code: def get_needs_parameters(self):
          
          parameters = []
          for resource in self.minimum_needs['resources']:
              parameter = ResourceParameter()
              parameter.name = resource['Resource name']
              parameter.help_text = resource['Resource description']
              # Adding in the frequency property. This is not in the
              # FloatParameter by default, so maybe we should subclass.
              parameter.frequency = resource['Frequency']
              parameter.description = self.format_sentence(
                  resource['Readable sentence'],
                  resource)
              parameter.minimum_allowed_value = float(
                  resource['Minimum allowed'])
              parameter.maximum_allowed_value = float(
                  resource['Maximum allowed'])
              parameter.unit.name = resource['Unit']
              parameter.unit.plural = resource['Units']
              parameter.unit.abbreviation = resource['Unit abbreviation']
              parameter.value = float(resource['Default'])
              # choose highest precision between resource's parameters
              # start with default of 1
              precisions = [1]
              precision_influence = [
                  'Maximum allowed', 'Minimum allowed', 'Default']
              for element in precision_influence:
                  resource_element = str(resource[element])
                  if resource[element] is not None and '.' in resource_element:
                      precisions.append(self.precision_of(resource_element))
  
              parameter.precision = max(precisions)
              parameters.append(parameter)
  
          prov_parameter = TextParameter()
          prov_parameter.name = tr('Provenance')
          prov_parameter.description = tr('The provenance of minimum needs')
          prov_parameter.help_text = tr('The provenance of minimum needs')
          try:
              prov_parameter.value = self.provenance
          except TypeError:
              prov_parameter.value = ''
          parameters.append(prov_parameter)
  
          return parameters
docs: Get the minimum needs resources in parameter format
  
          :returns: The minimum needs resources wrapped in parameters.
          :rtype: list