Notes for Contributers¶
If you intend to contribute to the development of HTSeq, these notes will help you to get started.
Source code¶
The source code is on an Subversion repository, hosted on SourceForge.
To check out the repository, use
svn co https://htseq.svn.sourceforge.net/svnroot/htseq/trunk htseq
To browse the repository, see here.
Languages¶
A good part of HTSeq is actually not written in Python but in
Cython. In case you don’t know it yet: Cython, a fork from Pyrex, is a
kind of Python compiler. You annotate Python code with additional type
informations (the lines starting with cdef
in the source code). Cython
will then transform the Cython source file (with extension pyx
) into
a C file, which calls the appropriate funnctions of Python’s C API. Without
type annotation, this looks and feels the same as normal Python and is not
really faster, either. With type annotation, significant performance gains
are possible, especially in inner loops.
A small part, namely the StepVector class, is written in C++ and exported with SWIG. (SWIG, the “Simple Wrapper and Interface Generator” is a very useful tool to generate C/C++ code to wrap an existing C/C++ library such that it becomes accessible as a native library within a number of scripting languages.) I am not so happy with this any more (the abstraction panelty of the object-oriented SWIG wrapping turned out to be a bit high) and ultimatively want to rewrite this part.
Build process¶
I do not want to burden the user with having to install SWIG or Cython. Both these tools work by generating C/C++ code which then can be compiled without the need of any files from SWIG or Cython. Hence, I’ve divided the build process into two steps:
- Step 1: Generate the C/C++ files from the SWIG and Cython source files.
This is done by the calling
make
in thesrc
directory. Note that theMakefile
there contains only calls tocython
andswig
but not to the C compiler. (Note: I am using Cython 0.11. Compiling with Cython 0.12 does not work at the moment, but I will update at some point.) - Step 2: The C files are compiled and copied together with the Python source
files into a
build
directory. This is done by callingpython setup.py build
in the root directory. It creates (as usual for a setup.py script) a new directorybuild
and in it a subdirectory for the machine architecture, which then contains the package directory.
To test during development, set the PYTHONPATH
to point to the maschine-specific
directory in the build
directory, so that Python can find the HTSeq
directory
that setup.py build
puts there. Whenever you make a change, call the shell
script build_it
, which contains just two lines: the first calls make
in src
,
the second calls setup.py build
.
Distributing¶
To wrap up a package, call build_it
(or at least make
in src
)
and then setup.py sdist
. This makes a directory dists
and in there,
a tarball with all the source files (Python and C/C++) and all kinds of other stuff
(unfortunately including the example_files
directory, that I hence always delete manually
before running setup.py sdist
to keep the package lean). The tarball contains, when unpacked
the setup.py
script, which allows installing with setup.py install
.
I am using setuptools (and not distutils) so that I can make Python eggs with
setup.py bdist_egg
. For Windows binaries, I use setup.py bdist_wininst --compiler=mingw32
on my virtual Windows box.
Files¶
The package contains the following source files:
HTSeq/__init__.py
:- The outer face of HTSeq. This file defines the name space of HTSeq and contains
the definition of all classes without performance-critical methods. The file
imports
_HTSeq
in its own namespace, so that, for the user, it does not matter whether an object is defined here or in_HTSeq.pyx
. src/HTSeq/_HTSeq.pyx
:- The core of HTSeq. All classes with perfomance-critical methods are defined here. For most of it, this file looks as a normal Python file. Only where performance is critical, type annotation has been added. See the Cython manual for details.
src/HTSeq/_HTSeq.pxd
:- The “header file” for
_HTSeq.pyx
. It contains the type annotation for all the fields of the classes defined in_HTSeq.pyx
. If a user would want to write her own Cython code, she could use Cython’scimport
directive to import this header file and so make Cython aware of the typed definitions of fields and methods in_HTSeq.pyx
, which may improve performance because it allows Cython to kick out all unnecessary type checking. HTSeq/_HTSeq_internal.py
:- There are a few limitation to the standard Python code allowed in Cython files;
most importantly, the
yield
statement is not yet supported. Hence,_HTSeq.pyx
imports this file, and whenever a method in_HTSeq.pyx
needs ayield
, it calls a function which is put in here. src/step_vector.h
:- The C++
step_vector
class template. As this is a pure template, there is nostep_vector.cc
file with definitions. If you want to use astep_vector
in a C++ project, this is all you need. src/StepVector.i
:- An input file to SWIG, which produces the Python wrapper around
step_vector.h
, i.e., theStepVector
module containing theStepVector
class. Note that this file contains not only SWIG directives but also Python and come C++ code. src/AutoPyObjPtr.i
:- A very small SWIG library that allows SWIG-wrapped C++ container classes to store Python objects in a way that Python’s garbage collector is happy with.
HTSeq/scripts/count.py
andHTSeq/scripts/qa.py
:- The source code for the stand-alone scripts
htseq-count
andhtseq-qa
. They reside in the sub-packageHTSeq.scripts
, allowing to call the scripts with, e.g.,python -m HTSeq.scripts.qa
. scripts/htseq-count
andscripts/htseq-qa
:- Short stubs to call the scripts from the command line simply as, e.g.,
htseq-qa
.
Furthermore, there are these files to support development:
src/Makefile
:- Generates C/C++ files from SWIG and Cython source files but does no C/C++ compiling.
setup.py
:- A typical setuptools setup.py file.
build_it
:- A three-line shell script that
* generates a file
HTSeq/_version.py
from the fileVERSION
. * callsmake
insrc
to processsrc/Makefile
* runssetup.py build
(see above) clean
:- Another two-line shell script to first call
make clean
insrc
and then delete whateversetup.py
may have written. test.py
- Performs all the deoctests in the documentation, using the example data in the
example_data
directory.
Finally, there are these files
VERSION
:- a one-line text-fil with the version number. It is read by
setup.py
, used bybuild_it
to generate the one-line Python fileHTSeq/_version.py
and also used when building the documentation. MANIFEST.in
:- Brings some files to the attention of
setup.py sdist
which would otherwise not be included LICENCE
:- The GPL, v3
README
:- Points the user to the web site.
and these directories
doc/
:- this documentation, in Sphinx reStructuredText format, and a Makefile to drive Sphinx.
example_files/
:- a few example files to be use by the doctests in the documentation.