Preprint.py

class Preprint:
    
	doi = ""
	identifiersLink = ""
	citationLink = ""
	preprintProvider = ""
	identifier = ""
	html_link = ""
	download_link = ""

	date_last_transitioned = ""
	date_modified = ""
	description = ""
	date_published = ""
	preprint_doi_created = ""

	# use a set instead of a list for efficiency
	# we're going to add only unique keywords and set update is faster
	keywords = set() 

	def setScalars( self, id, html_link, download_link ):

		self.identifier = id
		self.html_link = html_link
		self.download_link = download_link

	def printValues( self ):

		print( )
		print( "Preprint Service: ", self.preprintProvider )
		print( "Identifier Link: ", self.identifiersLink )
		print( "Citation Link: ", self.citationLink )
		print( "DOI: ", self.doi )
		print( "Identifier: ", self.identifier )
		print( "Download URL: ", self.download_link )
		print( "This preprint's homepage: ", self.html_link )
		print( "Date Last Transitioned: ", self.date_last_transitioned ) 
		print( "Date Modified: ", self.date_modified ) 
		print( "Abstract: ", self.description ) 
		print( "Date Published:", self.date_published ) 
		print( "Preprint DOI Created: ", self.preprint_doi_created ) 
		for keyword in self.keywords:
			print( "Keyword: ", keyword )

	def parseIdentifierData( self, idJSON ):

		if ( idJSON['attributes']['category'] == 'doi' ):
			self.doi = 'https://dx.doi.org/' + idJSON['attributes']['value']

	def parseAttrData( self, attr ):

		self.date_last_transitioned = attr['date_last_transitioned']
		self.date_modified = attr['date_modified']
		self.description = attr['description']
		self.date_published = attr['date_published']
		self.preprint_doi_created = attr['preprint_doi_created'] 
		n = len( attr['subjects'] )
		for i in range(n):
			keyword = attr['subjects'][i]
			n2 = len( keyword )
			for j in range(n2):
				# API returns the full keyword taxonomy, 
				# i.e Physical Sciences and Mathematics -> Earth Sciences -> Geology
				# We don't need to capture this each time
				# If we already have Physical Sciences and Mathematics -> Earth Sciences then just grab Geology
				if keyword[j]['text'] not in self.keywords:  # faster than `keyword not in {list}`
					self.keywords.add( keyword[j]['text'] )

  #'preprint_doi_created': '2017-12-19T15:25:34.574472', 'date_created': '2017-12-19T15:18:18.355026', 'tags': ['Geohazards', 'Norwegian Margin', 'Submarine Slide', 'Tsunami', 'Turbidites'], 'is_published': True


	def parseRelData( self, rel ):
		        
		self.identifiersLink = rel['identifiers']['links']['related']['href'] # DOI and other identifiers
		self.citationLink = rel['citation']['links']['related']['href'] # citation details
		self.preprintProvider = rel['provider']['data']['id'] # preprint server the paper came from

		# Other data that is returned, but not captured/used at the moment
		##
        #print( rel['files'] ) # list of storage providers enabled
        #print( rel['actions'] )
		#print( rel['primary_file'] ) # details about files and folders 
		#print( rel['contributors'] ) # who can make changes to the preprint
		#print( rel['license'] ) # license details