def run(self, data):
"""Updates a Keyword object information in Elasticsearch, based on the generator results.
:param data: list of keyword objects
:return: returns True.
"""
for key_object in data:
key_search = Keywords.search().query('match', faculty_id=key_object.faculty_id) \
.query('match' , datasource = key_object.datasource) \
.query('match', approach_id = key_object.approach_id) \
.execute()
try:
keywords = key_search[0]
except IndexError:
keywords = Keywords()
keywords.faculty_id = key_object.faculty_id
keywords.datasource = key_object.datasource
keywords.approach_id = key_object.approach_id
keywords.keywords = key_object.keywords
keywords.save()
return True
def run(self, data):
"""Performs a scraping of a faculty members ResearchId page.
:param data is a faculty object
:return: last faculty member handled
"""
faculty = data
if isinstance(faculty, str):
search_results = Faculty.search().query('match',
name=faculty).execute()
if len(search_results) > 1:
# Shouldn't happen, but could.
raise WorkflowException(
"Professor id is ambiguous during search ... More than 1 result"
)
faculty = search_results[0]
faculty_name = faculty.name
Document.search().query('match', faculty_id=faculty.faculty_id) \
.query("match", source="ResearchId") \
.delete()
Keywords.search().query('match', faculty_id=faculty.faculty_id) \
.query("match", approach_id="4") \
.delete()
print("Running researchid scrape on {}. Research id {}.".format(
faculty_name, faculty.research_id))
if faculty.research_id is not None:
scraper = ScraperFactory.create_scraper(faculty.research_id,
ScraperType.RESEARCHID)
try:
scrapps = scraper.get_scrapps()
except ScraperException:
return faculty
keywords_and_description = scrapps[0]
titles = scrapps[1:]
doc = Document()
doc.faculty_id = faculty.faculty_id
doc.source = "ResearchId"
keywords = Keywords()
keywords.faculty_id = faculty.faculty_id
keywords.datasource = "user_keywords"
keywords.approach_id = "4"
try:
doc.text = keywords_and_description.meta_data["description"]
except:
print("No description")
doc.text = ""
try:
doc.user_keywords = keywords_and_description.meta_data[
"keywords"]
keywords.keywords = keywords_and_description.meta_data[
"keywords"]
except:
print("No keywords")
doc.date = datetime.now()
doc.save()
keywords.save()
for scrapp in titles:
doc = Document()
if scrapp.data_source == ScraperType.RESEARCHID:
doc.source = "ResearchId"
else:
doc.source = "ResearchIdAbstract"
doc.faculty_id = faculty.faculty_id
if scrapp.data_source == ScraperType.RESEARCHID:
doc.text = scrapp.title
else:
doc.text = scrapp.meta_data["text"]
doc.date = datetime.now()
doc.save()
return faculty