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from datetime import datetime, timedelta |
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import mysql.connector |
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import collections |
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from decimal import Decimal |
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import config |
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import statistics |
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######################################################################################################################## |
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# Aggregate hourly data by period |
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# rows_hourly: list of (start_datetime_utc, actual_value), should belong to one energy_category_id |
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# start_datetime_utc: start datetime in utc |
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# end_datetime_utc: end datetime in utc |
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# period_type: one of the following period types, 'hourly', 'daily', 'monthly' and 'yearly' |
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# Note: this procedure doesn't work with multiple energy categories |
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######################################################################################################################## |
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def aggregate_hourly_data_by_period(rows_hourly, start_datetime_utc, end_datetime_utc, period_type): |
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# todo: validate parameters |
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start_datetime_utc = start_datetime_utc.replace(tzinfo=None) |
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end_datetime_utc = end_datetime_utc.replace(tzinfo=None) |
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if period_type == "hourly": |
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result_rows_hourly = list() |
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# todo: add config.working_day_start_time_local |
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# todo: add config.minutes_to_count |
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current_datetime_utc = start_datetime_utc.replace(minute=0, second=0, microsecond=0, tzinfo=None) |
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while current_datetime_utc <= end_datetime_utc: |
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subtotal = Decimal(0.0) |
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for row in rows_hourly: |
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if current_datetime_utc <= row[0] < current_datetime_utc + \ |
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timedelta(minutes=config.minutes_to_count): |
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subtotal += row[1] |
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result_rows_hourly.append((current_datetime_utc, subtotal)) |
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current_datetime_utc += timedelta(minutes=config.minutes_to_count) |
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return result_rows_hourly |
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elif period_type == "daily": |
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result_rows_daily = list() |
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# todo: add config.working_day_start_time_local |
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# todo: add config.minutes_to_count |
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# calculate the start datetime in utc of the first day in local |
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start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
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current_datetime_utc = start_datetime_local.replace(hour=0) - timedelta(hours=int(config.utc_offset[1:3])) |
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while current_datetime_utc <= end_datetime_utc: |
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subtotal = Decimal(0.0) |
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for row in rows_hourly: |
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if current_datetime_utc <= row[0] < current_datetime_utc + timedelta(days=1): |
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subtotal += row[1] |
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result_rows_daily.append((current_datetime_utc, subtotal)) |
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current_datetime_utc += timedelta(days=1) |
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return result_rows_daily |
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elif period_type == "monthly": |
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result_rows_monthly = list() |
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# todo: add config.working_day_start_time_local |
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# todo: add config.minutes_to_count |
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# calculate the start datetime in utc of the first day in the first month in local |
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start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
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current_datetime_utc = \ |
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start_datetime_local.replace(day=1, hour=0) - timedelta(hours=int(config.utc_offset[1:3])) |
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while current_datetime_utc <= end_datetime_utc: |
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# calculate the next datetime in utc |
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View Code Duplication |
if current_datetime_utc.month == 1: |
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temp_day = 28 |
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ny = current_datetime_utc.year |
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if (ny % 100 != 0 and ny % 4 == 0) or (ny % 100 == 0 and ny % 400 == 0): |
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temp_day = 29 |
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next_datetime_utc = datetime(year=current_datetime_utc.year, |
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month=current_datetime_utc.month + 1, |
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day=temp_day, |
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hour=current_datetime_utc.hour, |
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minute=current_datetime_utc.minute, |
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second=0, |
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microsecond=0, |
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tzinfo=None) |
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elif current_datetime_utc.month == 2: |
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next_datetime_utc = datetime(year=current_datetime_utc.year, |
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month=current_datetime_utc.month + 1, |
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day=31, |
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hour=current_datetime_utc.hour, |
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minute=current_datetime_utc.minute, |
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second=0, |
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microsecond=0, |
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tzinfo=None) |
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elif current_datetime_utc.month in [3, 5, 8, 10]: |
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next_datetime_utc = datetime(year=current_datetime_utc.year, |
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month=current_datetime_utc.month + 1, |
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day=30, |
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hour=current_datetime_utc.hour, |
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minute=current_datetime_utc.minute, |
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second=0, |
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microsecond=0, |
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tzinfo=None) |
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elif current_datetime_utc.month == 7: |
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next_datetime_utc = datetime(year=current_datetime_utc.year, |
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month=current_datetime_utc.month + 1, |
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day=31, |
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hour=current_datetime_utc.hour, |
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minute=current_datetime_utc.minute, |
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second=0, |
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microsecond=0, |
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tzinfo=None) |
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elif current_datetime_utc.month in [4, 6, 9, 11]: |
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next_datetime_utc = datetime(year=current_datetime_utc.year, |
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month=current_datetime_utc.month + 1, |
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day=31, |
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hour=current_datetime_utc.hour, |
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minute=current_datetime_utc.minute, |
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second=0, |
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microsecond=0, |
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tzinfo=None) |
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elif current_datetime_utc.month == 12: |
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next_datetime_utc = datetime(year=current_datetime_utc.year + 1, |
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month=1, |
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day=31, |
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hour=current_datetime_utc.hour, |
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minute=current_datetime_utc.minute, |
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second=0, |
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microsecond=0, |
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tzinfo=None) |
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subtotal = Decimal(0.0) |
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for row in rows_hourly: |
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if current_datetime_utc <= row[0] < next_datetime_utc: |
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subtotal += row[1] |
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result_rows_monthly.append((current_datetime_utc, subtotal)) |
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current_datetime_utc = next_datetime_utc |
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return result_rows_monthly |
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elif period_type == "yearly": |
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result_rows_yearly = list() |
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# todo: add config.working_day_start_time_local |
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# todo: add config.minutes_to_count |
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# calculate the start datetime in utc of the first day in the first month in local |
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start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
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current_datetime_utc = start_datetime_local.replace(month=1, day=1, hour=0) - timedelta( |
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hours=int(config.utc_offset[1:3])) |
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while current_datetime_utc <= end_datetime_utc: |
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# calculate the next datetime in utc |
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# todo: timedelta of year |
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next_datetime_utc = datetime(year=current_datetime_utc.year + 2, |
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month=1, |
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day=1, |
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hour=current_datetime_utc.hour, |
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minute=current_datetime_utc.minute, |
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second=current_datetime_utc.second, |
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microsecond=current_datetime_utc.microsecond, |
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tzinfo=current_datetime_utc.tzinfo) - timedelta(days=1) |
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subtotal = Decimal(0.0) |
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for row in rows_hourly: |
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if current_datetime_utc <= row[0] < next_datetime_utc: |
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subtotal += row[1] |
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result_rows_yearly.append((current_datetime_utc, subtotal)) |
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current_datetime_utc = next_datetime_utc |
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return result_rows_yearly |
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######################################################################################################################## |
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# Get tariffs by energy category |
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######################################################################################################################## |
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View Code Duplication |
def get_energy_category_tariffs(cost_center_id, energy_category_id, start_datetime_utc, end_datetime_utc): |
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# todo: validate parameters |
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if cost_center_id is None: |
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return dict() |
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start_datetime_utc = start_datetime_utc.replace(tzinfo=None) |
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end_datetime_utc = end_datetime_utc.replace(tzinfo=None) |
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# get timezone offset in minutes, this value will be returned to client |
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timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
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if config.utc_offset[0] == '-': |
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timezone_offset = -timezone_offset |
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tariff_dict = collections.OrderedDict() |
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cnx = None |
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cursor = None |
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try: |
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cnx = mysql.connector.connect(**config.myems_system_db) |
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cursor = cnx.cursor() |
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query_tariffs = (" SELECT t.id, t.valid_from_datetime_utc, t.valid_through_datetime_utc " |
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" FROM tbl_tariffs t, tbl_cost_centers_tariffs cct " |
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" WHERE t.energy_category_id = %s AND " |
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" t.id = cct.tariff_id AND " |
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" cct.cost_center_id = %s AND " |
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" t.valid_through_datetime_utc >= %s AND " |
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" t.valid_from_datetime_utc <= %s " |
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" ORDER BY t.valid_from_datetime_utc ") |
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cursor.execute(query_tariffs, (energy_category_id, cost_center_id, start_datetime_utc, end_datetime_utc,)) |
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rows_tariffs = cursor.fetchall() |
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except Exception as e: |
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print(str(e)) |
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if cnx: |
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cnx.disconnect() |
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if cursor: |
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cursor.close() |
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return dict() |
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if rows_tariffs is None or len(rows_tariffs) == 0: |
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if cursor: |
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cursor.close() |
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if cnx: |
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cnx.disconnect() |
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return dict() |
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for row in rows_tariffs: |
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tariff_dict[row[0]] = {'valid_from_datetime_utc': row[1], |
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'valid_through_datetime_utc': row[2], |
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'rates': list()} |
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try: |
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query_timeofuse_tariffs = (" SELECT tariff_id, start_time_of_day, end_time_of_day, price " |
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" FROM tbl_tariffs_timeofuses " |
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" WHERE tariff_id IN ( " + ', '.join(map(str, tariff_dict.keys())) + ")" |
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" ORDER BY tariff_id, start_time_of_day ") |
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cursor.execute(query_timeofuse_tariffs, ) |
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rows_timeofuse_tariffs = cursor.fetchall() |
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except Exception as e: |
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print(str(e)) |
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if cnx: |
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cnx.disconnect() |
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if cursor: |
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cursor.close() |
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return dict() |
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if cursor: |
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cursor.close() |
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if cnx: |
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cnx.disconnect() |
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if rows_timeofuse_tariffs is None or len(rows_timeofuse_tariffs) == 0: |
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return dict() |
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for row in rows_timeofuse_tariffs: |
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tariff_dict[row[0]]['rates'].append({'start_time_of_day': row[1], |
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'end_time_of_day': row[2], |
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'price': row[3]}) |
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result = dict() |
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for tariff_id, tariff_value in tariff_dict.items(): |
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current_datetime_utc = tariff_value['valid_from_datetime_utc'] |
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while current_datetime_utc < tariff_value['valid_through_datetime_utc']: |
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for rate in tariff_value['rates']: |
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current_datetime_local = current_datetime_utc + timedelta(minutes=timezone_offset) |
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seconds_since_midnight = (current_datetime_local - |
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current_datetime_local.replace(hour=0, |
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second=0, |
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microsecond=0, |
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tzinfo=None)).total_seconds() |
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if rate['start_time_of_day'].total_seconds() <= \ |
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seconds_since_midnight < rate['end_time_of_day'].total_seconds(): |
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result[current_datetime_utc] = rate['price'] |
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break |
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# start from the next time slot |
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current_datetime_utc += timedelta(minutes=config.minutes_to_count) |
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return {k: v for k, v in result.items() if start_datetime_utc <= k <= end_datetime_utc} |
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######################################################################################################################## |
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# Get peak types of tariff by energy category |
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# peak types: toppeak, onpeak, midpeak, offpeak |
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######################################################################################################################## |
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View Code Duplication |
def get_energy_category_peak_types(cost_center_id, energy_category_id, start_datetime_utc, end_datetime_utc): |
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# todo: validate parameters |
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if cost_center_id is None: |
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return dict() |
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start_datetime_utc = start_datetime_utc.replace(tzinfo=None) |
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end_datetime_utc = end_datetime_utc.replace(tzinfo=None) |
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# get timezone offset in minutes, this value will be returned to client |
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timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
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if config.utc_offset[0] == '-': |
|
284
|
|
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timezone_offset = -timezone_offset |
|
285
|
|
|
|
|
286
|
|
|
tariff_dict = collections.OrderedDict() |
|
287
|
|
|
|
|
288
|
|
|
cnx = None |
|
289
|
|
|
cursor = None |
|
290
|
|
|
try: |
|
291
|
|
|
cnx = mysql.connector.connect(**config.myems_system_db) |
|
292
|
|
|
cursor = cnx.cursor() |
|
293
|
|
|
query_tariffs = (" SELECT t.id, t.valid_from_datetime_utc, t.valid_through_datetime_utc " |
|
294
|
|
|
" FROM tbl_tariffs t, tbl_cost_centers_tariffs cct " |
|
295
|
|
|
" WHERE t.energy_category_id = %s AND " |
|
296
|
|
|
" t.id = cct.tariff_id AND " |
|
297
|
|
|
" cct.cost_center_id = %s AND " |
|
298
|
|
|
" t.valid_through_datetime_utc >= %s AND " |
|
299
|
|
|
" t.valid_from_datetime_utc <= %s " |
|
300
|
|
|
" ORDER BY t.valid_from_datetime_utc ") |
|
301
|
|
|
cursor.execute(query_tariffs, (energy_category_id, cost_center_id, start_datetime_utc, end_datetime_utc,)) |
|
302
|
|
|
rows_tariffs = cursor.fetchall() |
|
303
|
|
|
except Exception as e: |
|
304
|
|
|
print(str(e)) |
|
305
|
|
|
if cnx: |
|
306
|
|
|
cnx.disconnect() |
|
307
|
|
|
if cursor: |
|
308
|
|
|
cursor.close() |
|
309
|
|
|
return dict() |
|
310
|
|
|
|
|
311
|
|
|
if rows_tariffs is None or len(rows_tariffs) == 0: |
|
312
|
|
|
if cursor: |
|
313
|
|
|
cursor.close() |
|
314
|
|
|
if cnx: |
|
315
|
|
|
cnx.disconnect() |
|
316
|
|
|
return dict() |
|
317
|
|
|
|
|
318
|
|
|
for row in rows_tariffs: |
|
319
|
|
|
tariff_dict[row[0]] = {'valid_from_datetime_utc': row[1], |
|
320
|
|
|
'valid_through_datetime_utc': row[2], |
|
321
|
|
|
'rates': list()} |
|
322
|
|
|
|
|
323
|
|
|
try: |
|
324
|
|
|
query_timeofuse_tariffs = (" SELECT tariff_id, start_time_of_day, end_time_of_day, peak_type " |
|
325
|
|
|
" FROM tbl_tariffs_timeofuses " |
|
326
|
|
|
" WHERE tariff_id IN ( " + ', '.join(map(str, tariff_dict.keys())) + ")" |
|
327
|
|
|
" ORDER BY tariff_id, start_time_of_day ") |
|
328
|
|
|
cursor.execute(query_timeofuse_tariffs, ) |
|
329
|
|
|
rows_timeofuse_tariffs = cursor.fetchall() |
|
330
|
|
|
except Exception as e: |
|
331
|
|
|
print(str(e)) |
|
332
|
|
|
if cnx: |
|
333
|
|
|
cnx.disconnect() |
|
334
|
|
|
if cursor: |
|
335
|
|
|
cursor.close() |
|
336
|
|
|
return dict() |
|
337
|
|
|
|
|
338
|
|
|
if cursor: |
|
339
|
|
|
cursor.close() |
|
340
|
|
|
if cnx: |
|
341
|
|
|
cnx.disconnect() |
|
342
|
|
|
|
|
343
|
|
|
if rows_timeofuse_tariffs is None or len(rows_timeofuse_tariffs) == 0: |
|
344
|
|
|
return dict() |
|
345
|
|
|
|
|
346
|
|
|
for row in rows_timeofuse_tariffs: |
|
347
|
|
|
tariff_dict[row[0]]['rates'].append({'start_time_of_day': row[1], |
|
348
|
|
|
'end_time_of_day': row[2], |
|
349
|
|
|
'peak_type': row[3]}) |
|
350
|
|
|
|
|
351
|
|
|
result = dict() |
|
352
|
|
|
for tariff_id, tariff_value in tariff_dict.items(): |
|
353
|
|
|
current_datetime_utc = tariff_value['valid_from_datetime_utc'] |
|
354
|
|
|
while current_datetime_utc < tariff_value['valid_through_datetime_utc']: |
|
355
|
|
|
for rate in tariff_value['rates']: |
|
356
|
|
|
current_datetime_local = current_datetime_utc + timedelta(minutes=timezone_offset) |
|
357
|
|
|
seconds_since_midnight = (current_datetime_local - |
|
358
|
|
|
current_datetime_local.replace(hour=0, |
|
359
|
|
|
second=0, |
|
360
|
|
|
microsecond=0, |
|
361
|
|
|
tzinfo=None)).total_seconds() |
|
362
|
|
|
if rate['start_time_of_day'].total_seconds() <= \ |
|
363
|
|
|
seconds_since_midnight < rate['end_time_of_day'].total_seconds(): |
|
364
|
|
|
result[current_datetime_utc] = rate['peak_type'] |
|
365
|
|
|
break |
|
366
|
|
|
|
|
367
|
|
|
# start from the next time slot |
|
368
|
|
|
current_datetime_utc += timedelta(minutes=config.minutes_to_count) |
|
369
|
|
|
|
|
370
|
|
|
return {k: v for k, v in result.items() if start_datetime_utc <= k <= end_datetime_utc} |
|
371
|
|
|
|
|
372
|
|
|
|
|
373
|
|
|
######################################################################################################################## |
|
374
|
|
|
# Averaging calculator of hourly data by period |
|
375
|
|
|
# rows_hourly: list of (start_datetime_utc, actual_value), should belong to one energy_category_id |
|
376
|
|
|
# start_datetime_utc: start datetime in utc |
|
377
|
|
|
# end_datetime_utc: end datetime in utc |
|
378
|
|
|
# period_type: one of the following period types, 'hourly', 'daily', 'monthly' and 'yearly' |
|
379
|
|
|
# Returns: periodically data of average and maximum |
|
380
|
|
|
# Note: this procedure doesn't work with multiple energy categories |
|
381
|
|
|
######################################################################################################################## |
|
382
|
|
|
def averaging_hourly_data_by_period(rows_hourly, start_datetime_utc, end_datetime_utc, period_type): |
|
383
|
|
|
# todo: validate parameters |
|
384
|
|
|
start_datetime_utc = start_datetime_utc.replace(tzinfo=None) |
|
385
|
|
|
end_datetime_utc = end_datetime_utc.replace(tzinfo=None) |
|
386
|
|
|
|
|
387
|
|
|
if period_type == "hourly": |
|
388
|
|
|
result_rows_hourly = list() |
|
389
|
|
|
# todo: add config.working_day_start_time_local |
|
390
|
|
|
# todo: add config.minutes_to_count |
|
391
|
|
|
total = Decimal(0.0) |
|
392
|
|
|
maximum = None |
|
393
|
|
|
counter = 0 |
|
394
|
|
|
current_datetime_utc = start_datetime_utc.replace(minute=0, second=0, microsecond=0, tzinfo=None) |
|
395
|
|
View Code Duplication |
while current_datetime_utc <= end_datetime_utc: |
|
|
|
|
|
|
396
|
|
|
sub_total = Decimal(0.0) |
|
397
|
|
|
sub_maximum = None |
|
398
|
|
|
sub_counter = 0 |
|
399
|
|
|
for row in rows_hourly: |
|
400
|
|
|
if current_datetime_utc <= row[0] < current_datetime_utc + \ |
|
401
|
|
|
timedelta(minutes=config.minutes_to_count): |
|
402
|
|
|
sub_total += row[1] |
|
403
|
|
|
if sub_maximum is None: |
|
404
|
|
|
sub_maximum = row[1] |
|
405
|
|
|
elif sub_maximum < row[1]: |
|
406
|
|
|
sub_maximum = row[1] |
|
407
|
|
|
sub_counter += 1 |
|
408
|
|
|
|
|
409
|
|
|
sub_average = (sub_total / sub_counter) if sub_counter > 0 else None |
|
410
|
|
|
result_rows_hourly.append((current_datetime_utc, sub_average, sub_maximum)) |
|
411
|
|
|
|
|
412
|
|
|
total += sub_total |
|
413
|
|
|
counter += sub_counter |
|
414
|
|
|
if sub_maximum is None: |
|
415
|
|
|
pass |
|
416
|
|
|
elif maximum is None: |
|
417
|
|
|
maximum = sub_maximum |
|
418
|
|
|
elif maximum < sub_maximum: |
|
419
|
|
|
maximum = sub_maximum |
|
420
|
|
|
|
|
421
|
|
|
current_datetime_utc += timedelta(minutes=config.minutes_to_count) |
|
422
|
|
|
|
|
423
|
|
|
average = total / counter if counter > 0 else None |
|
424
|
|
|
return result_rows_hourly, average, maximum |
|
425
|
|
|
|
|
426
|
|
|
elif period_type == "daily": |
|
427
|
|
|
result_rows_daily = list() |
|
428
|
|
|
# todo: add config.working_day_start_time_local |
|
429
|
|
|
# todo: add config.minutes_to_count |
|
430
|
|
|
total = Decimal(0.0) |
|
431
|
|
|
maximum = None |
|
432
|
|
|
counter = 0 |
|
433
|
|
|
# calculate the start datetime in utc of the first day in local |
|
434
|
|
|
start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
|
435
|
|
|
current_datetime_utc = start_datetime_local.replace(hour=0) - timedelta(hours=int(config.utc_offset[1:3])) |
|
436
|
|
View Code Duplication |
while current_datetime_utc <= end_datetime_utc: |
|
|
|
|
|
|
437
|
|
|
sub_total = Decimal(0.0) |
|
438
|
|
|
sub_maximum = None |
|
439
|
|
|
sub_counter = 0 |
|
440
|
|
|
for row in rows_hourly: |
|
441
|
|
|
if current_datetime_utc <= row[0] < current_datetime_utc + timedelta(days=1): |
|
442
|
|
|
sub_total += row[1] |
|
443
|
|
|
if sub_maximum is None: |
|
444
|
|
|
sub_maximum = row[1] |
|
445
|
|
|
elif sub_maximum < row[1]: |
|
446
|
|
|
sub_maximum = row[1] |
|
447
|
|
|
sub_counter += 1 |
|
448
|
|
|
|
|
449
|
|
|
sub_average = (sub_total / sub_counter) if sub_counter > 0 else None |
|
450
|
|
|
result_rows_daily.append((current_datetime_utc, sub_average, sub_maximum)) |
|
451
|
|
|
total += sub_total |
|
452
|
|
|
counter += sub_counter |
|
453
|
|
|
if sub_maximum is None: |
|
454
|
|
|
pass |
|
455
|
|
|
elif maximum is None: |
|
456
|
|
|
maximum = sub_maximum |
|
457
|
|
|
elif maximum < sub_maximum: |
|
458
|
|
|
maximum = sub_maximum |
|
459
|
|
|
current_datetime_utc += timedelta(days=1) |
|
460
|
|
|
|
|
461
|
|
|
average = total / counter if counter > 0 else None |
|
462
|
|
|
return result_rows_daily, average, maximum |
|
463
|
|
|
|
|
464
|
|
|
elif period_type == "monthly": |
|
465
|
|
|
result_rows_monthly = list() |
|
466
|
|
|
# todo: add config.working_day_start_time_local |
|
467
|
|
|
# todo: add config.minutes_to_count |
|
468
|
|
|
total = Decimal(0.0) |
|
469
|
|
|
maximum = None |
|
470
|
|
|
counter = 0 |
|
471
|
|
|
# calculate the start datetime in utc of the first day in the first month in local |
|
472
|
|
|
start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
|
473
|
|
|
current_datetime_utc = \ |
|
474
|
|
|
start_datetime_local.replace(day=1, hour=0) - timedelta(hours=int(config.utc_offset[1:3])) |
|
475
|
|
|
|
|
476
|
|
|
while current_datetime_utc <= end_datetime_utc: |
|
477
|
|
|
# calculate the next datetime in utc |
|
478
|
|
View Code Duplication |
if current_datetime_utc.month == 1: |
|
|
|
|
|
|
479
|
|
|
temp_day = 28 |
|
480
|
|
|
ny = current_datetime_utc.year |
|
481
|
|
|
if (ny % 100 != 0 and ny % 4 == 0) or (ny % 100 == 0 and ny % 400 == 0): |
|
482
|
|
|
temp_day = 29 |
|
483
|
|
|
|
|
484
|
|
|
next_datetime_utc = datetime(year=current_datetime_utc.year, |
|
485
|
|
|
month=current_datetime_utc.month + 1, |
|
486
|
|
|
day=temp_day, |
|
487
|
|
|
hour=current_datetime_utc.hour, |
|
488
|
|
|
minute=current_datetime_utc.minute, |
|
489
|
|
|
second=0, |
|
490
|
|
|
microsecond=0, |
|
491
|
|
|
tzinfo=None) |
|
492
|
|
|
elif current_datetime_utc.month == 2: |
|
493
|
|
|
next_datetime_utc = datetime(year=current_datetime_utc.year, |
|
494
|
|
|
month=current_datetime_utc.month + 1, |
|
495
|
|
|
day=31, |
|
496
|
|
|
hour=current_datetime_utc.hour, |
|
497
|
|
|
minute=current_datetime_utc.minute, |
|
498
|
|
|
second=0, |
|
499
|
|
|
microsecond=0, |
|
500
|
|
|
tzinfo=None) |
|
501
|
|
|
elif current_datetime_utc.month in [3, 5, 8, 10]: |
|
502
|
|
|
next_datetime_utc = datetime(year=current_datetime_utc.year, |
|
503
|
|
|
month=current_datetime_utc.month + 1, |
|
504
|
|
|
day=30, |
|
505
|
|
|
hour=current_datetime_utc.hour, |
|
506
|
|
|
minute=current_datetime_utc.minute, |
|
507
|
|
|
second=0, |
|
508
|
|
|
microsecond=0, |
|
509
|
|
|
tzinfo=None) |
|
510
|
|
|
elif current_datetime_utc.month == 7: |
|
511
|
|
|
next_datetime_utc = datetime(year=current_datetime_utc.year, |
|
512
|
|
|
month=current_datetime_utc.month + 1, |
|
513
|
|
|
day=31, |
|
514
|
|
|
hour=current_datetime_utc.hour, |
|
515
|
|
|
minute=current_datetime_utc.minute, |
|
516
|
|
|
second=0, |
|
517
|
|
|
microsecond=0, |
|
518
|
|
|
tzinfo=None) |
|
519
|
|
|
elif current_datetime_utc.month in [4, 6, 9, 11]: |
|
520
|
|
|
next_datetime_utc = datetime(year=current_datetime_utc.year, |
|
521
|
|
|
month=current_datetime_utc.month + 1, |
|
522
|
|
|
day=31, |
|
523
|
|
|
hour=current_datetime_utc.hour, |
|
524
|
|
|
minute=current_datetime_utc.minute, |
|
525
|
|
|
second=0, |
|
526
|
|
|
microsecond=0, |
|
527
|
|
|
tzinfo=None) |
|
528
|
|
|
elif current_datetime_utc.month == 12: |
|
529
|
|
|
next_datetime_utc = datetime(year=current_datetime_utc.year + 1, |
|
530
|
|
|
month=1, |
|
531
|
|
|
day=31, |
|
532
|
|
|
hour=current_datetime_utc.hour, |
|
533
|
|
|
minute=current_datetime_utc.minute, |
|
534
|
|
|
second=0, |
|
535
|
|
|
microsecond=0, |
|
536
|
|
|
tzinfo=None) |
|
537
|
|
|
|
|
538
|
|
|
sub_total = Decimal(0.0) |
|
539
|
|
|
sub_maximum = None |
|
540
|
|
|
sub_counter = 0 |
|
541
|
|
|
for row in rows_hourly: |
|
542
|
|
|
if current_datetime_utc <= row[0] < next_datetime_utc: |
|
|
|
|
|
|
543
|
|
|
sub_total += row[1] |
|
544
|
|
|
if sub_maximum is None: |
|
545
|
|
|
sub_maximum = row[1] |
|
546
|
|
|
elif sub_maximum < row[1]: |
|
547
|
|
|
sub_maximum = row[1] |
|
548
|
|
|
sub_counter += 1 |
|
549
|
|
|
|
|
550
|
|
|
sub_average = (sub_total / sub_counter) if sub_counter > 0 else None |
|
551
|
|
|
result_rows_monthly.append((current_datetime_utc, sub_average, sub_maximum)) |
|
552
|
|
|
total += sub_total |
|
553
|
|
|
counter += sub_counter |
|
554
|
|
|
if sub_maximum is None: |
|
555
|
|
|
pass |
|
556
|
|
|
elif maximum is None: |
|
557
|
|
|
maximum = sub_maximum |
|
558
|
|
|
elif maximum < sub_maximum: |
|
559
|
|
|
maximum = sub_maximum |
|
560
|
|
|
current_datetime_utc = next_datetime_utc |
|
561
|
|
|
|
|
562
|
|
|
average = total / counter if counter > 0 else None |
|
563
|
|
|
return result_rows_monthly, average, maximum |
|
564
|
|
|
|
|
565
|
|
|
elif period_type == "yearly": |
|
566
|
|
|
result_rows_yearly = list() |
|
567
|
|
|
# todo: add config.working_day_start_time_local |
|
568
|
|
|
# todo: add config.minutes_to_count |
|
569
|
|
|
total = Decimal(0.0) |
|
570
|
|
|
maximum = None |
|
571
|
|
|
counter = 0 |
|
572
|
|
|
# calculate the start datetime in utc of the first day in the first month in local |
|
573
|
|
|
start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
|
574
|
|
|
current_datetime_utc = start_datetime_local.replace(month=1, day=1, hour=0) - timedelta( |
|
575
|
|
|
hours=int(config.utc_offset[1:3])) |
|
576
|
|
|
|
|
577
|
|
|
while current_datetime_utc <= end_datetime_utc: |
|
578
|
|
|
# calculate the next datetime in utc |
|
579
|
|
|
# todo: timedelta of year |
|
580
|
|
|
next_datetime_utc = datetime(year=current_datetime_utc.year + 2, |
|
581
|
|
|
month=1, |
|
582
|
|
|
day=1, |
|
583
|
|
|
hour=current_datetime_utc.hour, |
|
584
|
|
|
minute=current_datetime_utc.minute, |
|
585
|
|
|
second=current_datetime_utc.second, |
|
586
|
|
|
microsecond=current_datetime_utc.microsecond, |
|
587
|
|
|
tzinfo=current_datetime_utc.tzinfo) - timedelta(days=1) |
|
588
|
|
|
sub_total = Decimal(0.0) |
|
589
|
|
|
sub_maximum = None |
|
590
|
|
|
sub_counter = 0 |
|
591
|
|
|
for row in rows_hourly: |
|
592
|
|
|
if current_datetime_utc <= row[0] < next_datetime_utc: |
|
593
|
|
|
sub_total += row[1] |
|
594
|
|
|
if sub_maximum is None: |
|
595
|
|
|
sub_maximum = row[1] |
|
596
|
|
|
elif sub_maximum < row[1]: |
|
597
|
|
|
sub_maximum = row[1] |
|
598
|
|
|
sub_counter += 1 |
|
599
|
|
|
|
|
600
|
|
|
sub_average = (sub_total / sub_counter) if sub_counter > 0 else None |
|
601
|
|
|
result_rows_yearly.append((current_datetime_utc, sub_average, sub_maximum)) |
|
602
|
|
|
total += sub_total |
|
603
|
|
|
counter += sub_counter |
|
604
|
|
|
if sub_maximum is None: |
|
605
|
|
|
pass |
|
606
|
|
|
elif maximum is None: |
|
607
|
|
|
maximum = sub_maximum |
|
608
|
|
|
elif maximum < sub_maximum: |
|
609
|
|
|
maximum = sub_maximum |
|
610
|
|
|
current_datetime_utc = next_datetime_utc |
|
611
|
|
|
|
|
612
|
|
|
average = total / counter if counter > 0 else None |
|
613
|
|
|
return result_rows_yearly, average, maximum |
|
614
|
|
|
|
|
615
|
|
|
|
|
616
|
|
|
######################################################################################################################## |
|
617
|
|
|
# Statistics calculator of hourly data by period |
|
618
|
|
|
# rows_hourly: list of (start_datetime_utc, actual_value), should belong to one energy_category_id |
|
619
|
|
|
# start_datetime_utc: start datetime in utc |
|
620
|
|
|
# end_datetime_utc: end datetime in utc |
|
621
|
|
|
# period_type: one of the following period types, 'hourly', 'daily', 'monthly' and 'yearly' |
|
622
|
|
|
# Returns: periodically data of values and statistics of mean, median, minimum, maximum, stdev and variance |
|
623
|
|
|
# Note: this procedure doesn't work with multiple energy categories |
|
624
|
|
|
######################################################################################################################## |
|
625
|
|
|
def statistics_hourly_data_by_period(rows_hourly, start_datetime_utc, end_datetime_utc, period_type): |
|
626
|
|
|
# todo: validate parameters |
|
627
|
|
|
start_datetime_utc = start_datetime_utc.replace(tzinfo=None) |
|
628
|
|
|
end_datetime_utc = end_datetime_utc.replace(tzinfo=None) |
|
629
|
|
|
|
|
630
|
|
|
if period_type == "hourly": |
|
631
|
|
|
result_rows_hourly = list() |
|
632
|
|
|
sample_data = list() |
|
633
|
|
|
# todo: add config.working_day_start_time_local |
|
634
|
|
|
# todo: add config.minutes_to_count |
|
635
|
|
|
counter = 0 |
|
636
|
|
|
mean = None |
|
637
|
|
|
median = None |
|
638
|
|
|
minimum = None |
|
639
|
|
|
maximum = None |
|
640
|
|
|
stdev = None |
|
641
|
|
|
variance = None |
|
642
|
|
|
current_datetime_utc = start_datetime_utc.replace(minute=0, second=0, microsecond=0, tzinfo=None) |
|
643
|
|
View Code Duplication |
while current_datetime_utc <= end_datetime_utc: |
|
|
|
|
|
|
644
|
|
|
sub_total = Decimal(0.0) |
|
645
|
|
|
for row in rows_hourly: |
|
646
|
|
|
if current_datetime_utc <= row[0] < current_datetime_utc + \ |
|
647
|
|
|
timedelta(minutes=config.minutes_to_count): |
|
648
|
|
|
sub_total += row[1] |
|
649
|
|
|
|
|
650
|
|
|
result_rows_hourly.append((current_datetime_utc, sub_total)) |
|
651
|
|
|
sample_data.append(sub_total) |
|
652
|
|
|
|
|
653
|
|
|
counter += 1 |
|
654
|
|
|
if minimum is None: |
|
655
|
|
|
minimum = sub_total |
|
656
|
|
|
elif minimum > sub_total: |
|
657
|
|
|
minimum = sub_total |
|
658
|
|
|
|
|
659
|
|
|
if maximum is None: |
|
660
|
|
|
maximum = sub_total |
|
661
|
|
|
elif maximum < sub_total: |
|
662
|
|
|
maximum = sub_total |
|
663
|
|
|
|
|
664
|
|
|
current_datetime_utc += timedelta(minutes=config.minutes_to_count) |
|
665
|
|
|
|
|
666
|
|
|
if len(sample_data) > 1: |
|
667
|
|
|
mean = statistics.mean(sample_data) |
|
668
|
|
|
median = statistics.median(sample_data) |
|
669
|
|
|
stdev = statistics.stdev(sample_data) |
|
670
|
|
|
variance = statistics.variance(sample_data) |
|
671
|
|
|
|
|
672
|
|
|
return result_rows_hourly, mean, median, minimum, maximum, stdev, variance |
|
673
|
|
|
|
|
674
|
|
|
elif period_type == "daily": |
|
675
|
|
|
result_rows_daily = list() |
|
676
|
|
|
sample_data = list() |
|
677
|
|
|
# todo: add config.working_day_start_time_local |
|
678
|
|
|
# todo: add config.minutes_to_count |
|
679
|
|
|
counter = 0 |
|
680
|
|
|
mean = None |
|
681
|
|
|
median = None |
|
682
|
|
|
minimum = None |
|
683
|
|
|
maximum = None |
|
684
|
|
|
stdev = None |
|
685
|
|
|
variance = None |
|
686
|
|
|
# calculate the start datetime in utc of the first day in local |
|
687
|
|
|
start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
|
688
|
|
|
current_datetime_utc = start_datetime_local.replace(hour=0) - timedelta(hours=int(config.utc_offset[1:3])) |
|
689
|
|
View Code Duplication |
while current_datetime_utc <= end_datetime_utc: |
|
|
|
|
|
|
690
|
|
|
sub_total = Decimal(0.0) |
|
691
|
|
|
for row in rows_hourly: |
|
692
|
|
|
if current_datetime_utc <= row[0] < current_datetime_utc + timedelta(days=1): |
|
693
|
|
|
sub_total += row[1] |
|
694
|
|
|
|
|
695
|
|
|
result_rows_daily.append((current_datetime_utc, sub_total)) |
|
696
|
|
|
sample_data.append(sub_total) |
|
697
|
|
|
|
|
698
|
|
|
counter += 1 |
|
699
|
|
|
if minimum is None: |
|
700
|
|
|
minimum = sub_total |
|
701
|
|
|
elif minimum > sub_total: |
|
702
|
|
|
minimum = sub_total |
|
703
|
|
|
|
|
704
|
|
|
if maximum is None: |
|
705
|
|
|
maximum = sub_total |
|
706
|
|
|
elif maximum < sub_total: |
|
707
|
|
|
maximum = sub_total |
|
708
|
|
|
current_datetime_utc += timedelta(days=1) |
|
709
|
|
|
|
|
710
|
|
|
if len(sample_data) > 1: |
|
711
|
|
|
mean = statistics.mean(sample_data) |
|
712
|
|
|
median = statistics.median(sample_data) |
|
713
|
|
|
stdev = statistics.stdev(sample_data) |
|
714
|
|
|
variance = statistics.variance(sample_data) |
|
715
|
|
|
|
|
716
|
|
|
return result_rows_daily, mean, median, minimum, maximum, stdev, variance |
|
717
|
|
|
|
|
718
|
|
|
elif period_type == "monthly": |
|
719
|
|
|
result_rows_monthly = list() |
|
720
|
|
|
sample_data = list() |
|
721
|
|
|
# todo: add config.working_day_start_time_local |
|
722
|
|
|
# todo: add config.minutes_to_count |
|
723
|
|
|
counter = 0 |
|
724
|
|
|
mean = None |
|
725
|
|
|
median = None |
|
726
|
|
|
minimum = None |
|
727
|
|
|
maximum = None |
|
728
|
|
|
stdev = None |
|
729
|
|
|
variance = None |
|
730
|
|
|
# calculate the start datetime in utc of the first day in the first month in local |
|
731
|
|
|
start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
|
732
|
|
|
current_datetime_utc = \ |
|
733
|
|
|
start_datetime_local.replace(day=1, hour=0) - timedelta(hours=int(config.utc_offset[1:3])) |
|
734
|
|
|
|
|
735
|
|
|
while current_datetime_utc <= end_datetime_utc: |
|
736
|
|
|
# calculate the next datetime in utc |
|
737
|
|
View Code Duplication |
if current_datetime_utc.month == 1: |
|
|
|
|
|
|
738
|
|
|
temp_day = 28 |
|
739
|
|
|
ny = current_datetime_utc.year |
|
740
|
|
|
if (ny % 100 != 0 and ny % 4 == 0) or (ny % 100 == 0 and ny % 400 == 0): |
|
741
|
|
|
temp_day = 29 |
|
742
|
|
|
|
|
743
|
|
|
next_datetime_utc = datetime(year=current_datetime_utc.year, |
|
744
|
|
|
month=current_datetime_utc.month + 1, |
|
745
|
|
|
day=temp_day, |
|
746
|
|
|
hour=current_datetime_utc.hour, |
|
747
|
|
|
minute=current_datetime_utc.minute, |
|
748
|
|
|
second=0, |
|
749
|
|
|
microsecond=0, |
|
750
|
|
|
tzinfo=None) |
|
751
|
|
|
elif current_datetime_utc.month == 2: |
|
752
|
|
|
next_datetime_utc = datetime(year=current_datetime_utc.year, |
|
753
|
|
|
month=current_datetime_utc.month + 1, |
|
754
|
|
|
day=31, |
|
755
|
|
|
hour=current_datetime_utc.hour, |
|
756
|
|
|
minute=current_datetime_utc.minute, |
|
757
|
|
|
second=0, |
|
758
|
|
|
microsecond=0, |
|
759
|
|
|
tzinfo=None) |
|
760
|
|
|
elif current_datetime_utc.month in [3, 5, 8, 10]: |
|
761
|
|
|
next_datetime_utc = datetime(year=current_datetime_utc.year, |
|
762
|
|
|
month=current_datetime_utc.month + 1, |
|
763
|
|
|
day=30, |
|
764
|
|
|
hour=current_datetime_utc.hour, |
|
765
|
|
|
minute=current_datetime_utc.minute, |
|
766
|
|
|
second=0, |
|
767
|
|
|
microsecond=0, |
|
768
|
|
|
tzinfo=None) |
|
769
|
|
|
elif current_datetime_utc.month == 7: |
|
770
|
|
|
next_datetime_utc = datetime(year=current_datetime_utc.year, |
|
771
|
|
|
month=current_datetime_utc.month + 1, |
|
772
|
|
|
day=31, |
|
773
|
|
|
hour=current_datetime_utc.hour, |
|
774
|
|
|
minute=current_datetime_utc.minute, |
|
775
|
|
|
second=0, |
|
776
|
|
|
microsecond=0, |
|
777
|
|
|
tzinfo=None) |
|
778
|
|
|
elif current_datetime_utc.month in [4, 6, 9, 11]: |
|
779
|
|
|
next_datetime_utc = datetime(year=current_datetime_utc.year, |
|
780
|
|
|
month=current_datetime_utc.month + 1, |
|
781
|
|
|
day=31, |
|
782
|
|
|
hour=current_datetime_utc.hour, |
|
783
|
|
|
minute=current_datetime_utc.minute, |
|
784
|
|
|
second=0, |
|
785
|
|
|
microsecond=0, |
|
786
|
|
|
tzinfo=None) |
|
787
|
|
|
elif current_datetime_utc.month == 12: |
|
788
|
|
|
next_datetime_utc = datetime(year=current_datetime_utc.year + 1, |
|
789
|
|
|
month=1, |
|
790
|
|
|
day=31, |
|
791
|
|
|
hour=current_datetime_utc.hour, |
|
792
|
|
|
minute=current_datetime_utc.minute, |
|
793
|
|
|
second=0, |
|
794
|
|
|
microsecond=0, |
|
795
|
|
|
tzinfo=None) |
|
796
|
|
|
|
|
797
|
|
|
sub_total = Decimal(0.0) |
|
798
|
|
|
for row in rows_hourly: |
|
799
|
|
|
if current_datetime_utc <= row[0] < next_datetime_utc: |
|
|
|
|
|
|
800
|
|
|
sub_total += row[1] |
|
801
|
|
|
|
|
802
|
|
|
result_rows_monthly.append((current_datetime_utc, sub_total)) |
|
803
|
|
|
sample_data.append(sub_total) |
|
804
|
|
|
|
|
805
|
|
|
counter += 1 |
|
806
|
|
|
if minimum is None: |
|
807
|
|
|
minimum = sub_total |
|
808
|
|
|
elif minimum > sub_total: |
|
809
|
|
|
minimum = sub_total |
|
810
|
|
|
|
|
811
|
|
|
if maximum is None: |
|
812
|
|
|
maximum = sub_total |
|
813
|
|
|
elif maximum < sub_total: |
|
814
|
|
|
maximum = sub_total |
|
815
|
|
|
current_datetime_utc = next_datetime_utc |
|
816
|
|
|
|
|
817
|
|
|
if len(sample_data) > 1: |
|
818
|
|
|
mean = statistics.mean(sample_data) |
|
819
|
|
|
median = statistics.median(sample_data) |
|
820
|
|
|
stdev = statistics.stdev(sample_data) |
|
821
|
|
|
variance = statistics.variance(sample_data) |
|
822
|
|
|
|
|
823
|
|
|
return result_rows_monthly, mean, median, minimum, maximum, stdev, variance |
|
824
|
|
|
|
|
825
|
|
|
elif period_type == "yearly": |
|
826
|
|
|
result_rows_yearly = list() |
|
827
|
|
|
sample_data = list() |
|
828
|
|
|
# todo: add config.working_day_start_time_local |
|
829
|
|
|
# todo: add config.minutes_to_count |
|
830
|
|
|
mean = None |
|
831
|
|
|
median = None |
|
832
|
|
|
minimum = None |
|
833
|
|
|
maximum = None |
|
834
|
|
|
stdev = None |
|
835
|
|
|
variance = None |
|
836
|
|
|
# calculate the start datetime in utc of the first day in the first month in local |
|
837
|
|
|
start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
|
838
|
|
|
current_datetime_utc = start_datetime_local.replace(month=1, day=1, hour=0) - timedelta( |
|
839
|
|
|
hours=int(config.utc_offset[1:3])) |
|
840
|
|
|
|
|
841
|
|
|
while current_datetime_utc <= end_datetime_utc: |
|
842
|
|
|
# calculate the next datetime in utc |
|
843
|
|
|
# todo: timedelta of year |
|
844
|
|
|
next_datetime_utc = datetime(year=current_datetime_utc.year + 2, |
|
845
|
|
|
month=1, |
|
846
|
|
|
day=1, |
|
847
|
|
|
hour=current_datetime_utc.hour, |
|
848
|
|
|
minute=current_datetime_utc.minute, |
|
849
|
|
|
second=current_datetime_utc.second, |
|
850
|
|
|
microsecond=current_datetime_utc.microsecond, |
|
851
|
|
|
tzinfo=current_datetime_utc.tzinfo) - timedelta(days=1) |
|
852
|
|
|
sub_total = Decimal(0.0) |
|
853
|
|
|
for row in rows_hourly: |
|
854
|
|
|
if current_datetime_utc <= row[0] < next_datetime_utc: |
|
855
|
|
|
sub_total += row[1] |
|
856
|
|
|
|
|
857
|
|
|
result_rows_yearly.append((current_datetime_utc, sub_total)) |
|
858
|
|
|
sample_data.append(sub_total) |
|
859
|
|
|
|
|
860
|
|
|
if minimum is None: |
|
861
|
|
|
minimum = sub_total |
|
862
|
|
|
elif minimum > sub_total: |
|
863
|
|
|
minimum = sub_total |
|
864
|
|
|
if maximum is None: |
|
865
|
|
|
maximum = sub_total |
|
866
|
|
|
elif maximum < sub_total: |
|
867
|
|
|
maximum = sub_total |
|
868
|
|
|
|
|
869
|
|
|
current_datetime_utc = next_datetime_utc |
|
870
|
|
|
|
|
871
|
|
|
if len(sample_data) > 1: |
|
872
|
|
|
mean = statistics.mean(sample_data) |
|
873
|
|
|
median = statistics.median(sample_data) |
|
874
|
|
|
stdev = statistics.stdev(sample_data) |
|
875
|
|
|
variance = statistics.variance(sample_data) |
|
876
|
|
|
|
|
877
|
|
|
return result_rows_yearly, mean, median, minimum, maximum, stdev, variance |
|
878
|
|
|
|
myems /
myems-api
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