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Python Bindings for Neuroshare
C Python
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Python Bindings for Neuroshare

The Neuroshare API is a standardized interface to access
electrophysiology data stored in various different file
formats. To do so, it uses format- specific shared libraries.
Refer to the official website
for more information.

The aim of this library is to provide a high level interface
to the Neuroshare API, i.e. it focuses on API usability more
then being a mere python version of the C API. Thus none of
the original Neuroshare API calls are directly exposed but
the interface is through python objects that resemble (more
or less) the Neuroshare Entities.


The compile-time requirements for python-neuroshare are the
'setuptools' and the Python development files and a working
C compiler (clang or gcc) and NumPy. For Debian based
distributions, e.g. Ubuntu, this can easily be done with:

	$ sudo apt-get install clang python-setuptools \
                               python-dev python-numpy

After that, python-neuroshare is installed with the following

	$ sudo python install

Additional runtime dependencies:
	* The Neuroshare vendor DLLs for the specific data file(s)!
	  Please refer to the following section for more information.

Installation of vendor DLLs
- - - - - - - - - - - - - -

Python-neuroshare relies on the vendor specific DLLs to
access data failes. Therefore the specific DLLs for each
type of file must be downloaded and installed into one of
the following locations:

A (possibly incomplete) list of the vendor specific DLLs
can be obtained be obtained from the neuroshare website:

Please note that you need the corresponding DLLs for your
platform (e.g. Linux, 64-bit). If you find yourself in the
situation that there is no DLL for your specific platform
and you are either on a UNIX-like system you can use G-Node's
very one nswineproxy component to use the Windows 32 bit
DLLs. Please refer to the nswineproxy homepage for more


   Opening a file:

	>> import neuroshare as ns
	>> fd = ns.File ("")

   Iterate over the entities in the file:

   	>> for entity in fd.list_entities():
        >>    print entity.label, entity.entity_type
	>>    ... do something else with entity ...

Reporting Bugs & Submitting Patches
Any bugs can and should be filed to the project's issue
tracker at github:
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