32 KiB
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.withPackages (ps: [ps.numpy ps.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 thewith
statement brings all attributes ofnixpkgs
in the local scope. Therefore we can now usepkgs
. - Then we create a Python 3.5 environment with the
withPackages
function. - The
withPackages
function expects us to provide a function as an argument that takes the set of all python packages and returns a list of packages to include in the environment. Here, we select the packagesnumpy
andtoolz
from the package set. - And finally, for in interactive use we return the environment by using the
env
attribute.
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.withPackages (ps: [ps.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
withPackages
we used a
let
expression.
You can see that we used ps.numpy
to select numpy from the nixpkgs package set (ps
).
But we do not take toolz
from the nixpkgs package set this time.
Instead, toolz
will resolve to our local definition that we introduced with let
.
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.dev}/lib -L${pkgs.fftwFloat.out}/lib -L${pkgs.fftwLongDouble.out}/lib"
CFLAGS="-I${pkgs.fftw.dev}/include -I${pkgs.fftwFloat.dev}/include -I${pkgs.fftwLongDouble.dev}/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 withPackages
, 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.withPackages (ps: [ ps.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.withPackages
. Simpler interface tobuildEnv
. See section python.withPackages function for usage and documentation.sitePackages
. Alias forlib/${libPrefix}/site-packages
.executable
. Name of the interpreter executable, iepython3.4
.
Building packages and applications
Python packages (libraries) and applications that use setuptools
or
distutils
are typically built with respectively the buildPythonPackage
and
buildPythonApplication
functions.
All Python packages reside in pkgs/top-level/python-packages.nix
and all
applications elsewhere. Some packages are also defined in
pkgs/development/python-modules
. It is important that these packages are
called in pkgs/top-level/python-packages.nix
and not elsewhere, to guarantee
the right version of the package is built.
Based on the packages defined in pkgs/top-level/python-packages.nix
an
attribute set is created for each available Python interpreter. The available
sets are
pkgs.python26Packages
pkgs.python27Packages
pkgs.python33Packages
pkgs.python34Packages
pkgs.python35Packages
pkgs.pypyPackages
and the aliases
pkgs.pythonPackages
pointing topkgs.python27Packages
pkgs.python3Packages
pointing topkgs.python35Packages
buildPythonPackage
function
The buildPythonPackage
function is implemented in
pkgs/development/python-modules/generic/default.nix
and can be used as:
twisted = buildPythonPackage {
name = "twisted-8.1.0";
src = pkgs.fetchurl {
url = http://tmrc.mit.edu/mirror/twisted/Twisted/8.1/Twisted-8.1.0.tar.bz2;
sha256 = "0q25zbr4xzknaghha72mq57kh53qw1bf8csgp63pm9sfi72qhirl";
};
propagatedBuildInputs = [ self.ZopeInterface ];
meta = {
homepage = http://twistedmatrix.com/;
description = "Twisted, an event-driven networking engine written in Python";
license = stdenv.lib.licenses.mit; };
};
The buildPythonPackage
mainly does four things:
- In the
buildPhase
, it calls${python.interpreter} setup.py bdist_wheel
to build a wheel binary zipfile. - In the
installPhase
, it installs the wheel file usingpip install *.whl
. - In the
postFixup
phase, thewrapPythonPrograms
bash function is called to wrap all programs in the$out/bin/*
directory to include$PATH
environment variable and add dependent libraries to script'ssys.path
. - 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
: Iftrue
, package is not build for particular python interpreter version. Grep aroundpkgs/top-level/python-packages.nix
for examples.setupPyBuildFlags
: List of flags passed tosetup.py build_ext
command.pythonPath
: List of packages to be added into$PYTHONPATH
. Packages inpythonPath
are not propagated (contrary topropagatedBuildInputs
).preShellHook
: Hook to execute commands beforeshellHook
.postShellHook
: Hook to execute commands aftershellHook
.makeWrapperArgs
: A list of strings. Arguments to be passed tomakeWrapper
, which wraps generated binaries. By default, the arguments tomakeWrapper
setPATH
andPYTHONPATH
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 topip install
. To pass options topython setup.py install
, use--install-option
. E.g., `installFlags=["--install-option='--cpp_implementation'"].format
: Format of the source. Options aresetup
for when the source has asetup.py
andsetuptools
is used to build a wheel, andwheel
in case the source is already a binary wheel. The default value issetup
.catchConflicts
Iftrue
, abort package build if a package name appears more than once in dependency tree. Default istrue
.
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 <nixpkgs> {};
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 <nixpkgs> {};
(python3.buildEnv.override {
extraLibs = with python3Packages; [ numpy requests2 ];
}).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 isfalse
).
python.withPackages function
The python.withPackages
function provides a simpler interface to the python.buildEnv
functionality.
It takes a function as an argument that is passed the set of python packages and returns the list
of the packages to be included in the environment. Using the withPackages
function, the previous
example for the Pyramid Web Framework environment can be written like this:
with import <nixpkgs> {};
python.withPackages (ps: [ps.pyramid])
withPackages
passes the correct package set for the specific interpreter version as an
argument to the function. In the above example, ps
equals pythonPackages
.
But you can also easily switch to using python3:
with import <nixpkgs> {};
python3.withPackages (ps: [ps.pyramid])
Now, ps
is set to python3Packages
, matching the version of the interpreter.
As python.withPackages
simply uses python.buildEnv
under the hood, it also supports the env
attribute. The shell.nix
file from the previous section can thus be also written like this:
with import <nixpkgs> {};
(python33.withPackages (ps: [ps.numpy ps.requests2])).env
In contrast to python.buildEnv
, python.withPackages
does not support the more advanced options
such as ignoreCollisions = true
or postBuild
. If you need them, you have to use python.buildEnv
.
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 <nixpkgs> {};
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 can I install a working Python environment?
As explained in the user's guide installing individual Python packages
imperatively with nix-env -i
or declaratively in environment.systemPackages
is not supported. However, it is possible to install a Python environment with packages (python.buildEnv
).
In the following examples we create an environment with Python 3.5, numpy
and ipython
.
As you might imagine there is one limitation here, and that's you can install
only one environment at a time. You will notice the complaints about collisions
when you try to install a second environment.
Environment defined in separate .nix
file
Create a file, e.g. build.nix
, with the following expression
with import <nixpkgs> {};
with python35Packages;
python.withPackages (ps: with ps; [ numpy ipython ])
and install it in your profile with
nix-env -if build.nix
Now you can use the Python interpreter, as well as the extra packages that you added to the environment.
Environment defined in ~/.nixpkgs/config.nix
If you prefer to, you could also add the environment as a package override to the Nixpkgs set.
packageOverrides = pkgs: with pkgs; with python35Packages; {
myEnv = python.withPackages (ps: with ps; [ numpy ipython ]);
};
and install it in your profile with
nix-env -iA nixos.blogEnv
Note that I'm using the attribute path here.
Environment defined in /etc/nixos/configuration.nix
For the sake of completeness, here's another example how to install the environment system-wide.
environment.systemPackages = with pkgs; [
(python35Packages.python.withPackages (ps: callPackage ../packages/common-python-packages.nix { pythonPackages = ps; }))
];
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.withPackages (ps: [ps.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 newpkgs.python35.withPackages (ps: [ps.blaze])
).env
The requested package blaze
depends upon pandas
which itself depends on scipy
.
python setup.py bdist_wheel
cannot create .whl
Executing python setup.py bdist_wheel
fails with
ValueError: ZIP does not support timestamps before 1980
This is because files are included that depend on items in the Nix store which have a timestamp of, that is, it corresponds to January the 1st, 1970 at 00:00:00. And as the error informs you, ZIP does not support that.
Fortunately bdist_wheel
takes into account SOURCE_DATE_EPOCH
. On Nix this value is set to 1. By setting it to a value correspond to 1980 or later it is possible to build wheels.
Use 1980 as timestamp:
SOURCE_DATE_EPOCH=315532800 python3 setup.py bdist_wheel
or the current time:
SOURCE_DATE_EPOCH=$(date +%s) python3 setup.py bdist_wheel
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 tobuildPythonPackage
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 withbuildPythonPackage
. Python applications live outside ofpython-packages.nix
and are packaged withbuildPythonApplication
.