|
| 1 | +import logging |
| 2 | + |
| 3 | +from baseline.models import ( |
| 4 | + Community, |
| 5 | + LivelihoodActivity, |
| 6 | + LivelihoodStrategy, |
| 7 | + LivelihoodZoneBaseline, |
| 8 | + WealthGroup, |
| 9 | +) |
| 10 | +from ingestion.decorators import register |
| 11 | +from ingestion.importers import Importer |
| 12 | +from ingestion.models import SpreadsheetLocation |
| 13 | + |
| 14 | +logger = logging.getLogger(__name__) |
| 15 | + |
| 16 | + |
| 17 | +@register |
| 18 | +class LivelihoodZoneBaselineImporter(Importer): |
| 19 | + # Management command load_from_bss calls this importer's ingest() for a pre-saved LivelihoodZoneBaseline instance. |
| 20 | + |
| 21 | + class Meta: |
| 22 | + model = LivelihoodZoneBaseline |
| 23 | + dependent_model_fields = [ |
| 24 | + "livelihood_strategies", |
| 25 | + "communities", |
| 26 | + ] |
| 27 | + |
| 28 | + |
| 29 | +@register |
| 30 | +class LivelihoodStrategyImporter(Importer): |
| 31 | + class Meta: |
| 32 | + model = LivelihoodStrategy |
| 33 | + fields = [ |
| 34 | + "product", |
| 35 | + "strategy_type", |
| 36 | + "season", |
| 37 | + "unit_of_measure", |
| 38 | + "currency", |
| 39 | + "additional_identifier", |
| 40 | + ] |
| 41 | + parent_model_fields = [ |
| 42 | + "livelihood_zone_baseline", |
| 43 | + ] |
| 44 | + dependent_model_fields = [ |
| 45 | + "livelihoodactivity", |
| 46 | + ] |
| 47 | + |
| 48 | + def ingest_product( |
| 49 | + self, |
| 50 | + field_def, |
| 51 | + successful_mappings, |
| 52 | + failed_mappings, |
| 53 | + parent_instances, |
| 54 | + bss_value_extractors, |
| 55 | + ): |
| 56 | + # Scan down column A of the three Data sheets looking for a product alias. |
| 57 | + for sheet_name in ("Data", "Data2", "Data3"): |
| 58 | + row_count, column_count = parent_instances[LivelihoodZoneBaseline][0].load_sheet(sheet_name).shape |
| 59 | + for row in range(7, min(row_count, 3000)): |
| 60 | + new_spreadsheet_location, successful_mappings, failed_mappings = self.attempt_load_from_cell( |
| 61 | + parent_instances=parent_instances, |
| 62 | + field_def=field_def, |
| 63 | + find_field=False, |
| 64 | + sheet_name=sheet_name, |
| 65 | + column=0, # col A |
| 66 | + row=row, |
| 67 | + bss_value_extractors=bss_value_extractors, |
| 68 | + successful_mappings=successful_mappings, |
| 69 | + failed_mappings=failed_mappings, |
| 70 | + ) |
| 71 | + return successful_mappings, failed_mappings, parent_instances |
| 72 | + |
| 73 | + def ingest_strategy_type( |
| 74 | + self, |
| 75 | + field_def, |
| 76 | + successful_mappings, |
| 77 | + failed_mappings, |
| 78 | + parent_instances, |
| 79 | + bss_value_extractors, |
| 80 | + ): |
| 81 | + # The products must already have been mapped, so we know how many LSes we have and which rows they're on. |
| 82 | + # This finds the strategy_types (~12), then generates a strategy_type SpreadsheetLocation per LS (~90). |
| 83 | + |
| 84 | + # 1. Identify SpreadsheetLocation of each strategy_type found in the BSS (approx 12): |
| 85 | + strategy_type_spreadsheet_locations = [] |
| 86 | + for sheet_name in ("Data", "Data2", "Data3"): |
| 87 | + row_count, column_count = parent_instances[LivelihoodZoneBaseline][0].load_sheet(sheet_name).shape |
| 88 | + for row in range(10, min(row_count, 3000 + 1)): |
| 89 | + new_spreadsheet_location, successful_mappings, failed_mappings = self.attempt_load_from_cell( |
| 90 | + parent_instances=parent_instances, |
| 91 | + field_def=field_def, |
| 92 | + find_field=False, |
| 93 | + sheet_name=sheet_name, |
| 94 | + column=0, # all in column A |
| 95 | + row=row, |
| 96 | + bss_value_extractors=bss_value_extractors, |
| 97 | + successful_mappings=successful_mappings, |
| 98 | + failed_mappings=failed_mappings, |
| 99 | + ) |
| 100 | + if new_spreadsheet_location: |
| 101 | + strategy_type_spreadsheet_locations.append(new_spreadsheet_location) |
| 102 | + |
| 103 | + # 2. Generate a strategy_type SpreadsheetLocation per LivelihoodStrategy in the BSS (approx 90): |
| 104 | + # The first row of each LivelihoodStrategy has the product in col A, so we use product mappings to iterate LS. |
| 105 | + sl_per_livelihood_strategy = [] |
| 106 | + for instance_number, product_sl in enumerate(successful_mappings["product"]): |
| 107 | + strategy_type_sl = self.get_strategy_type_for_instance(instance_number, successful_mappings) |
| 108 | + sl_per_livelihood_strategy.append(strategy_type_sl) |
| 109 | + |
| 110 | + # 3. Clean up working data: |
| 111 | + # Grab the PKs of the SLs not attached to any LS instance for deletion later |
| 112 | + sls_to_delete = [o.pk for o in strategy_type_spreadsheet_locations] |
| 113 | + |
| 114 | + # Generate a new SpreadsheetLocation per LivelihoodStrategy instance |
| 115 | + for instance_number, sl in enumerate(sl_per_livelihood_strategy): |
| 116 | + sl.pk = None |
| 117 | + sl.id = None |
| 118 | + sl.instance_number = instance_number |
| 119 | + sl.save() |
| 120 | + |
| 121 | + # Delete the strategy_type SpreadsheetLocations not attached to any LivelihoodStrategy instance |
| 122 | + SpreadsheetLocation.objects.filter(pk__in=sls_to_delete).delete() |
| 123 | + |
| 124 | + return successful_mappings, failed_mappings, parent_instances |
| 125 | + |
| 126 | + @staticmethod |
| 127 | + def get_strategy_type_for_instance(instance_number, successful_mappings): |
| 128 | + # The strategy type for a given LivelihoodStrategy instance is the one closest above it in the BSS: |
| 129 | + product = successful_mappings["product"][instance_number] |
| 130 | + strategy_types = successful_mappings["strategy_type"] |
| 131 | + st_index = 0 |
| 132 | + while st_index < len(strategy_types) and ( |
| 133 | + product.sheet_name != strategy_types[st_index].sheet_name or product.row < strategy_types[st_index].row |
| 134 | + ): |
| 135 | + st_index += 1 |
| 136 | + return strategy_types[st_index] |
| 137 | + |
| 138 | + |
| 139 | +@register |
| 140 | +class CommunityImporter(Importer): |
| 141 | + class Meta: |
| 142 | + model = Community |
| 143 | + fields = [ |
| 144 | + "name", |
| 145 | + "full_name", |
| 146 | + "code", |
| 147 | + "interview_number", |
| 148 | + ] |
| 149 | + dependent_model_fields = [ |
| 150 | + "wealth_groups", |
| 151 | + ] |
| 152 | + |
| 153 | + def ingest_name( |
| 154 | + self, |
| 155 | + field_def, |
| 156 | + successful_mappings, |
| 157 | + failed_mappings, |
| 158 | + parent_instances, |
| 159 | + bss_value_extractors, |
| 160 | + ): |
| 161 | + # The community/village names are on row 4, repeated for each wealth category (on row 2). |
| 162 | + # So scan across the first wealth category accumulating village names. |
| 163 | + sheet_name = "Data" |
| 164 | + sheet = parent_instances[LivelihoodZoneBaseline][0].load_sheet(sheet_name) |
| 165 | + row = 4 |
| 166 | + column = 1 |
| 167 | + first_wc = sheet.iloc[2, column] |
| 168 | + while first_wc == sheet.iloc[2, column]: |
| 169 | + new_spreadsheet_location, successful_mappings, failed_mappings = self.attempt_load_from_cell( |
| 170 | + parent_instances=parent_instances, |
| 171 | + field_def=field_def, |
| 172 | + find_field=False, |
| 173 | + sheet_name=sheet_name, |
| 174 | + column=column, |
| 175 | + row=row, |
| 176 | + bss_value_extractors=bss_value_extractors, |
| 177 | + successful_mappings=successful_mappings, |
| 178 | + failed_mappings=failed_mappings, |
| 179 | + ) |
| 180 | + column += 1 |
| 181 | + return successful_mappings, failed_mappings, parent_instances |
| 182 | + |
| 183 | + def ingest_full_name( |
| 184 | + self, |
| 185 | + field_def, |
| 186 | + successful_mappings, |
| 187 | + failed_mappings, |
| 188 | + parent_instances, |
| 189 | + bss_value_extractors, |
| 190 | + ): |
| 191 | + # 1. Scan across Data sheet row 3 loading district names |
| 192 | + sheet_name = "Data" |
| 193 | + row = 3 |
| 194 | + for name_loc in successful_mappings["name"]: |
| 195 | + new_spreadsheet_location, successful_mappings, failed_mappings = self.attempt_load_from_cell( |
| 196 | + parent_instances=parent_instances, |
| 197 | + field_def=field_def, |
| 198 | + find_field=False, |
| 199 | + sheet_name=sheet_name, |
| 200 | + column=name_loc.column, |
| 201 | + row=row, |
| 202 | + bss_value_extractors=bss_value_extractors, |
| 203 | + successful_mappings=successful_mappings, |
| 204 | + failed_mappings=failed_mappings, |
| 205 | + ) |
| 206 | + # 2. Prefix the village names |
| 207 | + for i, full_name_loc in enumerate(successful_mappings[field_def.name]): |
| 208 | + village_loc = successful_mappings["name"][i] |
| 209 | + full_name_loc.mapped_value = ", ".join((village_loc.mapped_value, full_name_loc.mapped_value)) |
| 210 | + return successful_mappings, failed_mappings, parent_instances |
| 211 | + |
| 212 | + def ingest_code( |
| 213 | + self, |
| 214 | + field_def, |
| 215 | + successful_mappings, |
| 216 | + failed_mappings, |
| 217 | + parent_instances, |
| 218 | + bss_value_extractors, |
| 219 | + ): |
| 220 | + # 1. Populate in the same way as the name field |
| 221 | + successful_mappings, failed_mappings, parent_instances = self.ingest_name( |
| 222 | + field_def, |
| 223 | + successful_mappings, |
| 224 | + failed_mappings, |
| 225 | + parent_instances, |
| 226 | + bss_value_extractors, |
| 227 | + ) |
| 228 | + # 2. Convert to lower case |
| 229 | + for loc in successful_mappings[field_def.name]: |
| 230 | + loc.mapped_value = loc.mapped_value.lower() |
| 231 | + return successful_mappings, failed_mappings, parent_instances |
| 232 | + |
| 233 | + |
| 234 | +@register |
| 235 | +class LivelihoodActivityImporter(Importer): |
| 236 | + class Meta: |
| 237 | + model = LivelihoodActivity |
| 238 | + fields = [ |
| 239 | + "scenario", |
| 240 | + "wealth_group", |
| 241 | + "quantity_produced", |
| 242 | + "quantity_purchased", |
| 243 | + "quantity_sold", |
| 244 | + "quantity_other_uses", |
| 245 | + "quantity_consumed", |
| 246 | + "price", |
| 247 | + "income", |
| 248 | + "expenditure", |
| 249 | + "kcals_consumed", |
| 250 | + "percentage_kcals", |
| 251 | + "household_labor_provider", |
| 252 | + "strategy_type", |
| 253 | + ] |
| 254 | + parent_model_fields = [ |
| 255 | + "livelihood_strategy", |
| 256 | + "livelihood_zone_baseline", |
| 257 | + ] |
| 258 | + dependent_model_fields = [ |
| 259 | + "milkproduction", |
| 260 | + "butterproduction", |
| 261 | + "meatproduction", |
| 262 | + "livestocksale", |
| 263 | + "cropproduction", |
| 264 | + "foodpurchase", |
| 265 | + "paymentinkind", |
| 266 | + "reliefgiftother", |
| 267 | + "fishing", |
| 268 | + "wildfoodgathering", |
| 269 | + "othercashincome", |
| 270 | + "otherpurchase", |
| 271 | + ] |
| 272 | + |
| 273 | + def ingest_quantity_produced( |
| 274 | + self, |
| 275 | + field_def, |
| 276 | + successful_mappings, |
| 277 | + failed_mappings, |
| 278 | + parent_instances, |
| 279 | + bss_value_extractors, |
| 280 | + ): |
| 281 | + # The product is specified on the first row of each LS. |
| 282 | + # Use them to iterate over each LS's rows, looking for quantity_produced field name aliases |
| 283 | + for strategy_i, strategy_loc in enumerate(parent_instances[LivelihoodStrategy]["product"]): |
| 284 | + sheet = parent_instances[LivelihoodZoneBaseline][0].load_sheet(strategy_loc.sheet_name) |
| 285 | + row_count, column_count = sheet.shape |
| 286 | + row = strategy_loc.row |
| 287 | + |
| 288 | + # If there's a subsequent LS on the same sheet, scan col A until that row, otherwise scan to bottom |
| 289 | + if ( |
| 290 | + strategy_i + 1 < len(parent_instances[LivelihoodStrategy]["product"]) |
| 291 | + and parent_instances[LivelihoodStrategy]["product"][strategy_i + 1].sheet_name |
| 292 | + == strategy_loc.sheet_name |
| 293 | + ): |
| 294 | + last_row = parent_instances[LivelihoodStrategy]["product"][strategy_i + 1].row - 1 |
| 295 | + else: |
| 296 | + last_row = min(row_count, 3000) |
| 297 | + |
| 298 | + # locate the field in col A |
| 299 | + while row < last_row: |
| 300 | + new_spreadsheet_location, successful_mappings, failed_mappings = self.attempt_load_from_cell( |
| 301 | + parent_instances=parent_instances, |
| 302 | + field_def=field_def, |
| 303 | + find_field=True, |
| 304 | + sheet_name=strategy_loc.sheet_name, |
| 305 | + column=0, |
| 306 | + row=row, |
| 307 | + bss_value_extractors=bss_value_extractors, |
| 308 | + successful_mappings=successful_mappings, |
| 309 | + failed_mappings=failed_mappings, |
| 310 | + ) |
| 311 | + # When we locate a quantity_produced field alias in col A, stop looking and load the values |
| 312 | + if new_spreadsheet_location: |
| 313 | + break |
| 314 | + row += 1 |
| 315 | + |
| 316 | + # get the value on row `row` for each LA. |
| 317 | + # There is 1 WealthGroup per WealthCategory per Community, plus 1 WG per WealthCategory with no Community |
| 318 | + for wg_i, wg_loc in enumerate(parent_instances[WealthGroup]["wealth_category"]): |
| 319 | + new_spreadsheet_location, successful_mappings, failed_mappings = self.attempt_load_from_cell( |
| 320 | + parent_instances=parent_instances, |
| 321 | + field_def=field_def, |
| 322 | + find_field=False, |
| 323 | + sheet_name=strategy_loc.sheet_name, |
| 324 | + column=wg_loc.column, |
| 325 | + row=row, |
| 326 | + bss_value_extractors=bss_value_extractors, |
| 327 | + successful_mappings=successful_mappings, |
| 328 | + failed_mappings=failed_mappings, |
| 329 | + ) |
0 commit comments