def linksets(self, id=None):
#load controller for processing datasets by tag, group, organization, random number of datasets and all datasets
pan = PANController()
tempDatasets = toolkit.get_action('package_list')(
data_dict={})
pan_rezultati = pan.process_datasets(tempDatasets)
#get datasets with relations
dR = pan_rezultati['dR']
c.linksets = dR
tagURL = helpers.url_for(controller="package", action='read',qualified=True)
tagURL = tagURL.rstrip('packages') + 'dataset'
c.tagURL = tagURL
if (id == 'rdf'):
response.headers['Content-Type'] = 'application/rdf+xml; charset=utf-8'
return render('linksets/linksets.rdf')
elif(id == 'nt'):
response.headers['Content-Type'] = 'text/n3; charset=utf-8'
return render('linksets/linksets.nt')
else:
response.headers['Content-Type'] = 'text/n3; charset=utf-8'
return render('linksets/linksets.n3')
def linksets(self, id=None):
#load controller for processing datasets by tag, group, organization, random number of datasets and all datasets
pan = PANController()
tempDatasets = toolkit.get_action('package_list')(data_dict={})
pan_rezultati = pan.process_datasets(tempDatasets)
#get datasets with relations
dR = pan_rezultati['dR']
c.linksets = dR
tagURL = helpers.url_for(controller="package",
action='read',
qualified=True)
tagURL = tagURL.rstrip('packages') + 'dataset'
c.tagURL = tagURL
if (id == 'rdf'):
response.headers[
'Content-Type'] = 'application/rdf+xml; charset=utf-8'
return render('linksets/linksets.rdf')
elif (id == 'nt'):
response.headers['Content-Type'] = 'text/n3; charset=utf-8'
return render('linksets/linksets.nt')
else:
response.headers['Content-Type'] = 'text/n3; charset=utf-8'
return render('linksets/linksets.n3')
def machineProcessable(self, subjectInfo, objectInfo):
#creating a list of machine processable formats
formats = [
'rdf', 'ttl', 'rdfa', 'rdf+xml', 'n3', 'n-triples', 'nq', 'sparql',
'csv', 'json', 'tsv', 'xml', 'open xml'
]
mp = ''
#examine whether object dataset have at least one machine processable format
formatsSO = 0
formatsOS = 0
sDF = []
oDF = []
pan = PANController()
#get data formats in subject and object dataset
sDF = pan._get_formats(subjectInfo['name'])
oDF = pan._get_formats(objectInfo['name'])
#examine whether subject dataset have at least one machine processable format
for keyS, valueS in enumerate(sDF):
for keyF, valueF in enumerate(formats):
if (valueS.lower() == valueF):
formatsSO += 1
#examine whether object dataset have at least one machine processable format
for keyO, valueO in enumerate(oDF):
for keyF, valueF in enumerate(formats):
if (valueO.lower() == valueF):
formatsOS += 1
#compare results
if all(x > 0 for x in (formatsSO, formatsOS)):
mp = 'true'
else:
mp = 'false'
return mp
def machineProcessable(self, subjectInfo, objectInfo):
#creating a list of machine processable formats
formats = ['rdf','ttl','rdfa','rdf+xml','n3','n-triples','nq','sparql','csv','json','tsv','xml','open xml']
mp = ''
#examine whether object dataset have at least one machine processable format
formatsSO = 0
formatsOS = 0
sDF = []
oDF = []
pan = PANController()
#get data formats in subject and object dataset
sDF = pan._get_formats(subjectInfo['name'])
oDF = pan._get_formats(objectInfo['name'])
#examine whether subject dataset have at least one machine processable format
for keyS, valueS in enumerate(sDF):
for keyF, valueF in enumerate(formats):
if (valueS.lower() == valueF):
formatsSO += 1
#examine whether object dataset have at least one machine processable format
for keyO, valueO in enumerate(oDF):
for keyF, valueF in enumerate(formats):
if (valueO.lower() == valueF):
formatsOS += 1
#compare results
if all(x > 0 for x in (formatsSO, formatsOS)):
mp = 'true'
else:
mp = 'false'
return mp
def linkedFormat(self, subjectInfo, objectInfo):
#creating a list of linked data formats
formats = [
'rdf', 'rdfa', 'ttl', 'n3', 'nq', 'rdf+xml', 'turtle', 'n-triples'
]
lF = ''
formatsSO = 0
formatsOS = 0
sDF = []
oDF = []
pan = PANController()
#get data formats in subject and object dataset
sDF = pan._get_formats(subjectInfo['name'])
oDF = pan._get_formats(objectInfo['name'])
#examine whether subject dataset have at least one linked data format
for keyS, valueS in enumerate(sDF):
for keyF, valueF in enumerate(formats):
if (valueS.lower() == valueF):
formatsSO += 1
#examine whether object dataset have at least one linked data format
for keyO, valueO in enumerate(oDF):
for keyF, valueF in enumerate(formats):
if (valueO.lower() == valueF):
formatsOS += 1
#compare results
if all(x > 0 for x in (formatsSO, formatsOS)):
lF = 'true'
else:
lF = 'false'
return lF
def linkedFormat(self, subjectInfo, objectInfo):
#creating a list of linked data formats
formats = ['rdf', 'rdfa', 'ttl', 'n3', 'nq' ,'rdf+xml', 'turtle', 'n-triples']
lF = ''
formatsSO = 0
formatsOS = 0
sDF = []
oDF = []
pan = PANController()
#get data formats in subject and object dataset
sDF = pan._get_formats(subjectInfo['name'])
oDF = pan._get_formats(objectInfo['name'])
#examine whether subject dataset have at least one linked data format
for keyS, valueS in enumerate(sDF):
for keyF, valueF in enumerate(formats):
if (valueS.lower() == valueF):
formatsSO += 1
#examine whether object dataset have at least one linked data format
for keyO, valueO in enumerate(oDF):
for keyF, valueF in enumerate(formats):
if (valueO.lower() == valueF):
formatsOS += 1
#compare results
if all(x > 0 for x in (formatsSO, formatsOS)):
lF = 'true'
else:
lF = 'false'
return lF
def compareFormats(self, subjectInfo, objectInfo):
formatsSO = 0
formatsOS = 0
sDF = []
oDF = []
pan = PANController()
#get data formats in subject and object dataset
sDF = pan._get_formats(subjectInfo['name'])
oDF = pan._get_formats(objectInfo['name'])
#examine number of similar formats from subject dataset in object dataset
for keyS, valueS in enumerate(sDF):
for keyO, valueO in enumerate(oDF):
if (valueS == valueO):
formatsSO += 1
#examine number of similar formats from object dataset in subject dataset
for keyO, valueO in enumerate(oDF):
for keyS, valueS in enumerate(sDF):
if (valueO == valueS):
formatsOS += 1
#calculating mean value for both cases
formatsSO = formatsSO / len(oDF)
formatsSO = int(round(formatsSO, 2) * 100)
formatsOS = formatsOS / len(sDF)
formatsOS = int(round(formatsOS, 2) * 100)
results = [formatsSO, formatsOS]
return results
def compareFormats(self, subjectInfo, objectInfo):
formatsSO = 0
formatsOS = 0
sDF = []
oDF = []
pan = PANController()
#get data formats in subject and object dataset
sDF = pan._get_formats(subjectInfo['name'])
oDF = pan._get_formats(objectInfo['name'])
#examine number of similar formats from subject dataset in object dataset
for keyS, valueS in enumerate(sDF):
for keyO, valueO in enumerate(oDF):
if (valueS == valueO):
formatsSO += 1
#examine number of similar formats from object dataset in subject dataset
for keyO, valueO in enumerate(oDF):
for keyS, valueS in enumerate(sDF):
if (valueO == valueS):
formatsOS += 1
#calculating mean value for both cases
formatsSO = formatsSO / len(oDF)
formatsSO = int(round(formatsSO, 2) * 100)
formatsOS = formatsOS / len(sDF)
formatsOS = int(round(formatsOS, 2) * 100)
results = [formatsSO, formatsOS]
return results
def manager(self):
#load controller for processing datasets by tag, group, organization, random number of datasets and all datasets
pan = PANController()
#load controller for preparing datasets for visual display
relin = RELINController()
#load controller for using functions to process datasets
func = FUNCTIONSController()
#create temporary list for storing results of processing of datasets
tempDatasets = []
#IF conditions for storing HTML fields values sent by HTTP from index page
if ('form[random]' not in request.params):
randomNum = 0
elif request.params['form[random]'] == '':
randomNum = 0
else:
randomNum = int(request.params['form[random]'])
if ('form[tag]' not in request.params):
tag = ''
else:
tag = request.params['form[tag]']
if ('form[group]' not in request.params):
group = ''
else:
group = request.params['form[group]']
if ('form[organization]' not in request.params):
organization = ''
else:
organization = request.params['form[organization]']
#examining which field on start HTML user choosed and processing datasets by that condition
if (randomNum > 0):
tempDatasets = toolkit.get_action('package_list')(
data_dict={})
datasets = random.sample( tempDatasets, randomNum )
pan_rezultati = pan.process_datasets(datasets)
elif (tag != ''):
tempTags = toolkit.get_action('tag_show')(
data_dict={'id': tag})
for tempList in tempTags['packages']:
for tempKey,tempValue in tempList.items():
if 'name' in tempKey:
tempDatasets.append(tempValue)
pan_rezultati = pan.process_datasets(tempDatasets)
elif (group != ''):
tempGroup = toolkit.get_action('group_show')(
data_dict={'id': group})
for tempList in tempGroup['packages']:
for tempKey,tempValue in tempList.items():
if 'name' in tempKey:
tempDatasets.append(tempValue)
pan_rezultati = pan.process_datasets(tempDatasets)
elif (organization != ''):
tempOrganization = toolkit.get_action('organization_show')(
data_dict={'id': organization})
for tempList in tempOrganization['packages']:
for tempKey,tempValue in tempList.items():
if 'name' in tempKey:
tempDatasets.append(tempValue)
pan_rezultati = pan.process_datasets(tempDatasets)
else:
tempDatasets = toolkit.get_action('package_list')(
data_dict={})
pan_rezultati = pan.process_datasets(tempDatasets)
#get names of datasets who have relations
relationships = pan_rezultati['relationships']
#get datasets with relations
dR = pan_rezultati['dR']
#get data about datasets that will be displayed
datasets = pan_rezultati['datasets']
#get all relations for each dataset
eKey = relin.oneToAllRelationships(relationships,datasets)
#filter commutative relations
eKey = relin.removeCommutative(eKey)
#get all datasets from portal
datasetsPortal = toolkit.get_action('package_list')(
data_dict={})
#replace datasets name with their keys from datasetsPortal dict because jQuery library uses object with names e10, e2, e3 to draw relations
for k,v in enumerate(eKey):
if (eKey[k]['subject'] in datasetsPortal):
eKey[k]['type'] = func.getType(eKey[k]['subject'],eKey[k]['object'],dR)
eKey[k]['subject'] = func.getKey(eKey[k]['subject'],datasets)
eKey[k]['object'] = func.getKey(eKey[k]['object'],datasets)
else:
del eKey[k]
#specify formats that describe linked data
LDF = ['rdf','rdfa','sparql','n-triples','turtle','n3','nq']
#preparing data for using in HTML template
c.eKey = eKey
c.datasets = datasets
c.ldf = LDF
tagURL = helpers.url_for(controller="package", action='read',qualified=True)
c.tagURL = tagURL.rstrip('packages') + 'dataset'
c.relin_info_test = ''
#specifying HTML template to render
return p.toolkit.render('lire/manager.html')
def manager(self):
#load controller for processing datasets by tag, group, organization, random number of datasets and all datasets
pan = PANController()
#load controller for preparing datasets for visual display
relin = RELINController()
#load controller for using functions to process datasets
func = FUNCTIONSController()
#create temporary list for storing results of processing of datasets
tempDatasets = []
#IF conditions for storing HTML fields values sent by HTTP from index page
if ('form[random]' not in request.params):
randomNum = 0
elif request.params['form[random]'] == '':
randomNum = 0
else:
randomNum = int(request.params['form[random]'])
if ('form[tag]' not in request.params):
tag = ''
else:
tag = request.params['form[tag]']
if ('form[group]' not in request.params):
group = ''
else:
group = request.params['form[group]']
if ('form[organization]' not in request.params):
organization = ''
else:
organization = request.params['form[organization]']
#examining which field on start HTML user choosed and processing datasets by that condition
if (randomNum > 0):
tempDatasets = toolkit.get_action('package_list')(
data_dict={})
datasets = random.sample( tempDatasets, randomNum )
pan_rezultati = pan.process_datasets(datasets)
elif (tag != ''):
tempTags = toolkit.get_action('tag_show')(
data_dict={'id': tag})
for tempList in tempTags['packages']:
for tempKey,tempValue in tempList.items():
if 'name' in tempKey:
tempDatasets.append(tempValue)
pan_rezultati = pan.process_datasets(tempDatasets)
elif (group != ''):
tempGroup = toolkit.get_action('group_show')(
data_dict={'id': group})
for tempList in tempGroup['packages']:
for tempKey,tempValue in tempList.items():
if 'name' in tempKey:
tempDatasets.append(tempValue)
pan_rezultati = pan.process_datasets(tempDatasets)
elif (organization != ''):
tempOrganization = toolkit.get_action('organization_show')(
data_dict={'id': organization})
for tempList in tempOrganization['packages']:
for tempKey,tempValue in tempList.items():
if 'name' in tempKey:
tempDatasets.append(tempValue)
pan_rezultati = pan.process_datasets(tempDatasets)
else:
tempDatasets = toolkit.get_action('package_list')(
data_dict={})
pan_rezultati = pan.process_datasets(tempDatasets)
#get names of datasets who have relations
relationships = pan_rezultati['relationships']
#get datasets with relations
dR = pan_rezultati['dR']
#get data about datasets that will be displayed
datasets = pan_rezultati['datasets']
#get all relations for each dataset
eKey = relin.oneToAllRelationships(relationships,datasets)
#filter commutative relations
eKey = relin.removeCommutative(eKey)
#get all datasets from portal
datasetsPortal = toolkit.get_action('package_list')(
data_dict={})
#replace datasets name with their keys from datasetsPortal dict because jQuery library uses object with names e10, e2, e3 to draw relations
for k,v in enumerate(eKey):
if (eKey[k]['subject'] in datasetsPortal):
eKey[k]['type'] = func.getType(eKey[k]['subject'],eKey[k]['object'],dR)
eKey[k]['subject'] = func.getKey(eKey[k]['subject'],datasets)
eKey[k]['object'] = func.getKey(eKey[k]['object'],datasets)
else:
del eKey[k]
#specify formats that describe linked data
LDF = ['rdf','rdfa','sparql','n-triples','turtle','n3','nq', 'nt']
#preparing data for using in HTML template
c.eKey = eKey
c.datasets = datasets
c.ldf = LDF
tagURL = helpers.url_for(controller="package", action='read',qualified=True)
c.tagURL = tagURL.rstrip('packages') + 'dataset'
c.relin_info_test = ''
#specifying HTML template to render
return p.toolkit.render('lire/manager.html')
