from pynwb import validate, NWBHDF5IO

def get_chached_namespaces_to_validate(path):
   """
   Determine the most specific namespace(s) (i.e., extensions) that are chached in the given
   NWB file that should be used for validation.

   :param path: Path for the NWB file
   :return: Tuple with:
     - List of strings with the most specific namespace(s) to use for validation.
     - BuildManager object for opening the file for validation
     - Dict with the full result from NWBHDF5IO.load_namespaces
   """
   # Importing locally here so we can easily switch to using pynwb.validate.get_chached_namespaces_to_validate
   # once it is part of the release
   from hdmf.spec import NamespaceCatalog
   from hdmf.build import BuildManager
   from pynwb.spec import NWBDatasetSpec, NWBGroupSpec, NWBNamespace
   from hdmf.build import TypeMap as TypeMap

   catalog = NamespaceCatalog(NWBGroupSpec, NWBDatasetSpec, NWBNamespace)
   ns_deps = NWBHDF5IO.load_namespaces(catalog, path)
   s = set(ns_deps.keys())  # determine which namespaces are the most
   for k in ns_deps:  # specific (i.e. extensions) and validate
      s -= ns_deps[k].keys()  # against those
   # TODO remove this workaround for issue https://github.com/NeurodataWithoutBorders/pynwb/issues/1357
   if 'hdmf-experimental' in s:
      s.remove('hdmf-experimental')  # remove validation of hdmf-experimental for now
   namespaces = list(sorted(s))

   if len(namespaces) > 0:
      tm = TypeMap(catalog)
      manager = BuildManager(tm)
   else:
      manager = None

   return namespaces, manager, ns_deps


if __name__ == '__main__':
   path = "001_140709EXP_A1.nwb"
   validate_namespaces, manager, chached_namespaces = get_chached_namespaces_to_validate(path)
   with NWBHDF5IO(path, "r", manager=manager) as reader:
      errors = []
      for ns in validate_namespaces:
         errors += validate(io=reader, namespace=ns)
      print("%i errors found" % len(errors))