Conditions | 99 |
Total Lines | 490 |
Code Lines | 368 |
Lines | 490 |
Ratio | 100 % |
Changes | 0 |
Small methods make your code easier to understand, in particular if combined with a good name. Besides, if your method is small, finding a good name is usually much easier.
For example, if you find yourself adding comments to a method's body, this is usually a good sign to extract the commented part to a new method, and use the comment as a starting point when coming up with a good name for this new method.
Commonly applied refactorings include:
If many parameters/temporary variables are present:
Complex classes like reports.combinedequipmentcost.Reporting.on_get() 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 | import falcon |
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31 | @staticmethod |
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32 | def on_get(req, resp): |
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33 | print(req.params) |
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34 | combined_equipment_id = req.params.get('combinedequipmentid') |
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35 | period_type = req.params.get('periodtype') |
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36 | base_start_datetime_local = req.params.get('baseperiodstartdatetime') |
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37 | base_end_datetime_local = req.params.get('baseperiodenddatetime') |
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38 | reporting_start_datetime_local = req.params.get('reportingperiodstartdatetime') |
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39 | reporting_end_datetime_local = req.params.get('reportingperiodenddatetime') |
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40 | |||
41 | ################################################################################################################ |
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42 | # Step 1: valid parameters |
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43 | ################################################################################################################ |
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44 | if combined_equipment_id is None: |
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45 | raise falcon.HTTPError(falcon.HTTP_400, |
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46 | title='API.BAD_REQUEST', |
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47 | description='API.INVALID_COMBINED_EQUIPMENT_ID') |
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48 | else: |
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49 | combined_equipment_id = str.strip(combined_equipment_id) |
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50 | if not combined_equipment_id.isdigit() or int(combined_equipment_id) <= 0: |
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51 | raise falcon.HTTPError(falcon.HTTP_400, |
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52 | title='API.BAD_REQUEST', |
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53 | description='API.INVALID_COMBINED_EQUIPMENT_ID') |
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54 | |||
55 | if period_type is None: |
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56 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') |
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57 | else: |
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58 | period_type = str.strip(period_type) |
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59 | if period_type not in ['hourly', 'daily', 'monthly', 'yearly']: |
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60 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE') |
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61 | |||
62 | timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6]) |
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63 | if config.utc_offset[0] == '-': |
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64 | timezone_offset = -timezone_offset |
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65 | |||
66 | base_start_datetime_utc = None |
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67 | if base_start_datetime_local is not None and len(str.strip(base_start_datetime_local)) > 0: |
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68 | base_start_datetime_local = str.strip(base_start_datetime_local) |
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69 | try: |
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70 | base_start_datetime_utc = datetime.strptime(base_start_datetime_local, |
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71 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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72 | timedelta(minutes=timezone_offset) |
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73 | except ValueError: |
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74 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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75 | description="API.INVALID_BASE_PERIOD_START_DATETIME") |
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76 | |||
77 | base_end_datetime_utc = None |
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78 | if base_end_datetime_local is not None and len(str.strip(base_end_datetime_local)) > 0: |
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79 | base_end_datetime_local = str.strip(base_end_datetime_local) |
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80 | try: |
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81 | base_end_datetime_utc = datetime.strptime(base_end_datetime_local, |
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82 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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83 | timedelta(minutes=timezone_offset) |
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84 | except ValueError: |
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85 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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86 | description="API.INVALID_BASE_PERIOD_END_DATETIME") |
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87 | |||
88 | if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \ |
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89 | base_start_datetime_utc >= base_end_datetime_utc: |
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90 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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91 | description='API.INVALID_BASE_PERIOD_END_DATETIME') |
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92 | |||
93 | if reporting_start_datetime_local is None: |
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94 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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95 | description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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96 | else: |
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97 | reporting_start_datetime_local = str.strip(reporting_start_datetime_local) |
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98 | try: |
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99 | reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local, |
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100 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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101 | timedelta(minutes=timezone_offset) |
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102 | except ValueError: |
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103 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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104 | description="API.INVALID_REPORTING_PERIOD_START_DATETIME") |
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105 | |||
106 | if reporting_end_datetime_local is None: |
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107 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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108 | description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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109 | else: |
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110 | reporting_end_datetime_local = str.strip(reporting_end_datetime_local) |
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111 | try: |
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112 | reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local, |
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113 | '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \ |
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114 | timedelta(minutes=timezone_offset) |
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115 | except ValueError: |
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116 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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117 | description="API.INVALID_REPORTING_PERIOD_END_DATETIME") |
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118 | |||
119 | if reporting_start_datetime_utc >= reporting_end_datetime_utc: |
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120 | raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', |
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121 | description='API.INVALID_REPORTING_PERIOD_END_DATETIME') |
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122 | |||
123 | ################################################################################################################ |
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124 | # Step 2: query the combined equipment |
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125 | ################################################################################################################ |
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126 | cnx_system = mysql.connector.connect(**config.myems_system_db) |
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127 | cursor_system = cnx_system.cursor() |
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128 | |||
129 | cnx_billing = mysql.connector.connect(**config.myems_billing_db) |
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130 | cursor_billing = cnx_billing.cursor() |
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131 | |||
132 | cnx_historical = mysql.connector.connect(**config.myems_historical_db) |
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133 | cursor_historical = cnx_historical.cursor() |
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134 | |||
135 | cursor_system.execute(" SELECT id, name, cost_center_id " |
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136 | " FROM tbl_combined_equipments " |
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137 | " WHERE id = %s ", (combined_equipment_id,)) |
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138 | row_combined_equipment = cursor_system.fetchone() |
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139 | if row_combined_equipment is None: |
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140 | if cursor_system: |
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141 | cursor_system.close() |
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142 | if cnx_system: |
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143 | cnx_system.disconnect() |
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144 | |||
145 | if cursor_billing: |
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146 | cursor_billing.close() |
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147 | if cnx_billing: |
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148 | cnx_billing.disconnect() |
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149 | |||
150 | if cnx_historical: |
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151 | cnx_historical.close() |
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152 | if cursor_historical: |
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153 | cursor_historical.disconnect() |
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154 | raise falcon.HTTPError(falcon.HTTP_404, |
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155 | title='API.NOT_FOUND', |
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156 | description='API.COMBINED_EQUIPMENT_NOT_FOUND') |
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157 | |||
158 | combined_equipment = dict() |
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159 | combined_equipment['id'] = row_combined_equipment[0] |
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160 | combined_equipment['name'] = row_combined_equipment[1] |
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161 | combined_equipment['cost_center_id'] = row_combined_equipment[2] |
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162 | |||
163 | ################################################################################################################ |
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164 | # Step 3: query energy categories |
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165 | ################################################################################################################ |
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166 | energy_category_set = set() |
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167 | # query energy categories in base period |
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168 | cursor_billing.execute(" SELECT DISTINCT(energy_category_id) " |
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169 | " FROM tbl_combined_equipment_input_category_hourly " |
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170 | " WHERE combined_equipment_id = %s " |
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171 | " AND start_datetime_utc >= %s " |
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172 | " AND start_datetime_utc < %s ", |
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173 | (combined_equipment['id'], base_start_datetime_utc, base_end_datetime_utc)) |
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174 | rows_energy_categories = cursor_billing.fetchall() |
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175 | if rows_energy_categories is not None or len(rows_energy_categories) > 0: |
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176 | for row_energy_category in rows_energy_categories: |
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177 | energy_category_set.add(row_energy_category[0]) |
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178 | |||
179 | # query energy categories in reporting period |
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180 | cursor_billing.execute(" SELECT DISTINCT(energy_category_id) " |
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181 | " FROM tbl_combined_equipment_input_category_hourly " |
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182 | " WHERE combined_equipment_id = %s " |
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183 | " AND start_datetime_utc >= %s " |
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184 | " AND start_datetime_utc < %s ", |
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185 | (combined_equipment['id'], reporting_start_datetime_utc, reporting_end_datetime_utc)) |
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186 | rows_energy_categories = cursor_billing.fetchall() |
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187 | if rows_energy_categories is not None or len(rows_energy_categories) > 0: |
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188 | for row_energy_category in rows_energy_categories: |
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189 | energy_category_set.add(row_energy_category[0]) |
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190 | |||
191 | # query all energy categories in base period and reporting period |
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192 | cursor_system.execute(" SELECT id, name, unit_of_measure, kgce, kgco2e " |
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193 | " FROM tbl_energy_categories " |
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194 | " ORDER BY id ", ) |
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195 | rows_energy_categories = cursor_system.fetchall() |
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196 | if rows_energy_categories is None or len(rows_energy_categories) == 0: |
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197 | if cursor_system: |
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198 | cursor_system.close() |
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199 | if cnx_system: |
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200 | cnx_system.disconnect() |
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201 | |||
202 | if cursor_billing: |
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203 | cursor_billing.close() |
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204 | if cnx_billing: |
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205 | cnx_billing.disconnect() |
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206 | |||
207 | if cnx_historical: |
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208 | cnx_historical.close() |
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209 | if cursor_historical: |
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210 | cursor_historical.disconnect() |
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211 | raise falcon.HTTPError(falcon.HTTP_404, |
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212 | title='API.NOT_FOUND', |
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213 | description='API.ENERGY_CATEGORY_NOT_FOUND') |
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214 | energy_category_dict = dict() |
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215 | for row_energy_category in rows_energy_categories: |
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216 | if row_energy_category[0] in energy_category_set: |
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217 | energy_category_dict[row_energy_category[0]] = {"name": row_energy_category[1], |
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218 | "unit_of_measure": row_energy_category[2], |
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219 | "kgce": row_energy_category[3], |
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220 | "kgco2e": row_energy_category[4]} |
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221 | |||
222 | ################################################################################################################ |
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223 | # Step 4: query associated points |
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224 | ################################################################################################################ |
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225 | point_list = list() |
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226 | cursor_system.execute(" SELECT p.id, p.name, p.units, p.object_type " |
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227 | " FROM tbl_combined_equipments e, tbl_combined_equipments_parameters ep, tbl_points p " |
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228 | " WHERE e.id = %s AND e.id = ep.combined_equipment_id AND ep.parameter_type = 'point' " |
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229 | " AND ep.point_id = p.id " |
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230 | " ORDER BY p.id ", (combined_equipment['id'],)) |
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231 | rows_points = cursor_system.fetchall() |
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232 | if rows_points is not None and len(rows_points) > 0: |
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233 | for row in rows_points: |
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234 | point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]}) |
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235 | |||
236 | ################################################################################################################ |
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237 | # Step 5: query base period energy cost |
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238 | ################################################################################################################ |
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239 | base = dict() |
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240 | if energy_category_set is not None and len(energy_category_set) > 0: |
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241 | for energy_category_id in energy_category_set: |
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242 | base[energy_category_id] = dict() |
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243 | base[energy_category_id]['timestamps'] = list() |
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244 | base[energy_category_id]['values'] = list() |
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245 | base[energy_category_id]['subtotal'] = Decimal(0.0) |
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246 | |||
247 | cursor_billing.execute(" SELECT start_datetime_utc, actual_value " |
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248 | " FROM tbl_combined_equipment_input_category_hourly " |
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249 | " WHERE combined_equipment_id = %s " |
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250 | " AND energy_category_id = %s " |
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251 | " AND start_datetime_utc >= %s " |
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252 | " AND start_datetime_utc < %s " |
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253 | " ORDER BY start_datetime_utc ", |
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254 | (combined_equipment['id'], |
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255 | energy_category_id, |
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256 | base_start_datetime_utc, |
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257 | base_end_datetime_utc)) |
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258 | rows_combined_equipment_hourly = cursor_billing.fetchall() |
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259 | |||
260 | rows_combined_equipment_periodically = \ |
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261 | utilities.aggregate_hourly_data_by_period(rows_combined_equipment_hourly, |
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262 | base_start_datetime_utc, |
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263 | base_end_datetime_utc, |
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264 | period_type) |
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265 | for row_combined_equipment_periodically in rows_combined_equipment_periodically: |
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266 | current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ |
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267 | timedelta(minutes=timezone_offset) |
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268 | if period_type == 'hourly': |
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269 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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270 | elif period_type == 'daily': |
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271 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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272 | elif period_type == 'monthly': |
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273 | current_datetime = current_datetime_local.strftime('%Y-%m') |
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274 | elif period_type == 'yearly': |
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275 | current_datetime = current_datetime_local.strftime('%Y') |
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276 | |||
277 | actual_value = Decimal(0.0) if row_combined_equipment_periodically[1] is None \ |
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278 | else row_combined_equipment_periodically[1] |
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279 | base[energy_category_id]['timestamps'].append(current_datetime) |
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280 | base[energy_category_id]['values'].append(actual_value) |
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281 | base[energy_category_id]['subtotal'] += actual_value |
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282 | |||
283 | ################################################################################################################ |
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284 | # Step 6: query reporting period energy cost |
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285 | ################################################################################################################ |
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286 | reporting = dict() |
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287 | if energy_category_set is not None and len(energy_category_set) > 0: |
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288 | for energy_category_id in energy_category_set: |
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289 | reporting[energy_category_id] = dict() |
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290 | reporting[energy_category_id]['timestamps'] = list() |
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291 | reporting[energy_category_id]['values'] = list() |
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292 | reporting[energy_category_id]['subtotal'] = Decimal(0.0) |
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293 | reporting[energy_category_id]['toppeak'] = Decimal(0.0) |
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294 | reporting[energy_category_id]['onpeak'] = Decimal(0.0) |
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295 | reporting[energy_category_id]['midpeak'] = Decimal(0.0) |
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296 | reporting[energy_category_id]['offpeak'] = Decimal(0.0) |
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297 | |||
298 | cursor_billing.execute(" SELECT start_datetime_utc, actual_value " |
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299 | " FROM tbl_combined_equipment_input_category_hourly " |
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300 | " WHERE combined_equipment_id = %s " |
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301 | " AND energy_category_id = %s " |
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302 | " AND start_datetime_utc >= %s " |
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303 | " AND start_datetime_utc < %s " |
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304 | " ORDER BY start_datetime_utc ", |
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305 | (combined_equipment['id'], |
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306 | energy_category_id, |
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307 | reporting_start_datetime_utc, |
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308 | reporting_end_datetime_utc)) |
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309 | rows_combined_equipment_hourly = cursor_billing.fetchall() |
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310 | |||
311 | rows_combined_equipment_periodically = \ |
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312 | utilities.aggregate_hourly_data_by_period(rows_combined_equipment_hourly, |
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313 | reporting_start_datetime_utc, |
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314 | reporting_end_datetime_utc, |
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315 | period_type) |
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316 | for row_combined_equipment_periodically in rows_combined_equipment_periodically: |
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317 | current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \ |
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318 | timedelta(minutes=timezone_offset) |
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319 | if period_type == 'hourly': |
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320 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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321 | elif period_type == 'daily': |
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322 | current_datetime = current_datetime_local.strftime('%Y-%m-%d') |
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323 | elif period_type == 'monthly': |
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324 | current_datetime = current_datetime_local.strftime('%Y-%m') |
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325 | elif period_type == 'yearly': |
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326 | current_datetime = current_datetime_local.strftime('%Y') |
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327 | |||
328 | actual_value = Decimal(0.0) if row_combined_equipment_periodically[1] is None \ |
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329 | else row_combined_equipment_periodically[1] |
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330 | reporting[energy_category_id]['timestamps'].append(current_datetime) |
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331 | reporting[energy_category_id]['values'].append(actual_value) |
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332 | reporting[energy_category_id]['subtotal'] += actual_value |
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333 | |||
334 | energy_category_tariff_dict = \ |
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335 | utilities.get_energy_category_peak_types(combined_equipment['cost_center_id'], |
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336 | energy_category_id, |
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337 | reporting_start_datetime_utc, |
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338 | reporting_end_datetime_utc) |
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339 | for row in rows_combined_equipment_hourly: |
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340 | peak_type = energy_category_tariff_dict.get(row[0], None) |
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341 | if peak_type == 'toppeak': |
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342 | reporting[energy_category_id]['toppeak'] += row[1] |
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343 | elif peak_type == 'onpeak': |
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344 | reporting[energy_category_id]['onpeak'] += row[1] |
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345 | elif peak_type == 'midpeak': |
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346 | reporting[energy_category_id]['midpeak'] += row[1] |
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347 | elif peak_type == 'offpeak': |
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348 | reporting[energy_category_id]['offpeak'] += row[1] |
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349 | |||
350 | ################################################################################################################ |
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351 | # Step 7: query tariff data |
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352 | ################################################################################################################ |
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353 | parameters_data = dict() |
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354 | parameters_data['names'] = list() |
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355 | parameters_data['timestamps'] = list() |
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356 | parameters_data['values'] = list() |
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357 | if energy_category_set is not None and len(energy_category_set) > 0: |
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358 | for energy_category_id in energy_category_set: |
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359 | energy_category_tariff_dict = \ |
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360 | utilities.get_energy_category_tariffs(combined_equipment['cost_center_id'], |
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361 | energy_category_id, |
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362 | reporting_start_datetime_utc, |
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363 | reporting_end_datetime_utc) |
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364 | tariff_timestamp_list = list() |
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365 | tariff_value_list = list() |
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366 | for k, v in energy_category_tariff_dict.items(): |
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367 | # convert k from utc to local |
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368 | k = k + timedelta(minutes=timezone_offset) |
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369 | tariff_timestamp_list.append(k.isoformat()[0:19][0:19]) |
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370 | tariff_value_list.append(v) |
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371 | |||
372 | parameters_data['names'].append('TARIFF-' + energy_category_dict[energy_category_id]['name']) |
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373 | parameters_data['timestamps'].append(tariff_timestamp_list) |
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374 | parameters_data['values'].append(tariff_value_list) |
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375 | |||
376 | ################################################################################################################ |
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377 | # Step 8: query associated points data |
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378 | ################################################################################################################ |
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379 | for point in point_list: |
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380 | point_values = [] |
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381 | point_timestamps = [] |
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382 | if point['object_type'] == 'ANALOG_VALUE': |
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383 | query = (" SELECT utc_date_time, actual_value " |
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384 | " FROM tbl_analog_value " |
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385 | " WHERE point_id = %s " |
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386 | " AND utc_date_time BETWEEN %s AND %s " |
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387 | " ORDER BY utc_date_time ") |
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388 | cursor_historical.execute(query, (point['id'], |
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389 | reporting_start_datetime_utc, |
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390 | reporting_end_datetime_utc)) |
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391 | rows = cursor_historical.fetchall() |
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392 | |||
393 | if rows is not None and len(rows) > 0: |
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394 | for row in rows: |
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395 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
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396 | timedelta(minutes=timezone_offset) |
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397 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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398 | point_timestamps.append(current_datetime) |
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399 | point_values.append(row[1]) |
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400 | |||
401 | elif point['object_type'] == 'ENERGY_VALUE': |
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402 | query = (" SELECT utc_date_time, actual_value " |
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403 | " FROM tbl_energy_value " |
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404 | " WHERE point_id = %s " |
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405 | " AND utc_date_time BETWEEN %s AND %s " |
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406 | " ORDER BY utc_date_time ") |
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407 | cursor_historical.execute(query, (point['id'], |
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408 | reporting_start_datetime_utc, |
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409 | reporting_end_datetime_utc)) |
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410 | rows = cursor_historical.fetchall() |
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411 | |||
412 | if rows is not None and len(rows) > 0: |
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413 | for row in rows: |
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414 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
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415 | timedelta(minutes=timezone_offset) |
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416 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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417 | point_timestamps.append(current_datetime) |
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418 | point_values.append(row[1]) |
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419 | elif point['object_type'] == 'DIGITAL_VALUE': |
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420 | query = (" SELECT utc_date_time, actual_value " |
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421 | " FROM tbl_digital_value " |
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422 | " WHERE point_id = %s " |
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423 | " AND utc_date_time BETWEEN %s AND %s ") |
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424 | cursor_historical.execute(query, (point['id'], |
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425 | reporting_start_datetime_utc, |
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426 | reporting_end_datetime_utc)) |
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427 | rows = cursor_historical.fetchall() |
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428 | |||
429 | if rows is not None and len(rows) > 0: |
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430 | for row in rows: |
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431 | current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \ |
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432 | timedelta(minutes=timezone_offset) |
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433 | current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S') |
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434 | point_timestamps.append(current_datetime) |
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435 | point_values.append(row[1]) |
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436 | |||
437 | parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')') |
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438 | parameters_data['timestamps'].append(point_timestamps) |
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439 | parameters_data['values'].append(point_values) |
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440 | |||
441 | ################################################################################################################ |
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442 | # Step 9: construct the report |
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443 | ################################################################################################################ |
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444 | if cursor_system: |
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445 | cursor_system.close() |
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446 | if cnx_system: |
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447 | cnx_system.disconnect() |
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448 | |||
449 | if cursor_billing: |
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450 | cursor_billing.close() |
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451 | if cnx_billing: |
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452 | cnx_billing.disconnect() |
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453 | |||
454 | result = dict() |
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455 | |||
456 | result['combined_equipment'] = dict() |
||
457 | result['combined_equipment']['name'] = combined_equipment['name'] |
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458 | |||
459 | result['base_period'] = dict() |
||
460 | result['base_period']['names'] = list() |
||
461 | result['base_period']['units'] = list() |
||
462 | result['base_period']['timestamps'] = list() |
||
463 | result['base_period']['values'] = list() |
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464 | result['base_period']['subtotals'] = list() |
||
465 | result['base_period']['total'] = Decimal(0.0) |
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466 | if energy_category_set is not None and len(energy_category_set) > 0: |
||
467 | for energy_category_id in energy_category_set: |
||
468 | result['base_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
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469 | result['base_period']['units'].append(config.currency_unit) |
||
470 | result['base_period']['timestamps'].append(base[energy_category_id]['timestamps']) |
||
471 | result['base_period']['values'].append(base[energy_category_id]['values']) |
||
472 | result['base_period']['subtotals'].append(base[energy_category_id]['subtotal']) |
||
473 | result['base_period']['total'] += base[energy_category_id]['subtotal'] |
||
474 | |||
475 | result['reporting_period'] = dict() |
||
476 | result['reporting_period']['names'] = list() |
||
477 | result['reporting_period']['energy_category_ids'] = list() |
||
478 | result['reporting_period']['units'] = list() |
||
479 | result['reporting_period']['timestamps'] = list() |
||
480 | result['reporting_period']['values'] = list() |
||
481 | result['reporting_period']['subtotals'] = list() |
||
482 | result['reporting_period']['toppeaks'] = list() |
||
483 | result['reporting_period']['onpeaks'] = list() |
||
484 | result['reporting_period']['midpeaks'] = list() |
||
485 | result['reporting_period']['offpeaks'] = list() |
||
486 | result['reporting_period']['increment_rates'] = list() |
||
487 | result['reporting_period']['total'] = Decimal(0.0) |
||
488 | result['reporting_period']['total_increment_rate'] = Decimal(0.0) |
||
489 | result['reporting_period']['total_unit'] = config.currency_unit |
||
490 | |||
491 | if energy_category_set is not None and len(energy_category_set) > 0: |
||
492 | for energy_category_id in energy_category_set: |
||
493 | result['reporting_period']['names'].append(energy_category_dict[energy_category_id]['name']) |
||
494 | result['reporting_period']['energy_category_ids'].append(energy_category_id) |
||
495 | result['reporting_period']['units'].append(config.currency_unit) |
||
496 | result['reporting_period']['timestamps'].append(reporting[energy_category_id]['timestamps']) |
||
497 | result['reporting_period']['values'].append(reporting[energy_category_id]['values']) |
||
498 | result['reporting_period']['subtotals'].append(reporting[energy_category_id]['subtotal']) |
||
499 | result['reporting_period']['toppeaks'].append(reporting[energy_category_id]['toppeak']) |
||
500 | result['reporting_period']['onpeaks'].append(reporting[energy_category_id]['onpeak']) |
||
501 | result['reporting_period']['midpeaks'].append(reporting[energy_category_id]['midpeak']) |
||
502 | result['reporting_period']['offpeaks'].append(reporting[energy_category_id]['offpeak']) |
||
503 | result['reporting_period']['increment_rates'].append( |
||
504 | (reporting[energy_category_id]['subtotal'] - base[energy_category_id]['subtotal']) / |
||
505 | base[energy_category_id]['subtotal'] |
||
506 | if base[energy_category_id]['subtotal'] > 0.0 else None) |
||
507 | result['reporting_period']['total'] += reporting[energy_category_id]['subtotal'] |
||
508 | |||
509 | result['reporting_period']['total_increment_rate'] = \ |
||
510 | (result['reporting_period']['total'] - result['base_period']['total']) / \ |
||
511 | result['base_period']['total'] \ |
||
512 | if result['base_period']['total'] > Decimal(0.0) else None |
||
513 | |||
514 | result['parameters'] = { |
||
515 | "names": parameters_data['names'], |
||
516 | "timestamps": parameters_data['timestamps'], |
||
517 | "values": parameters_data['values'] |
||
518 | } |
||
519 | |||
520 | resp.body = json.dumps(result) |
||
521 |