Freely available tools for computational molecular biology.
Biopython README file
The Biopython Project is an international association of developers of freely available Python tools for computational molecular biology.
Our user-centric documentation is hosted on http://biopython.org including the main Biopython Tutorial and Cookbook:
This README file is intended primarily for people interested in working with the Biopython source code, either one of the releases from the http://biopython.org website, or from our repository on GitHub https://github.com/biopython/biopython
This Biopython package is open source software made available under generous terms. Please see the LICENSE file for further details.
If you use Biopython in work contributing to a scientific publication, we ask that you cite our application note (below) or one of the module specific publications (listed on our website):
Cock, P.J.A. et al. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics 2009 Jun 1; 25(11) 1422-3 http://dx.doi.org/10.1093/bioinformatics/btp163 pmid:19304878
For the impatient
To build and install Biopython, download and unzip the source code, go to this directory at the command line, and type:
python setup.py build python setup.py test sudo python setup.py install
Windows users are instead recommended to use the installation packages provided on our website, http://biopython.org
We currently recommend using Python 2.7 from http://www.python.org which is the final version of Python 2. Early adopters are encouraged to try Biopython under Python 3.3 as well.
Biopython is currently supported and tested on the following Python verions:
Python 2.6, 2.7, 3.3 – see http://www.python.org
This is the currently the primary development platform for Biopython.
PyPy 1.9, 2.0, 2.1 – see http://www.pypy.org
Aside from modules with C code or dependent of NumPy, everything should work. PyPy’s NumPy reimplementation NumPyPy is still in progress.
Jython 2.7 – see http://www.jython.org
Aside from modules with C code, or dependent on SQLite3 or NumPy, everything should work.
Please note that Biopython 1.62 was our final release to support Python 2.5 and Jython 2.5.
Depending on which parts of Biopython you plan to use, there are a number of other optional Python dependencies - which can in general be installed after Biopython.
NumPy, see http://numpy.scipy.org (optional, but strongly recommended) This package is only used in the computationally-oriented modules. It is required for Bio.Cluster, Bio.PDB and a few other modules. If you think you might need these modules, then please install NumPy first BEFORE installing Biopython. The older Numeric library is no longer supported in Biopython.
ReportLab, see http://www.reportlab.com/software/opensource/ (optional) This package is only used in Bio.Graphics, so if you do not need this functionality, you will not need to install this package. You can install it later if needed.
matplotlib, see http://matplotlib.org/ (optional) Bio.Phylo uses this package to plot phylogenetic trees. As with ReportLab, you can install this at any time to enable the plotting functionality.
networkx, see http://networkx.lanl.gov/ (optional) and pygraphviz or pydot, see http://networkx.lanl.gov/pygraphviz/ and http://code.google.com/p/pydot/ (optional) These packages are used for certain niche functions in Bio.Phylo. Again, they are only needed to enable these functions and can be installed later if needed.
rdflib, see https://github.com/RDFLib/rdflib (optional) This package is used in the CDAO parser under Bio.Phylo, and can be installed as needed.
MySQLdb, see http://sourceforge.net/projects/mysql-python (optional) This package is used by BioSQL to access a MySQL database.
Note that some of these libraries are not available for Jython or PyPy.
In addition there are a number of useful third party tools you may wish to install such as standalone NCBI BLAST, EMBOSS or ClustalW.
First, make sure that Python is installed correctly. Second, we recommend you install NumPy (see above). Then install Biopython.
Windows users should use the appropriate provided installation package from our website (each is specific to a different Python version).
Installation from source should be as simple as going to the Biopython source code directory, and typing:
python setup.py build python setup.py test sudo python setup.py install
Substitute python with your specific version, for example python3, jython or pypy.
If you need to do additional configuration, e.g. changing the base directory, please type python setup.py, or see the documentation here:
Biopython includes a suite of regression tests to check if everything is running correctly. To run the tests, go to the biopython source code directory and type:
python setup.py test
Do not panic if you see messages warning of skipped tests:
test_DocSQL ... skipping. Install MySQLdb if you want to use Bio.DocSQL.
This most likely means that a package is not installed. You can ignore this if it occurs in the tests for a module that you were not planning on using. If you did want to use that module, please install the required dependency and re-run the tests.
There is more testing information in the Biopython Tutorial & Cookbook.
Biopython 1.61 introduced a new warning, Bio.BiopythonExperimentalWarning, which is used to mark any experimental code included in the otherwise stable Biopython releases. Such ‘beta’ level code is ready for wider testing, but still likely to change, and should only be tried by early adopters in order to give feedback via the biopython-dev mailing list.
We’d expect such experimental code to reach stable status within one or two releases, at which point our normal policies about trying to preserve backwards compatibility would apply.
While we try to ship a robust package, bugs inevitably pop up. If you are having problems that might be caused by a bug in Biopython, it is possible that it has already been identified. Update to the latest release if you are not using it already, and retry. If the problem persists, please search our bug database and our mailing lists to see if it has already been reported (and hopefully fixed), and if not please do report the bug. We can’t fix problems we don’t know about ;)
Old issue tracker: https://redmine.open-bio.org/projects/biopython
Current issue tracker: https://github.com/biopython/biopython/issues
If you suspect the problem lies within a parser, it is likely that the data format has changed and broken the parsing code. (The text BLAST and GenBank formats seem to be particularly fragile.) Thus, the parsing code in Biopython is sometimes updated faster than we can build Biopython releases. You can get the most recent parser by pulling the relevant files (e.g. the ones in Bio.SeqIO or Bio.Blast) from our git repository. However, be careful when doing this, because the code in github is not as well-tested as released code, and may contain new dependencies.
Finally, you can send a bug report to the bug database or the mailing list at firstname.lastname@example.org. In the bug report, please let us know:
Which operating system and hardware (32 bit or 64 bit) you are using
Biopython version (or git commit/date)
Traceback that occurs (the full error message)
And also ideally:
Example code that breaks
A data file that causes the problem
Contributing, Bug Reports
Biopython is run by volunteers from all over the world, with many types of backgrounds. We are always looking for people interested in helping with code development, web-site management, documentation writing, technical administration, and whatever else comes up.
README – This file.
NEWS – Release notes and news.
LICENSE – What you can do with the code.
CONTRIB – An (incomplete) list of people who helped Biopython in one way or another.
DEPRECATED – Contains information about modules in Biopython that are removed or no longer recommended for use, and how to update code that uses those modules.
MANIFEST.in – Tells distutils what files to distribute.
setup.py – Installation file.
Bio/ – The main code base code.
BioSQL/ – Code for using Biopython with BioSQL databases.
Doc/ – Documentation.
Scripts/ – Miscellaneous, possibly useful, standalone scripts.
Tests/ – Regression testing code including sample data files.
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