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Re: Proposal for a blog contribution on reproducible computations
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From: |
zimoun |
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Subject: |
Re: Proposal for a blog contribution on reproducible computations |
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Date: |
Thu, 9 Jan 2020 21:40:29 +0100 |
Hi Konrad,
Thank you! It is very interesting!!
Below questions.
And suggestions which I can Pull-Request with Github. :-)
Hope it is readable: indented text is your text; non-indented one is question.
Cheers,
simon
--
#+TITLE: Reproducible computations with Guix
#+STARTUP: inlineimages
* Dependencies: what it takes to run a program
Move this section title below.
This post is about reproducible computations, so let's start with a
computation. A short, though rather uninteresting, C program is a good
starting point. It computes π in three different ways:
#+begin_src c :tangle pi.c :eval no
#include <math.h>
#include <stdio.h>
int main()
{
printf( "M_PI : %.10lf\n", M_PI);
printf( "4 * atan(1.) : %.10lf\n", 4.*atan(1.));
printf( "Leibniz' formula (four terms): %.10lf\n",
4.*(1.-1./3.+1./5.-1./7.));
return 0;
}
#+end_src
Align ':' for easier looking.
This program uses no random element, such as a random number generator
or parallelism. It's strictly deterministic. It is reasonable to expect
it to produce exactly the same output, on any computer and at any point
in time. And yet, many programs whose results /should/ be perfectly
reproducible are in fact not. Programs using floating-point arithmetic,
such as this short example, are particularly prone to seemingly
inexplicable variations.
My goal is to explain why deterministic programs often fail to be
reproducible, and what it takes to fix this. The short answer to that
question is "use Guix", but even though Guix provides excellent support
for reproducibility, you still have to use it correctly, and that
requires some understanding of what's going on. The explanation I will
give is rather detailed, to the point of discussing parts of the Guile
API of Guix. You should be able to follow the reasoning without knowing
Guile though, you will just have to believe me that the scripts I will
show do what I claim they do. And in the end, I will provide a
ready-to-run Guile script that will let you explore package dependencies
right from the shell.
* Dependencies: what it takes to run a program
One keyword in discussions of reproducibility is "dependencies". I will
revisit the exact meaning of this term later, but to get started, I will
define it loosely as "any software package required to run a program".
Running the π computation shown above is normally done using something
like
#+begin_src sh :exports code :eval no
gcc pi.c -o pi && ./pi
#+end_src
Missing '&&'. It does not work without on my machine.
C programmers know that =gcc= is a C compiler, so that's one obvious
dependency for running our little program. But is a C compiler enough?
That question is surprisingly difficult to answer in practice. Your
computer is loaded with tons of software (otherwise it wouldn't be very
useful), and you don't really know what happens behind the scenes when
you run =gcc= or =pi=.
** Container is good
A major element of reproducibility support in Guix is the possibility to
run programs in well-defined environments that contain exactly the
software packages you request, and no more. So if your program runs in
an environment that contains only a C compiler, you can be sure it has
no other dependencies. Let's create such an environment:
#+begin_src sh :session C-compiler :results output :exports both
guix environment --container --ad-hoc gcc-toolchain
#+end_src
#+RESULTS:
The option =--container= ensures the best possible isolation from the
standard environment that your system installation and user account
provide for day-to-day work. This environment contains nothing but a C
compiler and a shell (which you need to type in commands), and has
access to no other files than those in the current directory.
Side note: the option =--container= requires support from the Linux
kernel that is not available on all systems. If it doesn't work for you,
use =--pure= instead. It provides a less isolated environment, but it is
usually more than good enough.
By default, I get:
--8<---------------cut here---------------start------------->8---
guix environment: error: cannot create container: unprivileged user
cannot create user namespaces
guix environment: error: please set
/proc/sys/kernel/unprivileged_userns_clone to "1"
--8<---------------cut here---------------end--------------->8---
Or a sentence explaining what to do. For example, "The =--container= option
requires allowing the kernel to clone for the unprivileged user, i.e., as
=root= just run the command
=echo 1 > /proc/sys/kernel/unprivileged_userns_clone=."
The above command leaves me in a shell inside my environment, where I
can now compile and run my little program:
#+begin_src sh :session C-compiler :results output :exports both
gcc pi.c -o pi && ./pi
#+end_src
Missing again '&&'. Sorry if it is me.
#+RESULTS:
: M_PI : 3.14159265358979311600
: 4 * atan(1.) : 3.14159265358979311600
: Leibniz' formula (four terms): 2.89523809523809561028
It works! So now I can be sure that my program has a single dependency:
the Guix package =gcc-toolchain=. Perfectionists who want to exclude
the possibility that my program requires a shell could run each step in
a separate container:
#+begin_src sh :results output :exports both
guix environment --container --ad-hoc gcc-toolchain -- gcc pi.c -o pi
guix environment --container --ad-hoc gcc-toolchain -- ./pi
#+end_src
#+RESULTS:
: M_PI : 3.14159265358979311600
: 4 * atan(1.) : 3.14159265358979311600
: Leibniz' formula (four terms): 2.89523809523809561028
** Let open the dependencies hell
Now that we know that our only dependency is =gcc-toolchain=, let's look
at it in more detail:
#+begin_src sh :results output :exports both
guix show gcc-toolchain
#+end_src
#+RESULTS:
#+begin_example
name: gcc-toolchain
version: 9.2.0
outputs: out debug static
systems: x86_64-linux i686-linux
dependencies: binutils@2.32 gcc@9.2.0 glibc@2.29 ld-wrapper@0
location: gnu/packages/commencement.scm:2532:4
homepage: https://gcc.gnu.org/
license: GPL 3+
synopsis: Complete GCC tool chain for C/C++ development
description: This package provides a complete GCC tool chain for C/C++
+ development to be installed in user profiles. This includes
GCC, as well as
+ libc (headers an d binaries, plus debugging symbols in the
`debug' output),
+ and Binutils.
name: gcc-toolchain
version: 8.3.0
outputs: out debug static
systems: x86_64-linux i686-linux
dependencies: binutils@2.32 gcc@8.3.0 glibc@2.29 ld-wrapper@0
location: gnu/packages/commencement.scm:2532:4
homepage: https://gcc.gnu.org/
license: GPL 3+
synopsis: Complete GCC tool chain for C/C++ development
description: This package provides a complete GCC tool chain for C/C++
+ development to be installed in user profiles. This includes
GCC, as well as
+ libc (headers an d binaries, plus debugging symbols in the
`debug' output),
+ and Binutils.
[...]
#+end_example
Guix actually knows about several versions of this toolchain. We didn't
ask for a specific one, so what we got is the first one in this list,
which is the one with the highest version number. Let's check that this
is true:
#+begin_src sh :results output :exports both
guix environment --container --ad-hoc gcc-toolchain -- gcc --version
#+end_src
#+RESULTS:
: gcc (GCC) 9.2.0
: Copyright (C) 2019 Free Software Foundation, Inc.
: This is free software; see the source for copying conditions.
There is NO
: warranty; not even for MERCHANTABILITY or FITNESS FOR A
PAR1TICULAR PURPOSE.
:
The output of =guix show= contains a line about dependencies. These are
the dependencies of our dependency, and you may already have guessed
that they will have dependencies as well. That's why reproducibility is
such a difficult job in practice! The dependencies of
=gcc-toolchain@9.2.0= are:
Let use =recsel= and teach also how to filter the package output. :-)
#+begin_src sh :results output :exports both
guix show gcc-toolchain@9.2.0 | recsel -P dependencies
#+end_src
#+RESULTS:
: binutils@2.32 gcc@9.2.0 glibc@2.29 ld-wrapper@0
#+begin_example
binutils@2.32 gcc@9.2.0 glibc@2.29 ld-wrapper@0
#+end_example
To dig deeper, we can try feeding these dependencies to =guix show=, one
by one, in order to learn more about them:
#+begin_src sh :results output :exports both
guix show binutils@2.32
#+end_src
#+RESULTS:
#+begin_example
name: binutils
version: 2.32
outputs: out
systems: x86_64-linux i686-linux
dependencies:
location: gnu/packages/base.scm:415:2
homepage: https://www.gnu.org/software/binutils/
license: GPL 3+
synopsis: Binary utilities: bfd gas gprof ld
description: GNU Binutils is a collection of tools for working with binary
+ files. Perhaps the most notable are "ld", a linker, and "as",
an assembler.
+ Other tools include programs to display binary profiling
information, list the
+ strings in a binary file, and utilities for working with
archives. The "bfd"
+ library for working with executable and object formats is also included.
#+end_example
#+begin_src sh :results output :exports both
exec 2>&1 guix show gcc@9.2.0 :
#+end_src
#+RESULTS:
: guix show: error: gcc@9.2.0: package not found
This looks a bit surprising. What's happening here is that =gcc= is
defined as a /hidden package/ in Guix. The package is there, but it is
hidden from package queries. There is a good reason for this: =gcc= on
its own is rather useless, you need =gcc-toolchain= to actually use the
compiler. But if both =gcc= and =gcc-toolchain= showed up in a search,
that would be more confusing than helpful for most users. Hiding the
package is a way of saying "for experts only".
Let's take this as a sign that it's time to move on to the next level of
Guix hacking: Guile scripts. Guile, an implementation of the Scheme
language, is Guix' native language, so using Guile scripts, you get
access to everything there is to know about Guix and its packages.
A note in passing: the
[[https://emacs-guix.gitlab.io/website/][emacs-guix]] package provides
an intermediate level
of Guix exploration for Emacs users. It lets you look at hidden
packages, for example. But much of what I will show in the following
really requires Guile scripts.
* Anatomy of a Guix package
From the user's point of view, a package is a piece of software with a
name and a version number that can be installed using =guix install=.
The packager's point of view is quite a bit different. In fact, what
users consider a package is more precisely called the package's /output/
in Guix jargon. The package is a recipe for creating this output.
To see how all these concepts fit together, let's look at an example of
a package definition: =xmag=. I have chosen this package not because I
care much about it, but because its definition is short while showcasing
all the features I want to explain. You can access it most easily by
typing =guix edit xmag=. Here is what you will see:
#+begin_src scheme :eval no
(package
(name "xmag")
(version "1.0.6")
(source
(origin
(method url-fetch)
(uri (string-append
"mirror://xorg/individual/app/" name "-" version ".tar.gz"))
(sha256
(base32
"19bsg5ykal458d52v0rvdx49v54vwxwqg8q36fdcsv9p2j8yri87"))))
(build-system gnu-build-system)
(arguments
`(#:configure-flags
(list (string-append "--with-appdefaultdir="
%output ,%app-defaults-dir))))
(inputs
`(("libxaw" ,libxaw)))
(native-inputs
`(("pkg-config" ,pkg-config)))
(home-page "https://www.x.org/wiki/";)
(synopsis "Display or capture a magnified part of a X11 screen")
(description "Xmag displays and captures a magnified snapshot
of a portion
of an X11 screen.")
(license license:x11))
#+end_src
After, a package (=glibc=) is used to show that the same package can produce
different outputs and this above example does not own the =outputs= fields.
The package definition starts with the name and version information you
expected. Next comes =source=, which says how to obtain the source code
and from where. It also provides a hash that allows to check the
integrity of the downloaded files. The next four items, =build-system=,
=arguments=, =inputs=, and =native-inputs= supply the information
required for /building/ the package, which is what creates its outputs.
The remaining items are documentation for human consumption, important
for other reasons but not for reproducibility, so I won't say any more
about them.
Link to the documentation and/or the cookbook entry about Packaging.
http://guix.gnu.org/manual/devel/en/html_node/Defining-Packages.html#Defining-Packages
http://guix.gnu.org/cookbook/en/html_node/Packaging.html#Packaging
The example package definition has =native-inputs= in addition to
"plain" =inputs=. There's a third variant, =propagated-inputs=, but
=xmag= doesn't have any. The differences between these variants don't
matter for my topic, so I will just refer to "inputs" from now
on. Another omission I will make is the possibility to define several
outputs for a package. This is done for particularly big packages, in
order to reduce the footprint of installations, but for the purposes of
reproducibility, it's OK to treat all outputs of a package a single
unit.
The following figure illustrates how the various pieces of information
from a package are used in the build process (done explicitly by =guix
build=, or implicitly when installing or otherwise using a package):
[[file:guix-package.svg]]
It may help to translate the Guix jargon to the vocabulary of C
programming:
| Guix package | C program |
|--------------+------------------|
| source code | source code |
| inputs | libraries |
| arguments | compiler options |
| build system | compiler |
| output | executable |
Building a package can be considered a generalization of compiling a
program. We could in fact create a "GCC build system" for Guix that
would simply run =gcc=. However, such a build system would be of little
practical use, since most real-life software consists of more than just
one C source code file, and requires additional pre- or post-processing
steps. The =gnu-build-system= used in the example is based on tools
such as =make= and =autoconf=, in addition to =gcc=.
* Package exploration in Guile
Guile uses a record type called =<package>= to represent packages, which
is
[[https://git.savannah.gnu.org/cgit/guix.git/tree/guix/packages.scm#n249][=<package>=]]
(hyperlink). Let spread Scheme. :-)
Is the syntax highlighting available for Savannah?
defined in module =(guix packages)=. There is also a module =(gnu
packages)=, which contains the actual package definitions - be careful
not
[[https://git.savannah.gnu.org/cgit/guix.git/tree/gnu/packages][=(gnu
packages)=]] (hyperlink).
to confuse the two (as I always do). Here is a simple Guile script that
shows some package information, much like the =guix show= command that I
used earlier:
#+begin_src scheme :results output
(use-modules (guix packages)
(gnu packages))
(define gcc-toolchain
(specification->package "gcc-toolchain"))
(format #t "Name : ~a\n" (package-name gcc-toolchain))
(format #t "Version: ~a\n" (package-version gcc-toolchain))
(format #t "Inputs : ~a\n" (package-direct-inputs gcc-toolchain))
#+end_src
#+RESULTS:
: Name : gcc-toolchain
: Version: 8.3.0
: Inputs : ((gcc #<package gcc@8.3.0 gnu/packages/gcc.scm:509
3b969a0>) (ld-wrapper #<package ld-wrapper@0 gnu/packages/base.scm:551
43e6bb0>) (binutils #<package binutils@2.31.1
gnu/packages/bootstrap.scm:150 43df6e0>) (libc #<package glibc@2.28
gnu/packages/commencement.scm:681 43df8f0>) (libc-debug #<package
glibc@2.28 gnu/packages/commencement.scm:681 43df8f0> debug)
(libc-static #<package glibc@2.28 gnu/packages/commencement.scm:681
43df8f0> static))
I would add something about =guix repl=. For example, "You can launch an
interactive REPL with =guix repl= and type directly these lines inside."
Adding also a footnote saying to add
#+begin_src scheme
(use-modules
(ice-9 readline)
(ice-9 format)
(ice-9 pretty-print))
(activate-readline)
#+end_src
in =~/.guile= to ease the REPL experience.
This script first calls =specification->package= to look up the package
using the same rules as the =guix= command line interface: pick the
latest available version if none is explicitly requested. Then it
extracts various information about the package. Note that
=package-direct-inputs= returns the combination of =package-inputs=,
=package-native-inputs=, and =package-propagated-inputs=. As I said
above, I don't care about the distinction here.
The inputs are not shown in a particularly nice form, so let's write two
Guile functions to improve it:
#+begin_src scheme :results output
(use-modules (guix packages)
(gnu packages)
(ice-9 match))
(define (package->specification package)
(format #f "~a@~a"
(package-name package)
(package-version package)))
(define (input->specification input)
(match input
((label (? package? package) . _)
(package->specification package))
(other-item
(format #f "~a" other-item))))
(define gcc-toolchain
(specification->package "gcc-toolchain"))
(format #t "Package: ~a\n"
(package->specification gcc-toolchain))
(format #t "Inputs : ~a\n"
(map input->specification (package-direct-inputs gcc-toolchain)))
#+end_src
#+RESULTS:
: Package: gcc-toolchain@8.3.0
: Inputs : (gcc@8.3.0 ld-wrapper@0 binutils@2.31.1 glibc@2.28
glibc@2.28 glibc@2.28)
That looks much better. As you can see from the code, a list of inputs
is a bit more than a list of packages. It is in fact a list of labelled
/package outputs/. That also explains why we see =glibc= three times in
the input list: =glibc= defines three distinct outputs, all of which are
used in =gcc-toolchain=.
It is not clear to me why there is 3 times =glibc=. Instead, I propose this.
#+begin_src scheme :results output
(use-modules (guix packages)
(gnu packages)
(ice-9 match))
(define (package->specification package)
(format #f "~a@~a"
(package-name package)
(package-version package)))
(define (input->specification input)
(match input
((label (? package? package) . _)
(package->specification package))
(other-item
(format #f "~a" other-item))))
(define gcc-toolchain
(specification->package "gcc-toolchain"))
(format #t "Package : ~a\n"
(package->specification gcc-toolchain))
(format #t "Inputs : ~a\n"
(map input->specification (package-direct-inputs gcc-toolchain)))
(format #t "Internals: ~a\n"
(map car (package-direct-inputs gcc-toolchain)))
(display "\n")
(define glibc
(specification->package "glibc"))
(format #t "Name : ~a\n"
(package-name glibc))
(format #t "Outputs : ~a\n"
(package-outputs glibc))
#+end_src
#+RESULTS:
: Package : gcc-toolchain@8.3.0
: Inputs : (gcc@8.3.0 ld-wrapper@0 binutils@2.31.1 glibc@2.28
glibc@2.28 glibc@2.28)
: Internals: (gcc ld-wrapper binutils libc libc-debug libc-static)
:
: Name : glibc
: Outputs : (out debug static)
The =car= is not so nice but the =Internals= mitigates, IMHO.
The addition does not add complexity and I hope it clarifies, at least to
me. ;-)
For reproducibility, all we care about is the package references. Later
on, we will deal with much longer input lists, so as a final cleanup
step, let's show only unique package references from the list of inputs:
#+begin_src scheme :results output
(use-modules (guix packages)
(gnu packages)
(srfi srfi-1)
(ice-9 match))
(define (package->specification package)
(format #f "~a@~a"
(package-name package)
(package-version package)))
(define (input->specification input)
(match input
((label (? package? package) . _)
(package->specification package))
(other-item
(format #f "~a" other-item))))
(define (unique-inputs inputs)
(delete-duplicates
(map input->specification inputs)))
(define gcc-toolchain
(specification->package "gcc-toolchain"))
(format #t "Package: ~a\n"
(package->specification gcc-toolchain))
(format #t "Inputs : ~a\n"
(unique-inputs (package-direct-inputs gcc-toolchain)))
#+end_src
#+RESULTS:
: Package: gcc-toolchain@8.3.0
: Inputs : (gcc@8.3.0 ld-wrapper@0 binutils@2.31.1 glibc@2.28)
* Dependencies
You may have noticed the absence of the term "dependency" from the last
two sections. There is a good reason for that: the term is used in
somewhat different meanings, and that can create confusion. Guix jargon
therefore avoids it.
The figure above shows three kinds of input to the build system: source,
inputs, and arguments. These categories reflect the packagers' point of
view: =source= is what the authors of the software supply, =inputs= are
other packages, and =arguments= is what the packagers themselves add to
the build procedure. It is important to understand that from a purely
technical point of view, there is no fundamental difference between the
three categories. You could, for example, define a package that contains
C source code in the build system =arguments=, but leaves =source=
empty. This would be inconvenient, and confusing for others, so I don't
recommend you actually do this. The three categories are important, but
for humans, not for computers. In fact, even the build system is not
fundamentally distinct from its inputs. You could define a
special-purpose build system for one package, and put all the source
code in there. At the level of the CPU and the computer's memory, a
build process (as in fact /any/ computation) looks like
[[file:computation.png]]
It is human interpretation that decomposes this into
[[file:data-code.png]]
and in a next step into
[[file:data-program-environment.png]]
We can go on and divide the environment into operating system,
development tools, and application software, for example, but the
further we go in decomposing the input to a computation, the more
arbitrary it gets.
From this point of view, a software's dependencies consist of everything
required to run it in addition to its source code. For a Guix package,
the dependencies are thus,
Adding ',' after 'thus'.
- its inputs
- the build system arguments
- the build system itself
- Guix (commit)
- the GNU/Linux operating system (kernel).
Adding (commit) and (kernel).
In the following, I will not mention the last two items any more,
because they are a common dependency of all Guix packages, but it's
important not to forget about them. A change in Guix or in GNU/Linux can
actually make a computation non-reproducible, although in practice that
happens very rarely. Moreover, Guix is actually designed to run older
versions of itself, as we will see later.
Hum? the assumption is the "GNU/Linux operating system" on which Guix
(package manager) is running does not change the reproducibility of the
computations. Right?
In practise, the results should be the same using the same Guix (commit) on
different GNU/Linux operating systems and from my understanding we are
missing data (experience) to report if it happens or not.
However, a change in Guix can lead to completely different packages, so
non-reproducible computations. And in practise it happens often, e.g., see how
many grafts Guix is doing. :-)
Well, I am not sure if I understand correctly the meaning of this paragraph.
* Build systems are packages as well
I hope that by now you have a good idea of what a package is: a recipe
for building outputs from source and inputs, with inputs being the
outputs of other packages. The recipe involves a build system and
arguments supplied to it. So... what exactly is a build system? I have
introduced it as a generalization of a compiler, which describes its
role. But where does a build system come from in Guix?
The ultimate answer is of course the
[[https://git.savannah.gnu.org/cgit/guix.git/tree/guix/build-system][sourcecode]].
Build systems are
pieces of Guile code that are part of Guix. But this Guile code is only
a shallow layer orchestrating invocations of other software, such as
=gcc= or =make=. And that software is defined by packages. So in the
end, from a reproducibility point of view, we can replace the "build
system" item in our list of dependenies by "a bundle of packages". In
other words: more inputs.
Before Guix can build a package, it must gather all the required
ingredients, and that includes replacing the build system by the
packages it represents. The resulting list of ingredients is called a
=bag=, and we can access it using a Guile script:
#+begin_src scheme :results output
(use-modules (guix packages)
(gnu packages)
(srfi srfi-1)
(ice-9 match))
(define (package->specification package)
(format #f "~a@~a"
(package-name package)
(package-version package)))
(define (input->specification input)
(match input
((label (? package? package) . _)
(package->specification package))
((label (? origin? origin))
(format #f "[source code from ~a]"
(origin-uri origin)))
(other-input
(format #f "~a" other-input))))
(define (unique-inputs inputs)
(delete-duplicates
(map input->specification inputs)))
(define hello
(specification->package "hello"))
(format #t "Package : ~a\n"
(package->specification hello))
(format #t "Package inputs: ~a\n"
(unique-inputs (package-direct-inputs hello)))
(format #t "Build inputs : ~a\n"
(unique-inputs
(bag-direct-inputs
(package->bag hello))))
#+end_src
#+RESULTS:
: Package : hello@2.10
: Package inputs: ()
: Build inputs : ([source code from
mirror://gnu/hello/hello-2.10.tar.gz] tar@1.30 gzip@1.9 bzip2@1.0.6
xz@5.2.4 file@5.33 diffutils@3.6 patch@2.7.6 findutils@4.6.0
gawk@4.2.1 sed@4.5 grep@3.1 coreutils@8.30 make@4.2.1
bash-minimal@4.4.23 ld-wrapper@0 binutils@2.31.1 gcc@5.5.0 glibc@2.28
glibc-utf8-locales@2.28)
I have used a different example, =hello=,
[[https://git.savannah.gnu.org/cgit/guix.git/tree/gnu/packages/base.scm#n72][=hello=]]
(link to package definition)
because for =gcc-toolchain=,
there is no difference between package inputs and build inputs (check
for yourself if you want!) My new example, =hello= (a short demo
[[https://hpc.guix.info/package/hello][=hello=]] (link to browser)
program printing "Hello, world" in the language of the system
installation), is interesting because it has no package inputs at all.
All the build inputs except for the source code have thus been
contributed by the build system.
If you compare this script to the previous one that printed only the
package inputs, you will notice two major new features. In
=input->specification=, there is an additional case for the source code
reference. And in the last statement, =package->bag= constructs a bag
from the package, before =bag-direct-inputs= is called to get that bag's
input list.
* Inputs are outputs
I have mentioned before that one package's inputs are other packages'
outputs, but that fact deserves a more in-depth discussion because of
its crucial importance for reproducibility. A package is a recipe for
building outputs from source and inputs. Since these inputs are outputs,
they must have been built as well. Package building is therefore a
process consisting of multiple steps. An immediate consequence is that
any computation making use of packaged software is a multi-step
computation as well.
Remember the short C program computing π from the beginning of this
post? Running that program is only the last step in a long series of
computations. Before you can run =pi=, you must compile =pi.c=. That
requires the package =gcc-toolchain=, which must first be built. And
before it can be built, its inputs must be built. And so on. If you
want the output of =pi= to be reproducible, *the whole chain of
computations must be reproducible*, because each step can have an impact
on the results produced by =pi=.
So... where does this chain start? Few people write machine code these
days, so almost all software requires some compiler or interpreter. And
that means that for every package, there are other packages that must be
built first. The question of how to get this chain started is known as
the bootstrapping problem. A rough summary of the solution is that the
chain starts on somebody else's computer, which creates a bootstrap
seed, an ideally small package that is downloaded in precompiled form.
See
[[https://guix.gnu.org/blog/2019/guix-reduces-bootstrap-seed-by-50/][this
post by Jan Nieuwenhuizen]] for details of this procedure. The
bootstrap seed is not the real start of the chain, but as long as we can
retrieve an identical copy at a later time, that's good enough for
reproducibility. In fact, the reason for requiring the bootstrap seed to
be small is not reproducibility, but inspectability: it should be
possible to audit the seed for bugs and malware, even in the absence of
source code.
** Closure of bag
Now we are finally ready for the ultimate step in dependency analysis:
identifying all packages on which a computation depends, right up to the
bootstrap seed. The starting point is the list of direct inputs of the
bag derived from a package, which we looked at in the previous
script. For each package in that list, we must apply this same
procedure, recursively. We don't have to write this code ourselves,
because the function =package-closure= in Guix does that job. If you
have a basic knowledge of Scheme, you should be able to understand its
[[https://git.savannah.gnu.org/cgit/guix.git/tree/guix/packages.scm#n817][implementation]]
now. Let's add it to our dependency analysis code:
#+begin_src scheme :results output
(use-modules (guix packages)
(gnu packages)
(srfi srfi-1)
(ice-9 match))
(define (package->specification package)
(format #f "~a@~a"
(package-name package)
(package-version package)))
(define (input->specification input)
(match input
((label (? package? package) . _)
(package->specification package))
((label (? origin? origin))
(format #f "[source code from ~a]"
(origin-uri origin)))
(other-input
(format #f "~a" other-input))))
(define (unique-inputs inputs)
(delete-duplicates
(map input->specification inputs)))
(define (length-and-list lists)
(list (length lists) lists))
(define hello
(specification->package "hello"))
(format #t "Package : ~a\n"
(package->specification hello))
(format #t "Package inputs : ~a\n"
(length-and-list (unique-inputs (package-direct-inputs hello))))
(format #t "Build inputs : ~a\n"
(length-and-list
(unique-inputs
(bag-direct-inputs
(package->bag hello)))))
(format #t "Package closure: ~a\n"
(length-and-list
(delete-duplicates
(map package->specification
(package-closure (list hello))))))
#+end_src
#+RESULTS:
: Package : hello@2.10
: Package inputs : (0 ())
: Build inputs : (20 ([source code from
mirror://gnu/hello/hello-2.10.tar.gz] tar@1.30 gzip@1.9 bzip2@1.0.6
xz@5.2.4 file@5.33 diffutils@3.6 patch@2.7.6 findutils@4.6.0
gawk@4.2.1 sed@4.5 grep@3.1 coreutils@8.30 make@4.2.1
bash-minimal@4.4.23 ld-wrapper@0 binutils@2.31.1 gcc@5.5.0 glibc@2.28
glibc-utf8-locales@2.28))
: Package closure: (62 (gzip@1.9 libstdc++-boot0@4.9.4
gcc-cross-boot0@5.5.0 m4@1.4.18 linux-libre-headers@4.14.67
gettext-boot0@0.19.8.1 bison@3.0.5 guile-bootstrap@2.0
glibc-intermediate@2.28 gcc-cross-boot0-wrapped@5.5.0
perl-boot0@5.28.0 bootstrap-binaries@0 file-boot0@5.33
findutils-boot0@4.6.0 diffutils-boot0@3.6 make-boot0@4.2.1
binutils-cross-boot0@2.31.1 ld-wrapper-boot0@0 zlib@1.2.11
libstdc++@5.5.0 ld-wrapper-boot3@0 bash-static@4.4.23 texinfo@6.5
libatomic-ops@7.6.6 pkg-config@0.29.2 gmp@6.1.2 libgc@7.6.6
libltdl@2.4.6 libunistring@0.9.10 libffi@3.2.1 guile@2.2.4 expat@2.2.6
perl@5.28.0 gettext-minimal@0.19.8.1 attr@2.4.47 libcap@2.25
acl@2.2.52 binutils-bootstrap@0 gcc-bootstrap@0 glibc-bootstrap@0
libsigsegv@2.12 lzip@1.20 ed@1.14.2 binutils@2.31.1 glibc@2.28
gcc@5.5.0 bash-minimal@4.4.23 glibc-utf8-locales@2.28 grep@3.1
coreutils@8.30 ld-wrapper@0 make@4.2.1 sed@4.5 gawk@4.2.1
findutils@4.6.0 patch@2.7.6 diffutils@3.6 file@5.33 xz@5.2.4
bzip2@1.0.6 tar@1.30 hello@2.10))
That's 84 packages, just for printing "Hello, world!". As promised, it
How do you obtain this 84 packages?
includes the boostrap seed, called =bootstrap-binaries=. It may be more
surprising to see Perl and Python in the dependency list of what is a
pure C program. The explanation is that the build process of =gcc= and
=glibc= contains Perl and Python code. Considering that both Perl and
Python are written in C and use =glibc=, this hints at why bootstrapping
is a hard problem!
** Ready to analyse yourself
As promised, here is a [[file:show-dependencies.scm][Guile
script]] that you can download and run from
the command line to do dependency analyses much like the ones I have
shown. Just give the packages whose combined list of dependencies you
want to analyze. For example:
#+begin_src sh :results output :exports both
./show-dependencies.scm hello
#+end_src
#+RESULTS:
: Packages: 1
: hello@2.10
: Package inputs: 0 packages
:
: Build inputs: 20 packages
: [source code from mirror://gnu/hello/hello-2.10.tar.gz]
bash-minimal@5.0.7 binutils@2.32 bzip2@1.0.6 coreutils@8.31
diffutils@3.7 file@5.33 findutils@4.6.0 gawk@5.0.1 gcc@7.4.0
glibc-utf8-locales@2.29 glibc@2.29 grep@3.3 gzip@1.10 ld-wrapper@0
make@4.2.1 patch@2.7.6 sed@4.7 tar@1.32 xz@5.2.4
: Package closure: 84 packages
: acl@2.2.53 attr@2.4.48 bash-minimal@5.0.7 bash-static@5.0.7
binutils-cross-boot0@2.32 binutils-mesboot0@2.20.1a
binutils-mesboot@2.20.1a binutils@2.32 bison@3.4.1
bootstrap-binaries@0 bootstrap-mes@0 bootstrap-mescc-tools@0.5.2
bzip2@1.0.6 coreutils@8.31 diffutils-boot0@3.7 diffutils-mesboot@2.7
diffutils@3.7 ed@1.15 expat@2.2.7 file-boot0@5.33 file@5.33
findutils-boot0@4.6.0 findutils@4.6.0 flex@2.6.4 gawk@5.0.1
gcc-core-mesboot@2.95.3 gcc-cross-boot0-wrapped@7.4.0
gcc-cross-boot0@7.4.0 gcc-mesboot-wrapper@4.9.4 gcc-mesboot0@2.95.3
gcc-mesboot1-wrapper@4.7.4 gcc-mesboot1@4.7.4 gcc-mesboot@4.9.4
gcc@7.4.0 gettext-boot0@0.19.8.1 gettext-minimal@0.20.1
glibc-headers-mesboot@2.16.0 glibc-intermediate@2.29
glibc-mesboot0@2.2.5 glibc-mesboot@2.16.0 glibc-utf8-locales@2.29
glibc@2.29 gmp@6.1.2 grep@3.3 guile-bootstrap@2.0 guile@2.2.6
gzip@1.10 hello@2.10 ld-wrapper-boot0@0 ld-wrapper-boot3@0
ld-wrapper@0 libatomic-ops@7.6.10 libcap@2.27 libffi@3.2.1
libgc@7.6.12 libltdl@2.4.6 libsigsegv@2.12 libstdc++-boot0@4.9.4
libstdc++@7.4.0 libunistring@0.9.10 libxml2@2.9.9
linux-libre-headers-bootstrap@0 linux-libre-headers@4.19.56 lzip@1.21
m4@1.4.18 make-boot0@4.2.1 make-mesboot0@3.80 make-mesboot@3.82
make@4.2.1 mes-boot@0.19 mesboot-headers@0.19 ncurses@6.1-20190609
patch@2.7.6 perl-boot0@5.30.0 perl@5.30.0 pkg-config@0.29.2
python-minimal@3.5.7 sed@4.7 tar@1.32 tcc-boot0@0.9.26-6.c004e9a
tcc-boot@0.9.27 texinfo@6.6 xz@5.2.4 zlib@1.2.11
You can now easily experiment yourself, even if you are not at ease with
Guile. For example, suppose you have a small Python script that plots
some data using matplotlib. What are its dependencies? First you should
check that it runs in a minimal environment:
#+begin_src sh :results output :exports both :eval no
guix environment --container --ad-hoc python python-matplotlib
-- python my-script.py
#+end_src
Next, find its dependencies:
#+begin_src sh :results output :exports both :eval no
./show-dependencies.scm python python-matplotlib
#+end_src
I won't show the output here because it is rather long - the package
closure contains 499 packages!
* OK, but... what are the /real/ dependencies?
I have explained dependencies along these lines in a few
seminars. There's one question that someone in the audience is bound to
ask: What do the results of a computation /really/ depend on? The
output of =hello= is ="Hello, world!"=, no matter which version of =gcc=
I use to compile it, and no matter which version of =python= was used in
building =glibc=. The package closure is a worst-case estimate: it
contains everything that can /potentially/ influence the results, though
most of it doesn't in practice. Unfortunately, there is no way to
identify the dependencies that matter automatically, because answering
that question in general (i.e. for arbitrary software) is equivalent to
solving the
[[https://en.wikipedia.org/wiki/Halting_problem][halting problem]].
Most package managers, such as Debian's =apt= or the multi-platform
=conda=, take a different point of view. They define the dependencies of
a program as all packages that need to be loaded into memory in order to
run it. They thus exclude the software that is required to /build/ the
program and its run-time dependencies, but can then be discarded.
Whereas Guix' definition errs on the safe side (its dependency list is
often longer than necessary but never too short), the run-time-only
definition is both too vast and too restrictive. Many run-time
dependencies don't have an impact on most programs' results, but some
build-time dependencies do.
>From my point of view, an essential point of this "worst-case estimate" is:
time travelling. Because the closure is well-defined, it is possible to
restore the complete set of the dependencies. And it is not possible with the
other point of view, if I understand correctly.
One important case where build-time dependencies matter is
floating-point computations. For historical reasons, they are surrounded
by an aura of vagueness and imprecision, which goes back to its early
days, when many details were poorly understood and implementations
varied a lot. Today, all computers used for scientific computing respect
the [[https://en.wikipedia.org/wiki/IEEE_754][IEEE 754 standard]]
that precisely defines how floating-point numbers
are represented in memory and what the result of each arithmetic
operation must be. Floating-point arithmetic is thus perfectly
deterministic and even perfectly portable between machines, if expressed
in terms of the operations defined by the standard. However, high-level
languages such as C or Fortran do not allow programmers to do that. Its
designers assume (probably correctly) that most programmers do not want
to deal with the intricate details of rounding. Therefore they provide
only a simplified interface to the arithmetic operations of IEE 754,
Missing E at IEEE.
which incidentally also provides more liberty for code optimization to
compiler writers. The net result is that the complete specification of a
program's results is its source code /plus the compiler and the
compilation options/. You thus /can/ get reproducible floating-point
results if you include all compilation steps into the perimeter of your
computation, at least for code running on a single processor. Parallel
computing is a different story: it involves voluntarily giving up
reproducibility in exchange for speed. Reproducibility then becomes a
best-effort approach of limiting the collateral damage done by
optimization through the clever design of algorithms.
It is out of scope and I have never read the IEEE 754 standard, so I do not
know if this simple propagation of errors depends on the compiler suite
and/or the machine.
#+begin_src C
#include <stdio.h>
int main() {
double x = 0.;
for (int i = 1; i < 10; i++) {
x = x + 0.1;
printf("(%d) x=%0.20f\n", i, x);
}
return 0;
}
#+end_src
And I do not know neither if the standard fixes associativity rules when no
parenthesis is provided or if it is up to the compiler.
#+begin_src C
#include <stdio.h>
int main() {
float x;
float r1, r2, r3, r4;
x = 1.0e21;
r1 = x + 1 - x + 1;
r2 = (x + 1) - (x - 1);
r3 = x + (1 - x) + 1;
r4 = x + (1 - (x - 1));
printf(" x + 1 - x + 1 =%f\n", r1);
printf("(x + 1) - (x - 1)=%f\n", r2);
printf(" x +(1 - x)+ 1 =%f\n", r3);
printf(" x +(1 - (x+ 1))=%f\n", r4);
return 0;
}
#+end_src
* Reproducing a reproducible computation
So far, I have explained the theory behind reproducible
computations. The take-home message is that to be sure to get exactly
the same results in the future, you have to use the exact same versions
of all packages in the package closure of your immediate dependencies. I
have also shown you how you can access that package closure. There is
one missing piece: how do you actually run your program in the future,
using the same environment?
The good news is that doing this is a lot simpler than understanding my
lengthy explanations (which is why I leave this for the end!). The
complex dependency graphs that I have analyzed up to here are encoded in
the Guix source code, so all you need to re-create your environment is
the exact same version of Guix! You get that version using
#+begin_src sh :results output :exports both
guix describe
#+end_src
#+RESULTS:
: Generation 15 Jan 06 2020 13:30:45 (current)
: guix 769b96b
: repository URL: https://git.savannah.gnu.org/git/guix.git
: branch: master
: commit: 769b96b62e8c09b078f73adc09fb860505920f8f
The critical information here is the unpleasantly looking string of
hexadecimal digits after "commit". This is all it takes to uniquely
identify a version of Guix. And to re-use it in the future, all you need
is Guix' time machine:
#+begin_src sh :session reproduce-C-compiler :results output :exports both
guix time-machine
--commit=769b96b62e8c09b078f73adc09fb860505920f8f -- environment
--ad-hoc gcc-toolchain
#+end_src
#+RESULTS:
:
: Updating channel 'guix' from Git repository at
'https://git.savannah.gnu.org/git/guix.git'...
#+begin_src sh :session reproduce-C-compiler :results output :exports both
gcc pi.c -o pi ./pi
#+end_src
#+RESULTS:
:
: pi = 3.1415926536
: 4 * atan(1.): 3.1415926536
: Leibniz' formula (four terms): 2.8952380952
The time machine actually downloads the specified version of Guix and
passes it the rest of the command line. You are running the same code
again. Even bugs in Guix will be reproduced faithfully!
For many practical use cases, this technique is sufficient. But there
are two variants you should know about for more complicated situations:
- If you need an environment with many packages, you should use a
manifest rather than list the packages on the command line.
See
[[https://guix.gnu.org/manual/en/html_node/Invoking-guix-environment.html][the
manual]] for details.
- If you need packages from additional channels, i.e. packages that are
not part of the official Guix distribution, you should store a
complete channel description in a file using
#+begin_src sh :results none :exports code
guix describe -f channels > guix-version-for-reproduction.txt
#+end_src
and feed that file to the time machine:
#+begin_src sh :session reproduce-C-compiler-2 :results output
:exports both
guix time-machine --channels=guix-version-for-reproduction.txt --
environment --ad-hoc gcc-toolchain
#+end_src
#+RESULTS:
:
: Updating channel 'guix' from Git repository at
'https://git.savannah.gnu.org/git/guix.git'...
#+begin_src sh :session reproduce-C-compiler-2 :results output
:exports both
gcc pi.c -o pi ./pi
#+end_src
#+RESULTS:
:
: pi = 3.1415926536
: 4 * atan(1.): 3.1415926536
: Leibniz' formula (four terms): 2.8952380952
Last, if your colleague does not use yet Guix, then let pack (plain tarball,
Docker or Singularity containers) and provide the image. For example,
#+begin_src sh :results none :exports code
guix pack \
-f docker \
-C none \
-S /bin=bin \
-S /lib=lib \
-S /share=share \
-S /etc=etc \
gcc-toolchain
#+end_src
and knowing the Guix commit (channel), you will be able in the future to
reproduce bit-to-bit this container using =guix time-machine=.
And now... congratulations for having survived to the end of this long
journey! May all your computations be reproducible, with Guix.