def handle(self, *args, **options):
today = date(2014,11,1)
last_week = get_week_number(today) - 1
first_week = get_week_number(data_start)
outf = "%s/%s" % (CHART_CSV_DOWNLOAD_DIR, CSV_FILE_NAME)
print "writing to %s" % outf
outfile = open(outf, 'w')
field_names = make_header(first_week, last_week)
outfile.write(",".join(field_names) +"\n")
dw = csv.writer(outfile)
if write_cumulative:
outcumf = "%s/%s" % (CHART_CSV_DOWNLOAD_DIR, CSV_FILE_NAME_CUMULATIVE)
print "writing cumulative numbers to %s" % outcumf
outcumfile = open(outcumf, 'w')
field_names = make_header(first_week, last_week)
outcumfile.write(",".join(field_names) +"\n")
cumdw = csv.writer(outcumfile)
for data in data_series:
this_row = [data['data_id'], data['data_series_name']]
this_cum_row = [data['data_id'], data['data_series_name']]
for week in range(first_week, last_week+1):
print "handling %s week %s" % (data['data_series_name'], week)
this_row.append(summarize_week_queryset(week, data['q']))
if write_cumulative:
this_cum_row.append(summarize_week_queryset_cumulative(week, data['q']))
dw.writerow(this_row)
if write_cumulative:
cumdw.writerow(this_cum_row)
def handle(self, *args, **options):
# stop after the election
today = date(2014,11,1)
last_week = get_week_number(today)
first_week = get_week_number(data_start)
outf = "%s/%s" % (CHART_CSV_DOWNLOAD_DIR, CSV_FILE_NAME)
outfile = open(outf, 'w')
field_names = make_header(first_week, last_week)
outfile.write(",".join(field_names) +"\n")
dw = csv.writer(outfile)
summaries = DistrictWeekly.objects.filter(cycle_week_number__gte=first_week, cycle_week_number__lte=last_week, district__pk__in=district_list).select_related('District')
summary_hash = {}
for s in summaries:
summary_hash["%s-%s" % (s.district.pk, s.cycle_week_number)] = s.outside_spending
# regroup by week
for i in senate_districts:
row = [i['state'], i['id']]
for week in range(first_week, last_week+1):
key = "%s-%s" % (i['id'], week)
try:
row.append(summary_hash[key])
except KeyError:
row.append(0)
dw.writerow(row)
def handle(self, *args, **options):
cursor = connection.cursor()
today = date.today()
last_week = get_week_number(today) - 1
first_week = get_week_number(data_start)
outf = "%s/%s" % (CHART_CSV_DOWNLOAD_DIR, CSV_FILE_NAME)
print "writing to %s" % outf
outfile = open(outf, 'w')
field_names = make_header(first_week, last_week)
outfile.write(",".join(field_names) + "\n")
dw = csv.writer(outfile)
if write_cumulative:
outcumf = "%s/%s" % (CHART_CSV_DOWNLOAD_DIR,
CSV_FILE_NAME_CUMULATIVE)
print "writing cumulative numbers to %s" % outcumf
outcumfile = open(outcumf, 'w')
cum_field_names = make_header(1, last_week)
outcumfile.write(",".join(cum_field_names) + "\n")
cumdw = csv.writer(outcumfile)
for data in data_series:
this_row = [data['data_id'], data['data_series_name']]
this_cum_row = [data['data_id'], data['data_series_name']]
for week in range(first_week, last_week + 1):
print "handling %s week %s" % (data['data_series_name'], week)
this_row.append(summarize_week(week, data['q'], cursor))
if write_cumulative:
this_cum_row.append(
summarize_week_cumulative(week, data['q'], cursor))
dw.writerow(this_row)
if write_cumulative:
cumdw.writerow(this_cum_row)
def handle(self, *args, **options):
# stop after the election
today = date(2014, 11, 1)
last_week = get_week_number(today)
first_week = get_week_number(data_start)
outf = "%s/%s" % (CHART_CSV_DOWNLOAD_DIR, CSV_FILE_NAME)
outfile = open(outf, 'w')
field_names = make_header(first_week, last_week)
outfile.write(",".join(field_names) + "\n")
dw = csv.writer(outfile)
summaries = DistrictWeekly.objects.filter(
cycle_week_number__gte=first_week,
cycle_week_number__lte=last_week,
district__pk__in=district_list).select_related('District')
summary_hash = {}
for s in summaries:
summary_hash["%s-%s" % (s.district.pk,
s.cycle_week_number)] = s.outside_spending
# regroup by week
for i in senate_districts:
row = [i['state'], i['id']]
for week in range(first_week, last_week + 1):
key = "%s-%s" % (i['id'], week)
try:
row.append(summary_hash[key])
except KeyError:
row.append(0)
dw.writerow(row)
def weekFilter(queryset, querydict):
try:
week = querydict["week"]
# if there's no commas, it's just a single district
if week.upper() == "NOW":
queryset = queryset.filter(cycle_week_number=get_week_number(date.today()))
if week.upper() == "LAST":
queryset = queryset.filter(cycle_week_number=get_week_number(date.today()) - 1)
except KeyError:
pass
return queryset
def weekFilter(queryset, querydict):
try:
week = querydict['week']
# if there's no commas, it's just a single district
if week.upper() == "NOW":
queryset = queryset.filter(
cycle_week_number=get_week_number(date.today()))
if week.upper() == "LAST":
queryset = queryset.filter(
cycle_week_number=get_week_number(date.today()) - 1)
except KeyError:
pass
return queryset
def top_current_races(request):
week_number = get_week_number(datetime.date.today()) - 1
week_start = get_week_start(int(week_number))
week_start_formatted = week_start.strftime('%m/%d')
week_end = get_week_end(int(week_number))
week_end_formatted = week_end.strftime('%m/%d, %Y')
previous_week_number = int(week_number) - 1
following_week_number = int(week_number) + 1
period_start = week_start - datetime.timedelta(days=14)
weeklysummaries = DistrictWeekly.objects.filter(cycle_week_number=week_number, outside_spending__gt=1000).order_by('-outside_spending')[:3]
title = "Top races by outside spending, %s-%s" % (week_start_formatted, week_end_formatted)
district_ids = weeklysummaries.values("district__pk")
district_id_list = [str(x['district__pk']) for x in district_ids]
district_list = ",".join(district_id_list)
data_url = "http://realtime.influenceexplorer.com/api/districts-weekly/?week_start=%s&week_end=%s&districts=%s&format=json" % (int(week_number)-2, week_number, district_list)
return render_to_response('datapages/top_races.html',
{
'previous_week_number':previous_week_number,
'following_week_number':following_week_number,
'title':title,
'period_start': period_start,
'week_start':week_start,
'week_end':week_end,
'weeklysummaries':weeklysummaries,
'week_number':week_number,
'data_url':data_url,
},
context_instance=RequestContext(request)
)
def top_current_races(request):
week_number = get_week_number(datetime.date.today()) - 1
week_start = get_week_start(int(week_number))
week_start_formatted = week_start.strftime('%m/%d')
week_end = get_week_end(int(week_number))
week_end_formatted = week_end.strftime('%m/%d, %Y')
previous_week_number = int(week_number) - 1
following_week_number = int(week_number) + 1
period_start = week_start - datetime.timedelta(days=14)
weeklysummaries = DistrictWeekly.objects.filter(
cycle_week_number=week_number,
outside_spending__gt=1000).order_by('-outside_spending')[:3]
title = "Top races by outside spending, %s-%s" % (week_start_formatted,
week_end_formatted)
district_ids = weeklysummaries.values("district__pk")
district_id_list = [str(x['district__pk']) for x in district_ids]
district_list = ",".join(district_id_list)
data_url = "http://realtime.influenceexplorer.com/api/districts-weekly/?week_start=%s&week_end=%s&districts=%s&format=json" % (
int(week_number) - 2, week_number, district_list)
return render_to_response('datapages/top_races.html', {
'previous_week_number': previous_week_number,
'following_week_number': following_week_number,
'title': title,
'period_start': period_start,
'week_start': week_start,
'week_end': week_end,
'weeklysummaries': weeklysummaries,
'week_number': week_number,
'data_url': data_url,
},
context_instance=RequestContext(request))
def handle(self, *args, **options):
current_week_number = get_week_number(date.today())
week_list = [current_week_number]
if options['run_all']:
week_list = range(1,current_week_number+1)
for week_number in week_list:
print "Summarizing week %s" % (week_number)
summarize_week(week_number)