def parse_amazon_date_to_range(d):
'''
Convert an AMAZON.DATE into a start/end date pair.
the payload from Amazon is one of the following:
specific date --> 20XX-XX-XX
week --> 20XX-WXX (i.e year-week_number)
month --> 20XX-XX (i.e. year-month_number)
'''
d = d.split('-')
if len(d) == 3:
# Specific date
d = map(int, d)
start = date(d[0], d[1], d[2])
return start, start + timedelta(hours=24)
if d[1].startswith('W'):
# A week number
c = Calendar()
# A list of weeks. Each week is a list of datetime.date instances
weeks = sum(c.yeardatescalendar(int(d[0]), 55)[0], [])
week_num = int(d[1][1:])
w = weeks[week_num]
return w[0], w[-1]
else:
# A month
y, m = map(int, d)
month_cal = sum(monthcalendar(y, m))
end = len([d for d in month_cal if d != 0])
return date(y, m, 1), date(y, m, end)
def most_frequent_days(year):
"""
List of most frequent days of the week in the given year
"""
calendar = Calendar(firstweekday=0)
i = calendar.yeardatescalendar(year, 1)
result = [
x.isoweekday() for x in i[0][0][0] + i[-1][-1][-1] if x.year == year
]
return [
day_name[x - 1] for x in set(result)
if result.count(x) == result.count(max(result, key=result.count))
]
open('generation_demand_full.csv', 'w'), [
'timestamp', 'demand', 'forecast', 'programmed', 'nuclear', 'coal',
'fuel_gas', 'combined_cycle', 'hydroelectric', 'solar', 'eolic',
'autoproduction', 'balearic_link', 'international_exchange'
])
generationDemandWriter.writeheader()
all_data = {}
now = datetime.now()
calendar = Calendar()
for year in range(2007, now.year + 1):
for date in filter(
lambda x: x.year == year,
chain(*chain(*calendar.yeardatescalendar(year, 12)[0]))):
if datetime(date.year, date.month, date.day) > now:
break
d = date.strftime('%Y-%m-%d')
filename = 'data/generation_demand_%s.json' % d
if not os.path.exists(filename):
data = r.generation_demand(d)
json.dump(data, open(filename, 'w'))
else:
data = json.load(open(filename, 'r'))
for datum in data:
if datum['timestamp'] not in all_data:
all_data[datum['timestamp']] = datum
filename = 'data/forecast_programmed_%s.json' % d
def get_months(date):
calendar = Calendar()
month_rows = calendar.yeardatescalendar(date.year, 1)
months = [month_row[0] for month_row in month_rows]
return months
import os.path
import csv
if not os.path.exists('data'):
os.mkdir('data')
generationDemandWriter = csv.DictWriter(open('generation_demand_full.csv', 'w'), ['timestamp', 'demand', 'forecast', 'programmed', 'nuclear', 'coal', 'fuel_gas', 'combined_cycle', 'hydroelectric', 'solar', 'eolic', 'autoproduction', 'balearic_link', 'international_exchange'])
generationDemandWriter.writeheader()
all_data = {}
now = datetime.now()
calendar = Calendar()
for year in range(2007, now.year + 1):
for date in filter(lambda x: x.year == year, chain(*chain(*calendar.yeardatescalendar(year, 12)[0]))):
if datetime(date.year, date.month, date.day) > now:
break
d = date.strftime('%Y-%m-%d')
filename = 'data/generation_demand_%s.json' % d
if not os.path.exists(filename):
data = r.generation_demand(d)
json.dump(data, open(filename, 'w'))
else:
data = json.load(open(filename, 'r'))
for datum in data:
if datum['timestamp'] not in all_data:
all_data[datum['timestamp']] = datum
filename = 'data/forecast_programmed_%s.json' % d
