Developers’ guide

These instructions are for developing on a Unix-like platform, e.g. Linux or Mac OS X, with the bash shell. If you develop on Windows, please get in touch.

Mailing lists

General discussion of Neo development takes place in the NeuralEnsemble Google group.

Discussion of issues specific to a particular ticket in the issue tracker should take place on the tracker.

Using the issue tracker

If you find a bug in Neo, please create a new ticket on the issue tracker, setting the type to “defect”. Choose a name that is as specific as possible to the problem you’ve found, and in the description give as much information as you think is necessary to recreate the problem. The best way to do this is to create the shortest possible Python script that demonstrates the problem, and attach the file to the ticket.

If you have an idea for an improvement to Neo, create a ticket with type “enhancement”. If you already have an implementation of the idea, create a patch (see below) and attach it to the ticket.

To keep track of changes to the code and to tickets, you can register for a GitHub account and then set to watch the repository at GitHub Repository (see


  • Python 2.6, 2.7, 3.3-3.5
  • numpy >= 1.7.1
  • quantities >= 0.9.0
  • if using Python 2.6, unittest2 >= 0.5.1
  • Setuptools >= 0.7
  • nose >= 0.11.1 (for running tests)
  • Sphinx >= 0.6.4 (for building documentation)
  • (optional) tox >= 0.9 (makes it easier to test with multiple Python versions)
  • (optional) coverage >= 2.85 (for measuring test coverage)
  • (optional) scipy >= 0.12 (for MatlabIO)
  • (optional) h5py >= 2.5 (for KwikIO, NeoHdf5IO)

We strongly recommend you develop within a virtual environment (from virtualenv, venv or conda). It is best to have at least one virtual environment with Python 2.7 and one with Python 3.x.

Getting the source code

We use the Git version control system. The best way to contribute is through GitHub. You will first need a GitHub account, and you should then fork the repository at GitHub Repository (see

To get a local copy of the repository:

$ cd /some/directory
$ git clone<username>/python-neo.git

Now you need to make sure that the neo package is on your PYTHONPATH. You can do this either by installing Neo:

$ cd python-neo
$ python install
$ python3 install

(if you do this, you will have to re-run install any time you make changes to the code) or by creating symbolic links from somewhere on your PYTHONPATH, for example:

$ ln -s python-neo/neo
$ export PYTHONPATH=/some/directory:${PYTHONPATH}

An alternate solution is to install Neo with the develop option, this avoids reinstalling when there are changes in the code:

$ sudo python develop

or using the “-e” option to pip:

$ pip install -e python-neo

To update to the latest version from the repository:

$ git pull

Running the test suite

Before you make any changes, run the test suite to make sure all the tests pass on your system:

$ cd neo/test

With Python 2.7 or 3.3:

$ python -m unittest discover
$ python3 -m unittest discover

If you have nose installed:

$ nosetests

At the end, if you see “OK”, then all the tests passed (or were skipped because certain dependencies are not installed), otherwise it will report on tests that failed or produced errors.

To run tests from an individual file:

$ python
$ python3

Writing tests

You should try to write automated tests for any new code that you add. If you have found a bug and want to fix it, first write a test that isolates the bug (and that therefore fails with the existing codebase). Then apply your fix and check that the test now passes.

To see how well the tests cover the code base, run:

$ nosetests --with-coverage --cover-package=neo --cover-erase

Working on the documentation

All modules, classes, functions, and methods (including private and subclassed builtin methods) should have docstrings. Please see PEP257 for a description of docstring conventions.

Module docstrings should explain briefly what functions or classes are present. Detailed descriptions can be left for the docstrings of the respective functions or classes. Private functions do not need to be explained here.

Class docstrings should include an explanation of the purpose of the class and, when applicable, how it relates to standard neuroscientific data. They should also include at least one example, which should be written so it can be run as-is from a clean newly-started Python interactive session (that means all imports should be included). Finally, they should include a list of all arguments, attributes, and properties, with explanations. Properties that return data calculated from other data should explain what calculation is done. A list of methods is not needed, since documentation will be generated from the method docstrings.

Method and function docstrings should include an explanation for what the method or function does. If this may not be clear, one or more examples may be included. Examples that are only a few lines do not need to include imports or setup, but more complicated examples should have them.

Examples can be tested easily using the iPython %doctest_mode magic. This will strip >>> and ... from the beginning of each line of the example, so the example can be copied and pasted as-is.

The documentation is written in reStructuredText, using the Sphinx documentation system. Any mention of another Neo module, class, attribute, method, or function should be properly marked up so automatic links can be generated. The same goes for quantities or numpy.

To build the documentation:

$ cd python-neo/doc
$ make html

Then open some/directory/python-neo/doc/build/html/index.html in your browser.

Committing your changes

Once you are happy with your changes, run the test suite again to check that you have not introduced any new bugs. It is also recommended to check your code with a code checking program, such as pyflakes or flake8. Then you can commit them to your local repository:

$ git commit -m 'informative commit message'

If this is your first commit to the project, please add your name and affiliation/employer to doc/source/authors.rst

You can then push your changes to your online repository on GitHub:

$ git push

Once you think your changes are ready to be included in the main Neo repository, open a pull request on GitHub (see

Python 3

Neo core should work with both recent versions of Python 2 (versions 2.6 and 2.7) and Python 3 (version 3.3 or newer). Neo IO modules should ideally work with both Python 2 and 3, but certain modules may only work with one or the other (see Installation).

So far, we have managed to write code that works with both Python 2 and 3. Mainly this involves avoiding the print statement (use instead), and putting from __future__ import division at the beginning of any file that uses division.

If in doubt, Porting to Python 3 by Lennart Regebro is an excellent resource.

The most important thing to remember is to run tests with at least one version of Python 2 and at least one version of Python 3. There is generally no problem in having multiple versions of Python installed on your computer at once: e.g., on Ubuntu Python 2 is available as python and Python 3 as python3, while on Arch Linux Python 2 is python2 and Python 3 python. See PEP394 for more on this. Using virtual environments makes this very straightforward.

Coding standards and style

All code should conform as much as possible to PEP 8, and should run with Python 2.6, 2.7, and 3.3 or newer.

You can use the pep8 program to check the code for PEP 8 conformity. You can also use flake8, which combines pep8 and pyflakes.

However, the pep8 and flake8 programs do not check for all PEP 8 issues. In particular, they do not check that the import statements are in the correct order.

Also, please do not use from xyz import *. This is slow, can lead to conflicts, and makes it difficult for code analysis software.

Making a release

Add a section in /doc/source/whatisnew.rst for the release.

First check that the version string (in neo/,, doc/ and doc/install.rst) is correct.

To build a source package:

$ python sdist

To upload the package to PyPI (currently Samuel Garcia and Andrew Davison have the necessary permissions to do this):

$ python sdist upload
$ python upload_docs --upload-dir=doc/build/html

Finally, tag the release in the Git repository and push it:

$ git tag <version>
$ git push --tags origin

If you want to develop your own IO module

See IO developers’ guide for implementation of a new IO.