def identify_bio_pages(self, firm):
fts = FirmTrainingSet.get_for_firm(firm)
spider = Spider(firm.domain, os.path.join(self.scrape_dir, str(fts.id) + ".db"), workers=4, retry_attempts=2)
self.stdout.write("Identifying bio pages...\n")
model = PageClassifier(os.path.join(self.model_dir, str(fts.id) + "_page.tgm"))
model.load()
self.stdout.write('Retrieving page features...\n')
bio_pages = []
for url in spider.urls:
page = spider.get(url)
cat = str(model.predict(page))
if cat == 'bio':
self.stdout.write(' * ' + url)
bio_pages.append(url)
self.stdout.write('Done.')
return bio_pages
def identify_bio_elements(self, firm, urls):
fts = FirmTrainingSet.get_for_firm(firm)
spider = Spider(firm.domain, os.path.join(self.scrape_dir, str(fts.id) + ".db"), workers=4, retry_attempts=2)
self.stdout.write("Identifying bio elements...\n")
model = ElementClassifier(os.path.join(settings.MODEL_DIR, 'model', str(fts.id) + "_element.tgm"))
model.load()
self.stdout.write('Retrieving element features...\n')
elements_out = []
for url in urls:
page = spider.get(url)
out_data = model.extract(page, format="html")
out_data['url'] = url
out_data = dict(out_data)
print json.dumps(out_data, indent=4)
elements_out.append(out_data)
self.stdout.write('Done.\n')
return elements_out
