def index(self, dataset, format='html'):
# Get the dataset into the context variable 'c'
self._get_dataset(dataset)
# If the format is either json or csv we direct the user to the search
# API instead
if format in ['json', 'csv']:
return redirect(h.url_for(controller='api/version2',
action='search',
format=format, dataset=dataset,
**request.params))
# Get the default view
handle_request(request, c, c.dataset)
# Parse the parameters using the SearchParamParser (used by the API)
parser = EntryIndexParamParser(request.params)
params, errors = parser.parse()
# We have to remove page from the parameters because that's also
# used in the Solr browser (which fetches the queries)
params.pop('page')
# We limit ourselve to only our dataset
params['filter']['dataset'] = [c.dataset.name]
facet_dimensions = {field.name: field
for field in c.dataset.dimensions
if field.facet}
params['facet_field'] = facet_dimensions.keys()
# Create a Solr browser and execute it
b = Browser(**params)
try:
b.execute()
except SolrException as e:
return {'errors': [unicode(e)]}
# Get the entries, each item is a tuple of the dataset and entry
solr_entries = b.get_entries()
entries = [entry for (dataset, entry) in solr_entries]
# Get expanded facets for this dataset,
c.facets = b.get_expanded_facets(c.dataset)
# Create a pager for the entries
c.entries = templating.Page(entries, **request.params)
# Set the search word and default to empty string
c.search = params.get('q', '')
# Set filters (but remove the dataset as we don't need it)
c.filters = params['filter']
del c.filters['dataset']
# We also make the facet dimensions and dimension names available
c.facet_dimensions = facet_dimensions
c.dimensions = [dimension.name for dimension in c.dataset.dimensions]
# Render the entries page
return templating.render('entry/index.html')
def index(self, dataset, format='html'):
# Get the dataset into the context variable 'c'
self._get_dataset(dataset)
# If the format is either json or csv we direct the user to the search
# API instead
if format in ['json', 'csv']:
return redirect(h.url_for(controller='api/version2',
action='search',
format=format, dataset=dataset,
**request.params))
# Get the default view
handle_request(request, c, c.dataset)
# Parse the parameters using the SearchParamParser (used by the API)
parser = EntryIndexParamParser(request.params)
params, errors = parser.parse()
# We have to remove page from the parameters because that's also
# used in the Solr browser (which fetches the queries)
params.pop('page')
# We limit ourselve to only our dataset
params['filter']['dataset'] = [c.dataset.name]
facet_dimensions = {field.name:field\
for field in c.dataset.dimensions \
if field.facet}
params['facet_field'] = facet_dimensions.keys()
# Create a Solr browser and execute it
b = Browser(**params)
try:
b.execute()
except SolrException, e:
return {'errors': [unicode(e)]}
def index(self, dataset, format='html'):
# Get the dataset into the context variable 'c'
self._get_dataset(dataset)
# If the format is either json or csv we direct the user to the search
# API instead
if format in ['json', 'csv']:
return redirect(
h.url_for(controller='api/version2',
action='search',
format=format,
dataset=dataset,
**request.params))
# Get the default view
handle_request(request, c, c.dataset)
# Parse the parameters using the SearchParamParser (used by the API)
parser = EntryIndexParamParser(request.params)
params, errors = parser.parse()
# We have to remove page from the parameters because that's also
# used in the Solr browser (which fetches the queries)
params.pop('page')
# We limit ourselve to only our dataset
params['filter']['dataset'] = [c.dataset.name]
facet_dimensions = {
field.name: field
for field in c.dataset.dimensions if field.facet
}
params['facet_field'] = facet_dimensions.keys()
# Create a Solr browser and execute it
b = Browser(**params)
try:
b.execute()
except SolrException as e:
return {'errors': [unicode(e)]}
# Get the entries, each item is a tuple of (dataset, entry)
solr_entries = b.get_entries()
# We are only interested in the entry in the tuple since we know
# the dataset
entries = [entry[1] for entry in solr_entries]
# Get expanded facets for this dataset,
c.facets = b.get_expanded_facets(c.dataset)
# Create a pager for the entries
c.entries = templating.Page(entries, **request.params)
# Set the search word and default to empty string
c.search = params.get('q', '')
# Set filters (but remove the dataset as we don't need it)
c.filters = params['filter']
del c.filters['dataset']
# We also make the facet dimensions and dimension names available
c.facet_dimensions = facet_dimensions
c.dimensions = [dimension.name for dimension in c.dataset.dimensions]
# Render the entries page
return templating.render('entry/index.html')