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Python

User Guide

Several versions of Python are available on Nix as well as a high amount of packages. The default interpreter is CPython 2.7.

Using Python

Installing Python and packages

It is important to make a distinction between Python packages that are used as libraries, and applications that are written in Python.

Applications on Nix are installed typically into your user profile imperatively using nix-env -i, and on NixOS declaratively by adding the package name to environment.systemPackages in /etc/nixos/configuration.nix. Dependencies such as libraries are automatically installed and should not be installed explicitly.

The same goes for Python applications and libraries. Python applications can be installed in your profile, but Python libraries you would like to use to develop cannot. If you do install libraries in your profile, then you will end up with import errors.

Python environments using `nix-shell`

The recommended method for creating Python environments for development is with nix-shell. Executing

$ nix-shell -p python35Packages.numpy python35Packages.toolz

opens a Nix shell which has available the requested packages and dependencies. Now you can launch the Python interpreter (which is itself a dependency)

[nix-shell:~] python3

If the packages were not available yet in the Nix store, Nix would download or build them automatically. A convenient option with nix-shell is the --run option, with which you can execute a command in the nix-shell. Let's say we want the above environment and directly run the Python interpreter

$ nix-shell -p python35Packages.numpy python35Packages.toolz --run "python3"

This way you can use the --run option also to directly run a script

$ nix-shell -p python35Packages.numpy python35Packages.toolz --run "python3 myscript.py"

In fact, for this specific use case there is a more convenient method. You can add a shebang to your script specifying which dependencies Nix shell needs. With the following shebang, you can use nix-shell myscript.py and it will make available all dependencies and run the script in the python3 shell.

#! /usr/bin/env nix-shell
#! nix-shell -i python3 -p python3Packages.numpy

import numpy

print(numpy.__version__)

Likely you do not want to type your dependencies each and every time. What you can do is write a simple Nix expression which sets up an environment for you, requiring you only to type nix-shell. Say we want to have Python 3.5, numpy and toolz, like before, in an environment. With a shell.nix file containing

with import <nixpkgs> {};

(pkgs.python35.buildEnv.override  {
  extraLibs = with pkgs.python35Packages; [ numpy toolz ];
}).env

executing nix-shell gives you again a Nix shell from which you can run Python.

What's happening here?

We begin with importing the Nix Packages collections. import <nixpkgs> import the <nixpkgs> function, {} calls it and the with statement brings all attributes of nixpkgs in the local scope. Therefore we can now use pkgs.
Then we create a Python 3.5 environment with pkgs.buildEnv. Because we want to use it with a custom set of Python packages, we override it.
The extraLibs argument of the original buildEnv function can be used to specify which packages should be included. We want numpy and toolz. Again, we use the with statement to bring a set of attributes into the local scope.
And finally, for in interactive use we return the environment.

Developing with Python

Now that you know how to get a working Python environment on Nix, it is time to go forward and start actually developing with Python. We will first have a look at how Python packages are packaged on Nix. Then, we will look how you can use development mode with your code.

Python packaging on Nix

On Nix all packages are built by functions. The main function in Nix for building Python packages is buildPythonPackage. Let's see how we would build the toolz package. According to python-packages.nix toolz is build using

toolz = buildPythonPackage rec{
  name = "toolz-${version}";
  version = "0.7.4";

  src = pkgs.fetchurl{
    url = "mirror://pypi/t/toolz/toolz-${version}.tar.gz";
    sha256 = "43c2c9e5e7a16b6c88ba3088a9bfc82f7db8e13378be7c78d6c14a5f8ed05afd";
  };

  meta = {
    homepage = "http://github.com/pytoolz/toolz/";
    description = "List processing tools and functional utilities";
    license = licenses.bsd3;
    maintainers = with maintainers; [ fridh ];
  };
};

What happens here? The function buildPythonPackage is called and as argument it accepts a set. In this case the set is a recursive set (rec). One of the arguments is the name of the package, which consists of a basename (generally following the name on PyPi) and a version. Another argument, src specifies the source, which in this case is fetched from an url. fetchurl not only downloads the target file, but also validates its hash. Furthermore, we specify some (optional) meta information.

The output of the function is a derivation, which is an attribute with the name toolz of the set pythonPackages. Actually, sets are created for all interpreter versions, so python27Packages, python34Packages, python35Packages and pypyPackages.

The above example works when you're directly working on pkgs/top-level/python-packages.nix in the Nixpkgs repository. Often though, you will want to test a Nix expression outside of the Nixpkgs tree. If you create a shell.nix file with the following contents

with import <nixpkgs> {};

pkgs.python35Packages.buildPythonPackage rec {
  name = "toolz-${version}";
  version = "0.7.4";

  src = pkgs.fetchurl{
    url = "mirror://pypi/t/toolz/toolz-${version}.tar.gz";
    sha256 = "43c2c9e5e7a16b6c88ba3088a9bfc82f7db8e13378be7c78d6c14a5f8ed05afd";
  };

  meta = {
    homepage = "http://github.com/pytoolz/toolz/";
    description = "List processing tools and functional utilities";
    license = licenses.bsd3;
    maintainers = with maintainers; [ fridh ];
  };
}

and then execute nix-shell will result in an environment in which you can use Python 3.5 and the toolz package. As you can see we had to explicitly mention for which Python version we want to build a package.

The above example considered only a single package. Generally you will want to use multiple packages. If we create a shell.nix file with the following contents

with import <nixpkgs> {};

( let
    toolz = pkgs.python35Packages.buildPythonPackage rec {
      name = "toolz-${version}";
      version = "0.7.4";

      src = pkgs.fetchurl{
        url = "mirror://pypi/t/toolz/toolz-${version}.tar.gz";
        sha256 = "43c2c9e5e7a16b6c88ba3088a9bfc82f7db8e13378be7c78d6c14a5f8ed05afd";
      };

      meta = {
        homepage = "http://github.com/pytoolz/toolz/";
        description = "List processing tools and functional utilities";
        license = licenses.bsd3;
        maintainers = with maintainers; [ fridh ];
      };
    };

  in pkgs.python35.buildEnv.override rec {

    extraLibs = [ pkgs.python35Packages.numpy toolz ];
}
).env

and again execute nix-shell, then we get a Python 3.5 environment with our locally defined package as well as numpy which is build according to the definition in Nixpkgs. What did we do here? Well, we took the Nix expression that we used earlier to build a Python environment, and said that we wanted to include our own version of toolz. To introduce our own package in the scope of buildEnv.override we used a let expression.

Handling dependencies

Our example, toolz, doesn't have any dependencies on other Python packages or system libraries. According to the manual, buildPythonPackage uses the arguments buildInputs and propagatedBuildInputs to specify dependencies. If something is exclusively a build-time dependency, then the dependency should be included as a buildInput, but if it is (also) a runtime dependency, then it should be added to propagatedBuildInputs. Test dependencies are considered build-time dependencies.

The following example shows which arguments are given to buildPythonPackage in order to build datashape.

datashape = buildPythonPackage rec {
  name = "datashape-${version}";
  version = "0.4.7";

  src = pkgs.fetchurl {
    url = "mirror://pypi/D/DataShape/${name}.tar.gz";
    sha256 = "14b2ef766d4c9652ab813182e866f493475e65e558bed0822e38bf07bba1a278";
  };

  buildInputs = with self; [ pytest ];
  propagatedBuildInputs = with self; [ numpy multipledispatch dateutil ];

  meta = {
    homepage = https://github.com/ContinuumIO/datashape;
    description = "A data description language";
    license = licenses.bsd2;
    maintainers = with maintainers; [ fridh ];
  };
};

We can see several runtime dependencies, numpy, multipledispatch, and dateutil. Furthermore, we have one buildInput, i.e. pytest. pytest is a test runner and is only used during the checkPhase and is therefore not added to propagatedBuildInputs.

In the previous case we had only dependencies on other Python packages to consider. Occasionally you have also system libraries to consider. E.g., lxml provides Python bindings to libxml2 and libxslt. These libraries are only required when building the bindings and are therefore added as buildInputs.

lxml = buildPythonPackage rec {
  name = "lxml-3.4.4";

  src = pkgs.fetchurl {
    url = "mirror://pypi/l/lxml/${name}.tar.gz";
    sha256 = "16a0fa97hym9ysdk3rmqz32xdjqmy4w34ld3rm3jf5viqjx65lxk";
  };

  buildInputs = with self; [ pkgs.libxml2 pkgs.libxslt ];

  meta = {
    description = "Pythonic binding for the libxml2 and libxslt libraries";
    homepage = http://lxml.de;
    license = licenses.bsd3;
    maintainers = with maintainers; [ sjourdois ];
  };
};

In this example lxml and Nix are able to work out exactly where the relevant files of the dependencies are. This is not always the case.

The example below shows bindings to The Fastest Fourier Transform in the West, commonly known as FFTW. On Nix we have separate packages of FFTW for the different types of floats ("single", "double", "long-double"). The bindings need all three types, and therefore we add all three as buildInputs. The bindings don't expect to find each of them in a different folder, and therefore we have to set LDFLAGS and CFLAGS.

pyfftw = buildPythonPackage rec {
  name = "pyfftw-${version}";
  version = "0.9.2";

  src = pkgs.fetchurl {
    url = "mirror://pypi/p/pyFFTW/pyFFTW-${version}.tar.gz";
    sha256 = "f6bbb6afa93085409ab24885a1a3cdb8909f095a142f4d49e346f2bd1b789074";
  };

  buildInputs = [ pkgs.fftw pkgs.fftwFloat pkgs.fftwLongDouble];

  propagatedBuildInputs = with self; [ numpy scipy ];

  # Tests cannot import pyfftw. pyfftw works fine though.
  doCheck = false;

  LDFLAGS="-L${pkgs.fftw}/lib -L${pkgs.fftwFloat}/lib -L${pkgs.fftwLongDouble}/lib"
  CFLAGS="-I${pkgs.fftw}/include -I${pkgs.fftwFloat}/include -I${pkgs.fftwLongDouble}/include"
  '';

  meta = {
    description = "A pythonic wrapper around FFTW, the FFT library, presenting a unified interface for all the supported transforms";
    homepage = http://hgomersall.github.com/pyFFTW/;
    license = with licenses; [ bsd2 bsd3 ];
    maintainer = with maintainers; [ fridh ];
  };
};

Note also the line doCheck = false;, we explicitly disabled running the test-suite.

Develop local package

As a Python developer you're likely aware of development mode (python setup.py develop); instead of installing the package this command creates a special link to the project code. That way, you can run updated code without having to reinstall after each and every change you make. Development mode is also available on Nix as explained in the Nixpkgs manual. Let's see how you can use it.

In the previous Nix expression the source was fetched from an url. We can also refer to a local source instead using

src = ./path/to/source/tree;

If we create a shell.nix file which calls buildPythonPackage, and if src is a local source, and if the local source has a setup.py, then development mode is activated.

In the following example we create a simple environment that has a Python 3.5 version of our package in it, as well as its dependencies and other packages we like to have in the environment, all specified with propagatedBuildInputs. Indeed, we can just add any package we like to have in our environment to propagatedBuildInputs.

with import <nixpkgs>;
with pkgs.python35Packages;

buildPythonPackage rec {
  name = "mypackage";
  src = ./path/to/package/source;
  propagatedBuildInputs = [ pytest numpy pkgs.libsndfile ];
};

It is important to note that due to how development mode is implemented on Nix it is not possible to have multiple packages simultaneously in development mode.

Organising your packages

So far we discussed how you can use Python on Nix, and how you can develop with it. We've looked at how you write expressions to package Python packages, and we looked at how you can create environments in which specified packages are available.

At some point you'll likely have multiple packages which you would like to be able to use in different projects. In order to minimise unnecessary duplication we now look at how you can maintain yourself a repository with your own packages. The important functions here are import and callPackage.

Including a derivation using `callPackage`

Earlier we created a Python environment using buildEnv, and included the toolz package via a let expression. Let's split the package definition from the environment definition.

We first create a function that builds toolz in ~/path/to/toolz/release.nix

{ pkgs, buildPythonPackage }:

buildPythonPackage rec {
  name = "toolz-${version}";
  version = "0.7.4";

  src = pkgs.fetchurl{
    url = "mirror://pypi/t/toolz/toolz-${version}.tar.gz";
    sha256 = "43c2c9e5e7a16b6c88ba3088a9bfc82f7db8e13378be7c78d6c14a5f8ed05afd";
  };

  meta = {
    homepage = "http://github.com/pytoolz/toolz/";
    description = "List processing tools and functional utilities";
    license = licenses.bsd3;
    maintainers = with maintainers; [ fridh ];
  };
};

It takes two arguments, pkgs and buildPythonPackage. We now call this function using callPackage in the definition of our environment

with import <nixpkgs> {};

( let
    toolz = pkgs.callPackage ~/path/to/toolz/release.nix { pkgs=pkgs; buildPythonPackage=pkgs.python35Packages.buildPythonPackage; };
  in pkgs.python35.buildEnv.override rec {
    extraLibs = [ pkgs.python35Packages.numpy  toolz ];
}
).env

Important to remember is that the Python version for which the package is made depends on the python derivation that is passed to buildPythonPackage. Nix tries to automatically pass arguments when possible, which is why generally you don't explicitly define which python derivation should be used. In the above example we use buildPythonPackage that is part of the set python35Packages, and in this case the python35 interpreter is automatically used.

Reference

Interpreters

Versions 2.6, 2.7, 3.3, 3.4 and 3.5 of the CPython interpreter are available on Nix and are available as python26, python27, python33, python34 and python35. The PyPy interpreter is also available as pypy. Currently, the aliases python and python3 correspond to respectively python27 and python35. The Nix expressions for the interpreters can be found in pkgs/development/interpreters/python.

Missing modules standard library

The interpreters python26 and python27 do not include modules that require external dependencies. This is done in order to reduce the closure size. The following modules need to be added as buildInput explicitly:

python.modules.bsddb
python.modules.curses
python.modules.curses_panel
python.modules.crypt
python.modules.gdbm
python.modules.sqlite3
python.modules.tkinter
python.modules.readline

For convenience python27Full and python26Full are provided with all modules included.

All packages depending on any Python interpreter get appended out/{python.sitePackages} to $PYTHONPATH if such directory exists.

Attributes on interpreters packages

Each interpreter has the following attributes:

libPrefix. Name of the folder in ${python}/lib/ for corresponding interpreter.
interpreter. Alias for ${python}/bin/${executable}.
buildEnv. Function to build python interpreter environments with extra packages bundled together. See section python.buildEnv function for usage and documentation.
sitePackages. Alias for lib/${libPrefix}/site-packages.
executable. Name of the interpreter executable, ie python3.4.

Building packages and applications

Python packages (libraries) and applications that use setuptools or distutils are typically built with respectively the buildPythonPackage and buildPythonApplication functions.

All Python packages reside in pkgs/top-level/python-packages.nix and all applications elsewhere. Some packages are also defined in pkgs/development/python-modules. It is important that these packages are called in pkgs/top-level/python-packages.nix and not elsewhere, to guarantee the right version of the package is built.

Based on the packages defined in pkgs/top-level/python-packages.nix an attribute set is created for each available Python interpreter. The available sets are

pkgs.python26Packages
pkgs.python27Packages
pkgs.python33Packages
pkgs.python34Packages
pkgs.python35Packages
pkgs.pypyPackages

and the aliases

pkgs.pythonPackages pointing to pkgs.python27Packages
pkgs.python3Packages pointing to pkgs.python35Packages

`buildPythonPackage` function

The buildPythonPackage function is implemented in pkgs/development/python-modules/generic/default.nix

and can be used as:

twisted = buildPythonPackage {
  name = "twisted-8.1.0";

  src = pkgs.fetchurl {
    url = http://tmrc.mit.edu/mirror/twisted/Twisted/8.1/Twisted-8.1.0.tar.bz2;
    sha256 = "0q25zbr4xzknaghha72mq57kh53qw1bf8csgp63pm9sfi72qhirl";
  };

  propagatedBuildInputs = [ self.ZopeInterface ];

  meta = {
    homepage = http://twistedmatrix.com/;
    description = "Twisted, an event-driven networking engine written in Python";
    license = stdenv.lib.licenses.mit; };
  };

The buildPythonPackage mainly does four things:

In the buildPhase, it calls ${python.interpreter} setup.py bdist_wheel to build a wheel binary zipfile.
In the installPhase, it installs the wheel file using pip install *.whl.
In the postFixup phase, the wrapPythonPrograms bash function is called to wrap all programs in the $out/bin/* directory to include $PYTHONPATH and $PATH environment variables.
In the installCheck phase, ${python.interpreter} setup.py test is ran.

As in Perl, dependencies on other Python packages can be specified in the buildInputs and propagatedBuildInputs attributes. If something is exclusively a build-time dependency, use buildInputs; if it’s (also) a runtime dependency, use propagatedBuildInputs.

By default tests are run because doCheck = true. Test dependencies, like e.g. the test runner, should be added to buildInputs.

By default meta.platforms is set to the same value as the interpreter unless overriden otherwise.

`buildPythonPackage` parameters

All parameters from mkDerivation function are still supported.

namePrefix: Prepended text to ${name} parameter. Defaults to "python3.3-" for Python 3.3, etc. Set it to "" if you're packaging an application or a command line tool.
disabled: If true, package is not build for particular python interpreter version. Grep around pkgs/top-level/python-packages.nix for examples.
setupPyBuildFlags: List of flags passed to setup.py build_ext command.
pythonPath: List of packages to be added into $PYTHONPATH. Packages in pythonPath are not propagated (contrary to propagatedBuildInputs).
preShellHook: Hook to execute commands before shellHook.
postShellHook: Hook to execute commands after shellHook.
makeWrapperArgs: A list of strings. Arguments to be passed to makeWrapper, which wraps generated binaries. By default, the arguments to makeWrapper set PATH and PYTHONPATH environment variables before calling the binary. Additional arguments here can allow a developer to set environment variables which will be available when the binary is run. For example, makeWrapperArgs = ["--set FOO BAR" "--set BAZ QUX"].
installFlags: A list of strings. Arguments to be passed to pip install. To pass options to python setup.py install, use --install-option. E.g., `installFlags=["--install-option='--cpp_implementation'"].

`buildPythonApplication` function

The buildPythonApplication function is practically the same as buildPythonPackage. The difference is that buildPythonPackage by default prefixes the names of the packages with the version of the interpreter. Because with an application we're not interested in multiple version the prefix is dropped.

python.buildEnv function

Python environments can be created using the low-level pkgs.buildEnv function. This example shows how to create an environment that has the Pyramid Web Framework. Saving the following as default.nix

with import {};

python.buildEnv.override {
  extraLibs = [ pkgs.pythonPackages.pyramid ];
  ignoreCollisions = true;
}

and running nix-build will create

/nix/store/cf1xhjwzmdki7fasgr4kz6di72ykicl5-python-2.7.8-env

with wrapped binaries in bin/.

You can also use the env attribute to create local environments with needed packages installed. This is somewhat comparable to virtualenv. For example, running nix-shell with the following shell.nix

with import {};

(python3.buildEnv.override {
  extraLibs = with python3Packages; [ numpy requests ];
}).env

will drop you into a shell where Python will have the specified packages in its path.

`python.buildEnv` arguments

extraLibs: List of packages installed inside the environment.
postBuild: Shell command executed after the build of environment.
ignoreCollisions: Ignore file collisions inside the environment (default is false).

Development mode

Development or editable mode is supported. To develop Python packages buildPythonPackage has additional logic inside shellPhase to run pip install -e . --prefix $TMPDIR/for the package.

Warning: shellPhase is executed only if setup.py exists.

Given a default.nix:

with import {};

buildPythonPackage { name = "myproject";

buildInputs = with pkgs.pythonPackages; [ pyramid ];

src = ./.; }

Running nix-shell with no arguments should give you the environment in which the package would be built with nix-build.

Shortcut to setup environments with C headers/libraries and python packages:

$ nix-shell -p pythonPackages.pyramid zlib libjpeg git

Note: There is a boolean value lib.inNixShell set to true if nix-shell is invoked.

Tools

Packages inside nixpkgs are written by hand. However many tools exist in community to help save time. No tool is preferred at the moment.

python2nix by Vladimir Kirillov
pypi2nix by Rok Garbas
pypi2nix by Jaka Hudoklin

FAQ

How to solve circular dependencies?

Consider the packages A and B that depend on each other. When packaging B, a solution is to override package A not to depend on B as an input. The same should also be done when packaging A.

How to override a Python package?

Recursively updating a package can be done with pkgs.overridePackages as explained in the Nixpkgs manual. Python attribute sets are created for each interpreter version. We will therefore override the attribute set for the interpreter version we're interested. In the following example we change the name of the package pandas to foo.

newpkgs = pkgs.overridePackages(self: super: rec {
  python35Packages = super.python35Packages.override {
    self = python35Packages // { pandas = python35Packages.pandas.override{name="foo";};};
  };
});

This can be tested with

with import <nixpkgs> {};

(let

newpkgs = pkgs.overridePackages(self: super: rec {
  python35Packages = super.python35Packages.override {
    self = python35Packages // { pandas = python35Packages.pandas.override{name="foo";};};
  };
});
in newpkgs.python35.buildEnv.override{
  extraLibs = [newpkgs.python35Packages.blaze ];
}).env

A typical use case is to switch to another version of a certain package. For example, in the Nixpkgs repository we have multiple versions of django and scipy. In the following example we use a different version of scipy. All packages in newpkgs will now use the updated scipy version.

with import <nixpkgs> {};

(let

newpkgs = pkgs.overridePackages(self: super: rec {
  python35Packages = super.python35Packages.override {
    self = python35Packages // { scipy = python35Packages.scipy_0_16;};
  };
});
in pkgs.python35.buildEnv.override{
  extraLibs = [newpkgs.python35Packages.blaze ];
}).env

The requested package blaze depends upon pandas which itself depends on scipy.

`install_data` / `data_files` problems

If you get the following error:

could not create '/nix/store/6l1bvljpy8gazlsw2aw9skwwp4pmvyxw-python-2.7.8/etc':
Permission denied

This is a known bug in setuptools. Setuptools install_data does not respect --prefix. An example of such package using the feature is pkgs/tools/X11/xpra/default.nix. As workaround install it as an extra preInstall step:

${python.interpreter} setup.py install_data --install-dir=$out --root=$out
sed -i '/ = data\_files/d' setup.py

Rationale of non-existent global site-packages

On most operating systems a global site-packages is maintained. This however becomes problematic if you want to run multiple Python versions or have multiple versions of certain libraries for your projects. Generally, you would solve such issues by creating virtual environments using virtualenv.

On Nix each package has an isolated dependency tree which, in the case of Python, guarantees the right versions of the interpreter and libraries or packages are available. There is therefore no need to maintain a global site-packages.

If you want to create a Python environment for development, then the recommended method is to use nix-shell, either with or without the python.buildEnv function.

Contributing

Contributing guidelines

Following rules are desired to be respected:

Make sure package builds for all python interpreters. Use disabled argument to buildPythonPackage to set unsupported interpreters.
If tests need to be disabled for a package, make sure you leave a comment about reasoning.
Packages in pkgs/top-level/python-packages.nix are sorted quasi-alphabetically to avoid merge conflicts.
Python libraries are supposed to be in python-packages.nix and packaged with buildPythonPackage. Python applications live outside of python-packages.nix and are packaged with buildPythonApplication.

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