def handle(self, *args, **kwargs):
# it's important to import this to register the table builder with the data store
import api.algorithms
# we certainly don't want to cache 25 GiB of tables in memory
settings.CACHE_TABLES_IN_MEMORY = False
self.stdout.write('This command will regenerate all the extrapolation tables. Existing tables will be overwritten.')
self.stdout.write('Please note that you should have about 25 GiB of free disk space.')
self.stdout.write('Rereading CSV to make sure we have the latest version of the dataset...')
dataStore.readCSVs()
sexes = api.algorithms.SEXES.keys()
countries = dataStore.countries
totalCount = len(sexes)*len(countries)
self.stdout.write('Regenerating %i extrapolation tables... this will take a while!' % totalCount)
counter = 0
calculationTimes = []
for sex in sexes:
for region in countries:
start = time.clock()
table = dataStore.generateExtrapolationTable(sex, region)
table = None # delete from memory immediately
calculationTimes.append(time.clock() - start)
counter += 1
avgCalcTime = sum(calculationTimes)/len(calculationTimes)
estimation = max(1.0, (totalCount - counter) * avgCalcTime / 60)
self.stdout.write('Generated %i / %i tables, estimating %i minutes left.' % (counter, totalCount, estimation))
def handle(self, *args, **kwargs):
dataStore.readCSVs()