myems /
myems-api
| Total Complexity | 175 |
| Total Lines | 878 |
| Duplicated Lines | 53.08 % |
| Changes | 0 | ||
Duplicate code is one of the most pungent code smells. A rule that is often used is to re-structure code once it is duplicated in three or more places.
Common duplication problems, and corresponding solutions are:
Complex classes like core.utilities often do a lot of different things. To break such a class down, we need to identify a cohesive component within that class. A common approach to find such a component is to look for fields/methods that share the same prefixes, or suffixes.
Once you have determined the fields that belong together, you can apply the Extract Class refactoring. If the component makes sense as a sub-class, Extract Subclass is also a candidate, and is often faster.
| 1 | from datetime import datetime, timedelta |
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| 2 | import mysql.connector |
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| 3 | import collections |
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| 4 | from decimal import Decimal |
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| 5 | import config |
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| 6 | import statistics |
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| 7 | |||
| 8 | |||
| 9 | ######################################################################################################################## |
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| 10 | # Aggregate hourly data by period |
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| 11 | # rows_hourly: list of (start_datetime_utc, actual_value), should belong to one energy_category_id |
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| 12 | # start_datetime_utc: start datetime in utc |
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| 13 | # end_datetime_utc: end datetime in utc |
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| 14 | # period_type: one of the following period types, 'hourly', 'daily', 'monthly' and 'yearly' |
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| 15 | # Note: this procedure doesn't work with multiple energy categories |
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| 16 | ######################################################################################################################## |
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| 17 | def aggregate_hourly_data_by_period(rows_hourly, start_datetime_utc, end_datetime_utc, period_type): |
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| 18 | # todo: validate parameters |
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| 19 | start_datetime_utc = start_datetime_utc.replace(tzinfo=None) |
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| 20 | end_datetime_utc = end_datetime_utc.replace(tzinfo=None) |
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| 21 | |||
| 22 | if period_type == "hourly": |
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| 23 | result_rows_hourly = list() |
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| 24 | # todo: add config.working_day_start_time_local |
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| 25 | # todo: add config.minutes_to_count |
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| 26 | current_datetime_utc = start_datetime_utc.replace(minute=0, second=0, microsecond=0, tzinfo=None) |
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| 27 | while current_datetime_utc <= end_datetime_utc: |
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| 28 | subtotal = Decimal(0.0) |
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| 29 | for row in rows_hourly: |
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| 30 | if current_datetime_utc <= row[0] < current_datetime_utc + \ |
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| 31 | timedelta(minutes=config.minutes_to_count): |
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| 32 | subtotal += row[1] |
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| 33 | result_rows_hourly.append((current_datetime_utc, subtotal)) |
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| 34 | current_datetime_utc += timedelta(minutes=config.minutes_to_count) |
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| 35 | |||
| 36 | return result_rows_hourly |
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| 37 | |||
| 38 | elif period_type == "daily": |
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| 39 | result_rows_daily = list() |
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| 40 | # todo: add config.working_day_start_time_local |
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| 41 | # todo: add config.minutes_to_count |
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| 42 | # calculate the start datetime in utc of the first day in local |
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| 43 | start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
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| 44 | current_datetime_utc = start_datetime_local.replace(hour=0) - timedelta(hours=int(config.utc_offset[1:3])) |
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| 45 | while current_datetime_utc <= end_datetime_utc: |
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| 46 | subtotal = Decimal(0.0) |
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| 47 | for row in rows_hourly: |
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| 48 | if current_datetime_utc <= row[0] < current_datetime_utc + timedelta(days=1): |
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| 49 | subtotal += row[1] |
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| 50 | result_rows_daily.append((current_datetime_utc, subtotal)) |
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| 51 | current_datetime_utc += timedelta(days=1) |
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| 52 | |||
| 53 | return result_rows_daily |
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| 54 | |||
| 55 | elif period_type == "monthly": |
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| 56 | result_rows_monthly = list() |
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| 57 | # todo: add config.working_day_start_time_local |
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| 58 | # todo: add config.minutes_to_count |
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| 59 | # calculate the start datetime in utc of the first day in the first month in local |
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| 60 | start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
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| 61 | current_datetime_utc = \ |
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| 62 | start_datetime_local.replace(day=1, hour=0) - timedelta(hours=int(config.utc_offset[1:3])) |
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| 63 | |||
| 64 | while current_datetime_utc <= end_datetime_utc: |
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| 65 | # calculate the next datetime in utc |
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| 66 | View Code Duplication | if current_datetime_utc.month == 1: |
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|
Duplication
introduced
by
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| 67 | temp_day = 28 |
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| 68 | ny = current_datetime_utc.year |
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| 69 | if (ny % 100 != 0 and ny % 4 == 0) or (ny % 100 == 0 and ny % 400 == 0): |
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| 70 | temp_day = 29 |
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| 71 | |||
| 72 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
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| 73 | month=current_datetime_utc.month + 1, |
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| 74 | day=temp_day, |
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| 75 | hour=current_datetime_utc.hour, |
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| 76 | minute=current_datetime_utc.minute, |
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| 77 | second=0, |
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| 78 | microsecond=0, |
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| 79 | tzinfo=None) |
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| 80 | elif current_datetime_utc.month == 2: |
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| 81 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
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| 82 | month=current_datetime_utc.month + 1, |
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| 83 | day=31, |
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| 84 | hour=current_datetime_utc.hour, |
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| 85 | minute=current_datetime_utc.minute, |
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| 86 | second=0, |
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| 87 | microsecond=0, |
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| 88 | tzinfo=None) |
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| 89 | elif current_datetime_utc.month in [3, 5, 8, 10]: |
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| 90 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
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| 91 | month=current_datetime_utc.month + 1, |
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| 92 | day=30, |
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| 93 | hour=current_datetime_utc.hour, |
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| 94 | minute=current_datetime_utc.minute, |
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| 95 | second=0, |
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| 96 | microsecond=0, |
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| 97 | tzinfo=None) |
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| 98 | elif current_datetime_utc.month == 7: |
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| 99 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
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| 100 | month=current_datetime_utc.month + 1, |
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| 101 | day=31, |
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| 102 | hour=current_datetime_utc.hour, |
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| 103 | minute=current_datetime_utc.minute, |
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| 104 | second=0, |
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| 105 | microsecond=0, |
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| 106 | tzinfo=None) |
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| 107 | elif current_datetime_utc.month in [4, 6, 9, 11]: |
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| 108 | next_datetime_utc = datetime(year=current_datetime_utc.year, |
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| 109 | month=current_datetime_utc.month + 1, |
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| 110 | day=31, |
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| 111 | hour=current_datetime_utc.hour, |
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| 112 | minute=current_datetime_utc.minute, |
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| 113 | second=0, |
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| 114 | microsecond=0, |
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| 115 | tzinfo=None) |
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| 116 | elif current_datetime_utc.month == 12: |
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| 117 | next_datetime_utc = datetime(year=current_datetime_utc.year + 1, |
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| 118 | month=1, |
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| 119 | day=31, |
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| 120 | hour=current_datetime_utc.hour, |
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| 121 | minute=current_datetime_utc.minute, |
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| 122 | second=0, |
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| 123 | microsecond=0, |
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| 124 | tzinfo=None) |
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| 125 | |||
| 126 | subtotal = Decimal(0.0) |
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| 127 | for row in rows_hourly: |
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| 128 | if current_datetime_utc <= row[0] < next_datetime_utc: |
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| 129 | subtotal += row[1] |
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| 130 | |||
| 131 | result_rows_monthly.append((current_datetime_utc, subtotal)) |
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| 132 | current_datetime_utc = next_datetime_utc |
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| 133 | |||
| 134 | return result_rows_monthly |
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| 135 | |||
| 136 | elif period_type == "yearly": |
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| 137 | result_rows_yearly = list() |
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| 138 | # todo: add config.working_day_start_time_local |
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| 139 | # todo: add config.minutes_to_count |
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| 140 | # calculate the start datetime in utc of the first day in the first month in local |
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| 141 | start_datetime_local = start_datetime_utc + timedelta(hours=int(config.utc_offset[1:3])) |
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| 142 | current_datetime_utc = start_datetime_local.replace(month=1, day=1, hour=0) - timedelta( |
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| 143 | hours=int(config.utc_offset[1:3])) |
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| 144 | |||
| 145 | while current_datetime_utc <= end_datetime_utc: |
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| 146 | # calculate the next datetime in utc |
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| 147 | # todo: timedelta of year |
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| 148 | next_datetime_utc = datetime(year=current_datetime_utc.year + 2, |
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| 149 | month=1, |
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| 150 | day=1, |
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| 151 | hour=current_datetime_utc.hour, |
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| 152 | minute=current_datetime_utc.minute, |
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| 153 | second=current_datetime_utc.second, |
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| 154 | microsecond=current_datetime_utc.microsecond, |
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| 155 | tzinfo=current_datetime_utc.tzinfo) - timedelta(days=1) |
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| 156 | subtotal = Decimal(0.0) |
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| 157 | for row in rows_hourly: |
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| 158 | if current_datetime_utc <= row[0] < next_datetime_utc: |
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| 159 | subtotal += row[1] |
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| 160 | |||
| 161 | result_rows_yearly.append((current_datetime_utc, subtotal)) |
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| 162 | current_datetime_utc = next_datetime_utc |
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| 163 | return result_rows_yearly |
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| 164 | |||
| 165 | |||
| 166 | ######################################################################################################################## |
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| 167 | # Get tariffs by energy category |
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| 168 | ######################################################################################################################## |
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| 169 | View Code Duplication | def get_energy_category_tariffs(cost_center_id, energy_category_id, start_datetime_utc, end_datetime_utc): |
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| 170 | # todo: validate parameters |
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| 171 | if cost_center_id is None: |
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| 172 | return dict() |
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| 173 | |||
| 174 | start_datetime_utc = start_datetime_utc.replace(tzinfo=None) |
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| 175 | end_datetime_utc = end_datetime_utc.replace(tzinfo=None) |
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| 176 | |||
| 177 | # get timezone offset in minutes, this value will be returned to client |
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| 178 | timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
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| 179 | if config.utc_offset[0] == '-': |
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| 180 | timezone_offset = -timezone_offset |
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| 181 | |||
| 182 | tariff_dict = collections.OrderedDict() |
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| 183 | |||
| 184 | cnx = None |
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| 185 | cursor = None |
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| 186 | try: |
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| 187 | cnx = mysql.connector.connect(**config.myems_system_db) |
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| 188 | cursor = cnx.cursor() |
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| 189 | query_tariffs = (" SELECT t.id, t.valid_from_datetime_utc, t.valid_through_datetime_utc " |
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| 190 | " FROM tbl_tariffs t, tbl_cost_centers_tariffs cct " |
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| 191 | " WHERE t.energy_category_id = %s AND " |
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| 192 | " t.id = cct.tariff_id AND " |
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| 193 | " cct.cost_center_id = %s AND " |
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| 194 | " t.valid_through_datetime_utc >= %s AND " |
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| 195 | " t.valid_from_datetime_utc <= %s " |
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| 196 | " ORDER BY t.valid_from_datetime_utc ") |
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| 197 | cursor.execute(query_tariffs, (energy_category_id, cost_center_id, start_datetime_utc, end_datetime_utc,)) |
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| 198 | rows_tariffs = cursor.fetchall() |
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| 199 | except Exception as e: |
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| 200 | print(str(e)) |
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| 201 | if cnx: |
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| 202 | cnx.disconnect() |
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| 203 | if cursor: |
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| 204 | cursor.close() |
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| 205 | return dict() |
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| 206 | |||
| 207 | if rows_tariffs is None or len(rows_tariffs) == 0: |
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| 208 | if cursor: |
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| 209 | cursor.close() |
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| 210 | if cnx: |
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| 211 | cnx.disconnect() |
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| 212 | return dict() |
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| 213 | |||
| 214 | for row in rows_tariffs: |
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| 215 | tariff_dict[row[0]] = {'valid_from_datetime_utc': row[1], |
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| 216 | 'valid_through_datetime_utc': row[2], |
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| 217 | 'rates': list()} |
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| 218 | |||
| 219 | try: |
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| 220 | query_timeofuse_tariffs = (" SELECT tariff_id, start_time_of_day, end_time_of_day, price " |
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| 221 | " FROM tbl_tariffs_timeofuses " |
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| 222 | " WHERE tariff_id IN ( " + ', '.join(map(str, tariff_dict.keys())) + ")" |
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| 223 | " ORDER BY tariff_id, start_time_of_day ") |
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| 224 | cursor.execute(query_timeofuse_tariffs, ) |
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| 225 | rows_timeofuse_tariffs = cursor.fetchall() |
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| 226 | except Exception as e: |
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| 227 | print(str(e)) |
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| 228 | if cnx: |
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| 229 | cnx.disconnect() |
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| 230 | if cursor: |
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| 231 | cursor.close() |
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| 232 | return dict() |
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| 233 | |||
| 234 | if cursor: |
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| 235 | cursor.close() |
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| 236 | if cnx: |
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| 237 | cnx.disconnect() |
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| 238 | |||
| 239 | if rows_timeofuse_tariffs is None or len(rows_timeofuse_tariffs) == 0: |
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| 240 | return dict() |
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| 241 | |||
| 242 | for row in rows_timeofuse_tariffs: |
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| 243 | tariff_dict[row[0]]['rates'].append({'start_time_of_day': row[1], |
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| 244 | 'end_time_of_day': row[2], |
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| 245 | 'price': row[3]}) |
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| 246 | |||
| 247 | result = dict() |
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| 248 | for tariff_id, tariff_value in tariff_dict.items(): |
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| 249 | current_datetime_utc = tariff_value['valid_from_datetime_utc'] |
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| 250 | while current_datetime_utc < tariff_value['valid_through_datetime_utc']: |
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| 251 | for rate in tariff_value['rates']: |
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| 252 | current_datetime_local = current_datetime_utc + timedelta(minutes=timezone_offset) |
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| 253 | seconds_since_midnight = (current_datetime_local - |
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| 254 | current_datetime_local.replace(hour=0, |
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| 255 | second=0, |
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| 256 | microsecond=0, |
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| 257 | tzinfo=None)).total_seconds() |
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| 258 | if rate['start_time_of_day'].total_seconds() <= \ |
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| 259 | seconds_since_midnight < rate['end_time_of_day'].total_seconds(): |
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| 260 | result[current_datetime_utc] = rate['price'] |
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| 261 | break |
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| 262 | |||
| 263 | # start from the next time slot |
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| 264 | current_datetime_utc += timedelta(minutes=config.minutes_to_count) |
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| 265 | |||
| 266 | return {k: v for k, v in result.items() if start_datetime_utc <= k <= end_datetime_utc} |
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| 267 | |||
| 268 | |||
| 269 | ######################################################################################################################## |
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| 270 | # Get peak types of tariff by energy category |
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| 271 | # peak types: toppeak, onpeak, midpeak, offpeak |
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| 272 | ######################################################################################################################## |
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| 273 | 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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| 274 | # todo: validate parameters |
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| 275 | if cost_center_id is None: |
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| 276 | return dict() |
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| 277 | |||
| 278 | start_datetime_utc = start_datetime_utc.replace(tzinfo=None) |
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| 279 | end_datetime_utc = end_datetime_utc.replace(tzinfo=None) |
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| 280 | |||
| 281 | # get timezone offset in minutes, this value will be returned to client |
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| 282 | timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
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| 283 | if config.utc_offset[0] == '-': |
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| 284 | timezone_offset = -timezone_offset |
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| 285 | |||
| 286 | tariff_dict = collections.OrderedDict() |
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| 287 | |||
| 288 | cnx = None |
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| 289 | cursor = None |
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| 290 | try: |
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| 291 | cnx = mysql.connector.connect(**config.myems_system_db) |
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| 292 | cursor = cnx.cursor() |
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| 293 | query_tariffs = (" SELECT t.id, t.valid_from_datetime_utc, t.valid_through_datetime_utc " |
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| 294 | " FROM tbl_tariffs t, tbl_cost_centers_tariffs cct " |
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| 295 | " WHERE t.energy_category_id = %s AND " |
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| 296 | " t.id = cct.tariff_id AND " |
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| 297 | " cct.cost_center_id = %s AND " |
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| 298 | " t.valid_through_datetime_utc >= %s AND " |
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| 299 | " t.valid_from_datetime_utc <= %s " |
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| 300 | " ORDER BY t.valid_from_datetime_utc ") |
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| 301 | cursor.execute(query_tariffs, (energy_category_id, cost_center_id, start_datetime_utc, end_datetime_utc,)) |
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| 302 | rows_tariffs = cursor.fetchall() |
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| 303 | except Exception as e: |
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| 304 | print(str(e)) |
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| 305 | if cnx: |
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| 306 | cnx.disconnect() |
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| 307 | if cursor: |
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| 308 | cursor.close() |
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| 309 | return dict() |
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| 310 | |||
| 311 | if rows_tariffs is None or len(rows_tariffs) == 0: |
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| 312 | if cursor: |
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| 313 | cursor.close() |
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| 314 | if cnx: |
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| 315 | cnx.disconnect() |
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| 316 | return dict() |
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| 317 | |||
| 318 | for row in rows_tariffs: |
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| 319 | tariff_dict[row[0]] = {'valid_from_datetime_utc': row[1], |
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| 320 | 'valid_through_datetime_utc': row[2], |
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| 321 | 'rates': list()} |
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| 322 | |||
| 323 | try: |
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| 324 | query_timeofuse_tariffs = (" SELECT tariff_id, start_time_of_day, end_time_of_day, peak_type " |
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| 325 | " FROM tbl_tariffs_timeofuses " |
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| 326 | " WHERE tariff_id IN ( " + ', '.join(map(str, tariff_dict.keys())) + ")" |
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| 327 | " ORDER BY tariff_id, start_time_of_day ") |
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| 328 | cursor.execute(query_timeofuse_tariffs, ) |
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| 329 | rows_timeofuse_tariffs = cursor.fetchall() |
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| 330 | except Exception as e: |
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| 331 | print(str(e)) |
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| 332 | if cnx: |
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| 333 | cnx.disconnect() |
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| 334 | if cursor: |
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| 335 | cursor.close() |
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| 336 | return dict() |
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| 337 | |||
| 338 | if cursor: |
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| 339 | cursor.close() |
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| 340 | if cnx: |
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| 341 | cnx.disconnect() |
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| 342 | |||
| 343 | if rows_timeofuse_tariffs is None or len(rows_timeofuse_tariffs) == 0: |
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| 344 | return dict() |
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| 345 | |||
| 346 | for row in rows_timeofuse_tariffs: |
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| 347 | tariff_dict[row[0]]['rates'].append({'start_time_of_day': row[1], |
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| 348 | 'end_time_of_day': row[2], |
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| 349 | 'peak_type': row[3]}) |
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| 350 | |||
| 351 | result = dict() |
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| 352 | for tariff_id, tariff_value in tariff_dict.items(): |
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| 353 | current_datetime_utc = tariff_value['valid_from_datetime_utc'] |
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| 354 | while current_datetime_utc < tariff_value['valid_through_datetime_utc']: |
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| 355 | for rate in tariff_value['rates']: |
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| 356 | current_datetime_local = current_datetime_utc + timedelta(minutes=timezone_offset) |
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| 357 | seconds_since_midnight = (current_datetime_local - |
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| 358 | current_datetime_local.replace(hour=0, |
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| 359 | second=0, |
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| 360 | microsecond=0, |
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| 361 | tzinfo=None)).total_seconds() |
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| 362 | if rate['start_time_of_day'].total_seconds() <= \ |
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| 363 | seconds_since_midnight < rate['end_time_of_day'].total_seconds(): |
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| 364 | result[current_datetime_utc] = rate['peak_type'] |
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| 365 | break |
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| 366 | |||
| 367 | # start from the next time slot |
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| 368 | current_datetime_utc += timedelta(minutes=config.minutes_to_count) |
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| 369 | |||
| 370 | return {k: v for k, v in result.items() if start_datetime_utc <= k <= end_datetime_utc} |
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| 371 | |||
| 372 | |||
| 373 | ######################################################################################################################## |
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| 374 | # Averaging calculator of hourly data by period |
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| 375 | # rows_hourly: list of (start_datetime_utc, actual_value), should belong to one energy_category_id |
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| 376 | # start_datetime_utc: start datetime in utc |
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| 377 | # end_datetime_utc: end datetime in utc |
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| 378 | # period_type: one of the following period types, 'hourly', 'daily', 'monthly' and 'yearly' |
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| 379 | # Returns: periodically data of average and maximum |
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| 380 | # Note: this procedure doesn't work with multiple energy categories |
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| 381 | ######################################################################################################################## |
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| 382 | def averaging_hourly_data_by_period(rows_hourly, start_datetime_utc, end_datetime_utc, period_type): |
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| 383 | # todo: validate parameters |
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| 384 | start_datetime_utc = start_datetime_utc.replace(tzinfo=None) |
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| 385 | end_datetime_utc = end_datetime_utc.replace(tzinfo=None) |
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| 386 | |||
| 387 | if period_type == "hourly": |
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| 388 | result_rows_hourly = list() |
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| 389 | # todo: add config.working_day_start_time_local |
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| 390 | # todo: add config.minutes_to_count |
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| 391 | total = Decimal(0.0) |
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| 392 | maximum = None |
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| 393 | counter = 0 |
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| 394 | current_datetime_utc = start_datetime_utc.replace(minute=0, second=0, microsecond=0, tzinfo=None) |
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| 395 | View Code Duplication | while current_datetime_utc <= end_datetime_utc: |
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| 396 | sub_total = Decimal(0.0) |
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| 397 | sub_maximum = None |
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| 398 | sub_counter = 0 |
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| 399 | for row in rows_hourly: |
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| 400 | if current_datetime_utc <= row[0] < current_datetime_utc + \ |
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| 401 | timedelta(minutes=config.minutes_to_count): |
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| 402 | sub_total += row[1] |
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| 403 | if sub_maximum is None: |
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| 404 | sub_maximum = row[1] |
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| 405 | elif sub_maximum < row[1]: |
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| 406 | sub_maximum = row[1] |
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| 407 | sub_counter += 1 |
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| 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 |
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