mylib[bn]'
This will first download and install the extra dependencies, and then mylib's core dependencies.
This is anologous to how you declare those dependencies with setuptools: http://pythonhosted.org/setuptools/setuptools.html#declaring-extras-optional-features-with-their-own-dependencies (see the install_requires value in the third example)

So pip is actually quite picky about installing libraries with extra requirements
pip install -e ".[extra,requirements]" # works with file paths
pip install "package[extra,requirements]" # works when downloading packages
pip install ".[extra,requirments]" # DOES NOT WORK
I think this is down to how the RequirementsSpec parser works, and pip does some extra magic with the -e flag. Anyhow after much head banging, here's a mildly ugly workaround
pip install "file:///path/to/your/python_code#egg=SomeName[extra,requirements]"
The egg=SomeName part is basically ignored, but pip correctly picks up the extra requirements
Caveats
Tested with pip 1.5.6 so make sure you're using a current version of pip.
As far as I can tell, the file:/// syntax is undocumented in pip, so I'm not sure if it'll change in the future. It looks a bit like the VCS Support syntax but I was a bit surprised it worked.
You could also get around this by running your own pypi server, but that's a bit out of scope.

Why use pip over easy_install?

A tweet reads:
Don't use easy_install, unless you
like stabbing yourself in the face.
Use pip.
Why use pip over easy_install? Doesn't the fault lie with PyPI and package authors mostly? If an author uploads crap source tarball (eg: missing files, no setup.py) to PyPI, then both pip and easy_install will fail. Other than cosmetic differences, why do Python people (like in the above tweet) seem to strongly favor pip over easy_install?
(Let's assume that we're talking about easy_install from the Distribute package, that is maintained by the community)

From Ian Bicking's own introduction to pip:
pip was originally written to improve on easy_install in the following ways
All packages are downloaded before installation. Partially-completed installation doesn’t occur as a result.
Care is taken to present useful output on the console.
The reasons for actions are kept track of. For instance, if a package is being installed, pip keeps track of why that package was required.
Error messages should be useful.
The code is relatively concise and cohesive, making it easier to use programmatically.
Packages don’t have to be installed as egg archives, they can be installed flat (while keeping the egg metadata).
Native support for other version control systems (Git, Mercurial and Bazaar)
Uninstallation of packages.
Simple to define fixed sets of requirements and reliably reproduce a set of packages.

Many of the answers here are out of date for 2015 (although the initially accepted one from Daniel Roseman is not). Here's the current state of things:
Binary packages are now distributed as wheels (.whl files)—not just on PyPI, but in third-party repositories like Christoph Gohlke's Extension Packages for Windows. pip can handle wheels; easy_install cannot.
Virtual environments (which come built-in with 3.4, or can be added to 2.6+/3.1+ with virtualenv) have become a very important and prominent tool (and recommended in the official docs); they include pip out of the box, but don't even work properly with easy_install.
The distribute package that included easy_install is no longer maintained. Its improvements over setuptools got merged back into setuptools. Trying to install distribute will just install setuptools instead.
easy_install itself is only quasi-maintained.
All of the cases where pip used to be inferior to easy_install—installing from an unpacked source tree, from a DVCS repo, etc.—are long-gone; you can pip install ., pip install git+https://.
pip comes with the official Python 2.7 and 3.4+ packages from python.org, and a pip bootstrap is included by default if you build from source.
The various incomplete bits of documentation on installing, using, and building packages have been replaced by the Python Packaging User Guide. Python's own documentation on Installing Python Modules now defers to this user guide, and explicitly calls out pip as "the preferred installer program".
Other new features have been added to pip over the years that will never be in easy_install. For example, pip makes it easy to clone your site-packages by building a requirements file and then installing it with a single command on each side. Or to convert your requirements file to a local repo to use for in-house development. And so on.
The only good reason that I know of to use easy_install in 2015 is the special case of using Apple's pre-installed Python versions with OS X 10.5-10.8. Since 10.5, Apple has included easy_install, but as of 10.10 they still don't include pip. With 10.9+, you should still just use get-pip.py, but for 10.5-10.8, this has some problems, so it's easier to sudo easy_install pip. (In general, easy_install pip is a bad idea; it's only for OS X 10.5-10.8 that you want to do this.) Also, 10.5-10.8 include readline in a way that easy_install knows how to kludge around but pip doesn't, so you also want to sudo easy_install readline if you want to upgrade that.

Another—as of yet unmentioned—reason for favoring pip is because it is the new hotness and will continue to be used in the future.
The infographic below—from the Current State of Packaging section in the The Hitchhiker's Guide to Packaging v1.0—shows that setuptools/easy_install will go away in the future.
Here's another infographic from distribute's documentation showing that Setuptools and easy_install will be replaced by the new hotness—distribute and pip. While pip is still the new hotness, Distribute merged with Setuptools in 2013 with the release of Setuptools v0.7.

Two reasons, there may be more:
pip provides an uninstall command
if an installation fails in the middle, pip will leave you in a clean state.

REQUIREMENTS files.
Seriously, I use this in conjunction with virtualenv every day.
QUICK DEPENDENCY MANAGEMENT TUTORIAL, FOLKS
Requirements files allow you to create a snapshot of all packages that have been installed through pip. By encapsulating those packages in a virtualenvironment, you can have your codebase work off a very specific set of packages and share that codebase with others.
From Heroku's documentation https://devcenter.heroku.com/articles/python
You create a virtual environment, and set your shell to use it. (bash/*nix instructions)
virtualenv env
source env/bin/activate
Now all python scripts run with this shell will use this environment's packages and configuration. Now you can install a package locally to this environment without needing to install it globally on your machine.
pip install flask
Now you can dump the info about which packages are installed with
pip freeze > requirements.txt
If you checked that file into version control, when someone else gets your code, they can setup their own virtual environment and install all the dependencies with:
pip install -r requirements.txt
Any time you can automate tedium like this is awesome.

pip won't install binary packages and isn't well tested on Windows.
As Windows doesn't come with a compiler by default pip often can't be used there. easy_install can install binary packages for Windows.

UPDATE: setuptools has absorbed distribute as opposed to the other way around, as some thought. setuptools is up-to-date with the latest distutils changes and the wheel format. Hence, easy_install and pip are more or less on equal footing now.
Source: http://pythonhosted.org/setuptools/merge-faq.html#why-setuptools-and-not-distribute-or-another-name

As an addition to fuzzyman's reply:
pip won't install binary packages and isn't well tested on Windows.
As Windows doesn't come with a compiler by default pip often can't be
used there. easy_install can install binary packages for Windows.
Here is a trick on Windows:
you can use easy_install <package> to install binary packages to avoid building a binary
you can use pip uninstall <package> even if you used easy_install.
This is just a work-around that works for me on windows.
Actually I always use pip if no binaries are involved.
See the current pip doku: http://www.pip-installer.org/en/latest/other-tools.html#pip-compared-to-easy-install
I will ask on the mailing list what is planned for that.
Here is the latest update:
The new supported way to install binaries is going to be wheel!
It is not yet in the standard, but almost. Current version is still an alpha: 1.0.0a1
https://pypi.python.org/pypi/wheel
http://wheel.readthedocs.org/en/latest/
I will test wheel by creating an OS X installer for PySide using wheel instead of eggs. Will get back and report about this.
cheers - Chris
A quick update:
The transition to wheel is almost over. Most packages are supporting wheel.
I promised to build wheels for PySide, and I did that last summer. Works great!
HINT:
A few developers failed so far to support the wheel format, simply because they forget to
replace distutils by setuptools.
Often, it is easy to convert such packages by replacing this single word in setup.py.

Just met one special case that I had to use easy_install instead of pip, or I have to pull the source codes directly.
For the package GitPython, the version in pip is too old, which is 0.1.7, while the one from easy_install is the latest which is 0.3.2.rc1.
I'm using Python 2.7.8. I'm not sure about the underlay mechanism of easy_install and pip, but at least the versions of some packages may be different from each other, and sometimes easy_install is the one with newer version.
easy_install GitPython