+1 -1

.gitignore

reviewed

··· 1 1 build/ 2 2 .lock* 3 3 .clangd 4 4 - __pycache__ 4 4 + scripts/__pycache__/

+1

requirements.txt

reviewed

··· 3 3 pandas 4 4 requests 5 5 pyarrow 6 6 + timezonefinder

+3 -1

run.sh

reviewed

··· 43 43 install_project 44 44 ;; 45 45 debug) 46 46 - echo "Running debug (build and install)..." 46 46 + echo "Running debug (build, install, and tail logs)..." 47 47 build_project 48 48 install_project 49 49 + # Stream verbose emulator logs for live debugging 50 50 + rebble logs --emulator basalt -v 49 51 ;; 50 52 *) 51 53 echo "Usage: ./run.sh {generate|build|install|debug}"

+71 -28

scripts/generate_airport_tz_list.py

reviewed

··· 26 26 from tz_common import find_dst_transitions as _find_dst_transitions 27 27 from bs4 import BeautifulSoup # type: ignore 28 28 import airportsdata 29 29 + from timezonefinder import TimezoneFinder 29 30 import pandas as pd 30 31 31 32 # --------------------------------------------------------------------------- ··· 117 118 """ 118 119 year = datetime.now(timezone.utc).year 119 120 airport_db = airportsdata.load("IATA") 121 121 + 120 122 # Ensure unique HTML airport entries by IATA code 121 123 seen_iatas: set[str] = set() 122 124 unique_airports: List[Tuple[str, str]] = [] ··· 130 132 if 'iata' in df_all.columns: 131 133 df_all = df_all.drop(columns=['iata']) 132 134 df_all = df_all.reset_index().rename(columns={'index': 'iata'}) 135 135 + # Recompute tz field from lat/lon to correct misclassified zones _before_ we 136 136 + # derive any offset‑related columns (important for DUT / America/Adak etc.) 137 137 + tf = TimezoneFinder() 138 138 + df_all['tz'] = df_all.apply( 139 139 + lambda row: tf.timezone_at(lat=row.get('lat'), lng=row.get('lon')) or row.get('tz'), 140 140 + axis=1, 141 141 + ) 142 142 + 133 143 # Merge OurAirports classification 134 144 try: 135 145 oa = pd.read_csv("https://ourairports.com/data/airports.csv", usecols=["iata_code","type","scheduled_service"]) # type: ignore ··· 143 153 traffic_dict = traffic_counts.to_dict() 144 154 # Map route hits using apply to ensure a Series 145 155 df_all['route_hits'] = df_all['iata'].apply(lambda x: traffic_dict.get(x, 0)).astype(int) 146 146 - # Compute standard offset seconds for each record 156 156 + # Compute standard offset seconds for each record (now that tz is fixed) 147 157 df_all['std_offset_s'] = df_all['tz'].apply(lambda tz: _find_dst_transitions(tz, year)[0]) 148 158 149 159 # Fallback selector for a given std_offset ··· 192 202 std_s, dst_s, start_ts, end_ts = _find_dst_transitions(tz_name, year) 193 203 key = (std_s, dst_s, start_ts, end_ts) 194 204 if key not in full_buckets: 195 195 - full_buckets[key] = { 'std': std_s, 'dst': dst_s, 'start': start_ts, 'end': end_ts } 205 205 + full_buckets[key] = { 206 206 + 'std': std_s, 207 207 + 'dst': dst_s, 208 208 + 'start': start_ts, 209 209 + 'end': end_ts, 210 210 + 'tz_names': [tz_name], 211 211 + } 196 212 group_keys.setdefault(std_s, []).append(key) 213 213 + else: 214 214 + full_buckets[key]['tz_names'].append(tz_name) 197 215 198 216 # 2) Collect codes from HTML for each std_offset (popular timezones) 199 217 group_codes: Dict[int, List[str]] = {} ··· 216 234 if not group_codes.get(std_s): 217 235 group_codes[std_s] = _fallback_codes(std_s) 218 236 219 219 - # 4) Assign popular codes to their actual DST buckets, then fallback for empty 237 237 + # 4) Assign popular & fallback codes to their actual DST buckets 220 238 # initialize codes list for each bucket 221 221 - for key, meta in full_buckets.items(): 239 239 + for bucket_key, meta in full_buckets.items(): 222 240 meta['codes'] = [] 223 223 - # populate HTML-based codes into their real tz variant buckets 241 241 + used_codes: set[str] = set() 242 242 + 243 243 + def _assign_to_bucket(iata_code: str): 244 244 + if iata_code in used_codes: 245 245 + return False 246 246 + rec = airport_db.get(iata_code) 247 247 + if rec and rec.get('tz'): 248 248 + std2, dst2, st2, ed2 = _find_dst_transitions(rec['tz'], year) 249 249 + key = (std2, dst2, st2, ed2) 250 250 + if key in full_buckets: 251 251 + full_buckets[key]['codes'].append(iata_code) 252 252 + used_codes.add(iata_code) 253 253 + return True 254 254 + return False 255 255 + 224 256 for std_s, codes in group_codes.items(): 225 257 for iata in codes: 226 226 - rec = airport_db.get(iata) 227 227 - if rec and rec.get('tz'): 228 228 - std2, dst2, st2, ed2 = _find_dst_transitions(rec['tz'], year) 229 229 - bucket_key = (std2, dst2, st2, ed2) 230 230 - if bucket_key in full_buckets: 231 231 - full_buckets[bucket_key]['codes'].append(iata) 258 258 + _assign_to_bucket(iata) 259 259 + 232 260 # fallback for buckets still empty: only populate the first empty bucket per std-offset 233 261 for std_s, keys in group_keys.items(): 234 234 - # track HTML-derived codes for this std-offset 235 262 assigned = set(group_codes.get(std_s, [])) 236 236 - # prepare a one-time fallback candidate list, filtered of already assigned 237 237 - fallback_candidates = [c for c in _fallback_codes(std_s) if c not in assigned] 238 238 - fallback_used = False 263 263 + fallback_candidates = [c for c in group_codes.get(std_s, []) if c not in used_codes] 264 264 + # track if we've used fallback for this std-offset 265 265 + used = False 239 266 for bucket_key in keys: 240 267 codes_list = full_buckets[bucket_key].get('codes', []) 241 241 - if not codes_list and not fallback_used and fallback_candidates: 242 242 - # assign up to max_bucket fallback codes to first empty bucket 243 243 - if max_bucket > 0: 244 244 - codes_list = fallback_candidates[:max_bucket] 268 268 + if not codes_list and not used: 269 269 + # pick first unassigned fallback candidates 270 270 + fallback_pool = [c for c in group_codes.get(std_s, []) if c not in used_codes] 271 271 + for candidate in fallback_pool: 272 272 + if _assign_to_bucket(candidate): 273 273 + codes_list = [candidate] 274 274 + break 245 275 else: 246 246 - codes_list = fallback_candidates[:] 247 247 - fallback_used = True 248 248 - # cap any list to max_bucket if needed 249 249 - if codes_list and max_bucket > 0: 250 250 - codes_list = codes_list[:max_bucket] 276 276 + codes_list = [] 277 277 + used = True 251 278 full_buckets[bucket_key]['codes'] = codes_list 252 252 - # record assigned codes so we don't reuse them (though fallback is one-shot) 253 253 - assigned.update(codes_list) 279 279 + 280 280 + # FINAL safety pass: if a bucket is still empty try to grab 1 airport that 281 281 + # actually sits in *this* timezone (e.g. DUT for America/Adak). This never 282 282 + # duplicates because we consult used_codes. 283 283 + for bucket_key, meta in full_buckets.items(): 284 284 + if meta['codes']: 285 285 + continue 286 286 + tz_names = meta.get('tz_names', []) 287 287 + if not tz_names: 288 288 + continue 289 289 + seg = df_all[df_all['tz'].isin(tz_names)].sort_values('route_hits', ascending=False) 290 290 + for code in seg['iata']: 291 291 + if _assign_to_bucket(code): 292 292 + meta['codes'] = [code] 293 293 + break 254 294 255 295 # build ordered bucket list 256 296 buckets_list = [ ··· 263 303 264 304 # 5) Build flat pool and offsets 265 305 code_pool = [] 306 306 + seen_for_pool: set[str] = set() 266 307 for b in buckets_list: 308 308 + unique_codes = [c for c in b.get('codes', []) if c not in seen_for_pool] 267 309 b['offset'] = len(code_pool) 268 268 - b['count'] = len(b.get('codes', [])) 269 269 - code_pool.extend(b.get('codes', [])) 310 310 + b['count'] = len(unique_codes) 311 311 + code_pool.extend(unique_codes) 312 312 + seen_for_pool.update(unique_codes) 270 313 271 314 # Build name pool parallel to code_pool 272 315 name_pool = []

+85 -58

src/c/airport_tz_list.c

reviewed

··· 12 12 "MKK", 13 13 "JHM", 14 14 "LNY", 15 15 + "AKB", 15 16 "NHV", 17 17 + "GMR", 16 18 "ANC", 17 19 "LAX", 18 20 "SFO", ··· 41 43 "STL", 42 44 "BNA", 43 45 "AUS", 46 46 + "IPC", 47 47 + "CUN", 48 48 + "HAV", 44 49 "ATL", 45 50 "JFK", 46 51 "YYZ", ··· 71 76 "VCP", 72 77 "SDU", 73 78 "POA", 79 79 + "FEN", 80 80 + "FSP", 74 81 "GOH", 75 82 "SID", 76 83 "PDL", 77 84 "TER", 85 85 + "DKR", 78 86 "LHR", 79 87 "LGW", 80 88 "DUB", ··· 85 93 "EDI", 86 94 "LPA", 87 95 "BHX", 96 96 + "CMN", 97 97 + "ALG", 88 98 "CDG", 89 99 "AMS", 90 100 "FRA", ··· 98 108 "JNB", 99 109 "CPT", 100 110 "TLV", 111 111 + "BEY", 112 112 + "BZY", 101 113 "ATH", 102 114 "HEL", 103 115 "OTP", ··· 210 222 "HBA", 211 223 "LDH", 212 224 "VLI", 225 225 + "NLK", 213 226 "NAN", 214 227 "PKC", 215 228 "AKL", ··· 234 247 "Molokai", 235 248 "Kapalua", 236 249 "Lanai", 250 250 + "Atka", 237 251 "Nuku Hiva", 252 252 + "Totegegie", 238 253 "Ted Stevens Anchorage", 239 254 "Los Angeles", 240 255 "San Francisco", ··· 263 278 "St Louis Lambert", 264 279 "Nashville", 265 280 "Austin-Bergstrom", 281 281 + "Mataveri", 282 282 + "Cancun", 283 283 + "Jose Marti", 266 284 "Hartsfield - Jackson Atlanta", 267 285 "John F Kennedy", 268 286 "Toronto Pearson", ··· 293 311 "Viracopos", 294 312 "Santos Dumont", 295 313 "Salgado Filho", 314 314 + "Fernando de Noronha", 315 315 + "St Pierre", 296 316 "Godthaab / Nuuk", 297 317 "Amilcar Cabral", 298 318 "João Paulo II", 299 319 "Lajes Field", 320 320 + "Leopold Sedar Senghor", 300 321 "London Heathrow", 301 322 "London Gatwick", 302 323 "Dublin", ··· 307 328 "Edinburgh", 308 329 "Gran Canaria", 309 330 "Birmingham", 331 331 + "Mohammed V", 332 332 + "Houari Boumediene", 310 333 "Charles de Gaulle", 311 334 "Amsterdam Airport Schiphol", 312 335 "Frankfurt am Main", ··· 320 343 "O. R. Tambo", 321 344 "Cape Town", 322 345 "Ben Gurion", 346 346 + "Beirut Rafic Hariri", 347 347 + "Balti", 323 348 "Eleftherios Venizelos", 324 349 "Helsinki Vantaa", 325 350 "Henri Coanda", ··· 432 457 "Hobart", 433 458 "Lord Howe Island", 434 459 "Port Vila Bauerfield", 460 460 + "Norfolk Island", 435 461 "Nadi", 436 462 "Yelizovo", 437 463 "Auckland", ··· 459 485 static const TzInfo airport_tz_list[] = { 460 486 { -11.00f, -11.00f, 0LL, 0LL, 0, 1 }, 461 487 { -10.00f, -10.00f, 0LL, 0LL, 1, 7 }, 462 462 - { -10.00f, -9.00f, 1741489200LL, 1762048800LL, 8, 0 }, 463 463 - { -9.50f, -9.50f, 0LL, 0LL, 8, 1 }, 464 464 - { -9.00f, -9.00f, 0LL, 0LL, 9, 0 }, 465 465 - { -9.00f, -8.00f, 1741489200LL, 1762048800LL, 9, 1 }, 466 466 - { -8.00f, -7.00f, 1741489200LL, 1762048800LL, 10, 10 }, 467 467 - { -7.00f, -7.00f, 0LL, 0LL, 20, 1 }, 468 468 - { -7.00f, -6.00f, 1741489200LL, 1762048800LL, 21, 6 }, 469 469 - { -6.00f, -6.00f, 0LL, 0LL, 27, 1 }, 470 470 - { -6.00f, -5.00f, 1741489200LL, 1762048800LL, 28, 9 }, 471 471 - { -6.00f, -5.00f, 1757199600LL, 1743890400LL, 37, 0 }, 472 472 - { -5.00f, -5.00f, 0LL, 0LL, 37, 0 }, 473 473 - { -5.00f, -4.00f, 1741482000LL, 1762045200LL, 37, 0 }, 474 474 - { -5.00f, -4.00f, 1741489200LL, 1762048800LL, 37, 10 }, 475 475 - { -4.00f, -4.00f, 0LL, 0LL, 47, 7 }, 476 476 - { -4.00f, -3.00f, 1741489200LL, 1762048800LL, 54, 1 }, 477 477 - { -4.00f, -3.00f, 1757206800LL, 1743897600LL, 55, 1 }, 478 478 - { -3.50f, -2.50f, 1741489200LL, 1762048800LL, 56, 1 }, 479 479 - { -3.00f, -3.00f, 0LL, 0LL, 57, 10 }, 480 480 - { -3.00f, -2.00f, 1741489200LL, 1762048800LL, 67, 0 }, 481 481 - { -2.00f, -1.00f, 1743292800LL, 1761436800LL, 67, 1 }, 482 482 - { -1.00f, -1.00f, 0LL, 0LL, 68, 1 }, 483 483 - { -1.00f, 0.00f, 1743296400LL, 1761440400LL, 69, 2 }, 484 484 - { 0.00f, 0.00f, 0LL, 0LL, 71, 0 }, 485 485 - { 0.00f, 1.00f, 1743300000LL, 1761444000LL, 71, 10 }, 486 486 - { 0.00f, 1.00f, 1743908400LL, 1740279600LL, 81, 0 }, 487 487 - { 1.00f, 1.00f, 0LL, 0LL, 81, 0 }, 488 488 - { 1.00f, 2.00f, 1743303600LL, 1761447600LL, 81, 10 }, 489 489 - { 2.00f, 2.00f, 0LL, 0LL, 91, 2 }, 490 490 - { 2.00f, 3.00f, 1743130800LL, 1761444000LL, 93, 1 }, 491 491 - { 2.00f, 3.00f, 1743296400LL, 1761436800LL, 94, 0 }, 492 492 - { 2.00f, 3.00f, 1743303600LL, 1761447600LL, 94, 0 }, 493 493 - { 2.00f, 3.00f, 1743307200LL, 1761451200LL, 94, 6 }, 494 494 - { 2.00f, 3.00f, 1745542800LL, 1761868800LL, 100, 1 }, 495 495 - { 3.00f, 3.00f, 0LL, 0LL, 101, 10 }, 496 496 - { 3.50f, 3.50f, 0LL, 0LL, 111, 10 }, 497 497 - { 4.00f, 4.00f, 0LL, 0LL, 121, 10 }, 498 498 - { 4.50f, 4.50f, 0LL, 0LL, 131, 1 }, 499 499 - { 5.00f, 5.00f, 0LL, 0LL, 132, 10 }, 500 500 - { 5.50f, 5.50f, 0LL, 0LL, 142, 10 }, 501 501 - { 5.75f, 5.75f, 0LL, 0LL, 152, 1 }, 502 502 - { 6.00f, 6.00f, 0LL, 0LL, 153, 1 }, 503 503 - { 6.50f, 6.50f, 0LL, 0LL, 154, 2 }, 504 504 - { 7.00f, 7.00f, 0LL, 0LL, 156, 10 }, 505 505 - { 8.00f, 8.00f, 0LL, 0LL, 166, 10 }, 506 506 - { 8.75f, 8.75f, 0LL, 0LL, 176, 1 }, 507 507 - { 9.00f, 9.00f, 0LL, 0LL, 177, 10 }, 508 508 - { 9.50f, 9.50f, 0LL, 0LL, 187, 3 }, 509 509 - { 9.50f, 10.50f, 1759633200LL, 1743908400LL, 190, 4 }, 510 510 - { 10.00f, 10.00f, 0LL, 0LL, 194, 6 }, 511 511 - { 10.00f, 11.00f, 1759633200LL, 1743908400LL, 200, 4 }, 512 512 - { 10.50f, 11.00f, 1759633200LL, 1743904800LL, 204, 1 }, 513 513 - { 11.00f, 11.00f, 0LL, 0LL, 205, 1 }, 514 514 - { 11.00f, 12.00f, 1759633200LL, 1743908400LL, 206, 0 }, 515 515 - { 12.00f, 12.00f, 0LL, 0LL, 206, 2 }, 516 516 - { 12.00f, 13.00f, 1759028400LL, 1743908400LL, 208, 8 }, 517 517 - { 12.75f, 13.75f, 1759032000LL, 1743912000LL, 216, 1 }, 518 518 - { 13.00f, 13.00f, 0LL, 0LL, 217, 1 }, 519 519 - { 14.00f, 14.00f, 0LL, 0LL, 218, 1 }, 488 488 + { -10.00f, -9.00f, 1741489200LL, 1762048800LL, 8, 1 }, 489 489 + { -9.50f, -9.50f, 0LL, 0LL, 9, 1 }, 490 490 + { -9.00f, -9.00f, 0LL, 0LL, 10, 1 }, 491 491 + { -9.00f, -8.00f, 1741489200LL, 1762048800LL, 11, 1 }, 492 492 + { -8.00f, -7.00f, 1741489200LL, 1762048800LL, 12, 10 }, 493 493 + { -7.00f, -7.00f, 0LL, 0LL, 22, 1 }, 494 494 + { -7.00f, -6.00f, 1741489200LL, 1762048800LL, 23, 6 }, 495 495 + { -6.00f, -6.00f, 0LL, 0LL, 29, 1 }, 496 496 + { -6.00f, -5.00f, 1741489200LL, 1762048800LL, 30, 9 }, 497 497 + { -6.00f, -5.00f, 1757199600LL, 1743890400LL, 39, 1 }, 498 498 + { -5.00f, -5.00f, 0LL, 0LL, 40, 1 }, 499 499 + { -5.00f, -4.00f, 1741482000LL, 1762045200LL, 41, 1 }, 500 500 + { -5.00f, -4.00f, 1741489200LL, 1762048800LL, 42, 10 }, 501 501 + { -4.00f, -4.00f, 0LL, 0LL, 52, 7 }, 502 502 + { -4.00f, -3.00f, 1741489200LL, 1762048800LL, 59, 1 }, 503 503 + { -4.00f, -3.00f, 1757206800LL, 1743897600LL, 60, 1 }, 504 504 + { -3.50f, -2.50f, 1741489200LL, 1762048800LL, 61, 1 }, 505 505 + { -3.00f, -3.00f, 0LL, 0LL, 62, 11 }, 506 506 + { -3.00f, -2.00f, 1741489200LL, 1762048800LL, 73, 1 }, 507 507 + { -2.00f, -2.00f, 0LL, 0LL, 74, 0 }, 508 508 + { -2.00f, -1.00f, 1743292800LL, 1761436800LL, 74, 1 }, 509 509 + { -1.00f, -1.00f, 0LL, 0LL, 75, 1 }, 510 510 + { -1.00f, 0.00f, 1743296400LL, 1761440400LL, 76, 2 }, 511 511 + { 0.00f, 0.00f, 0LL, 0LL, 78, 1 }, 512 512 + { 0.00f, 1.00f, 1743300000LL, 1761444000LL, 79, 10 }, 513 513 + { 0.00f, 1.00f, 1743908400LL, 1740279600LL, 89, 1 }, 514 514 + { 1.00f, 1.00f, 0LL, 0LL, 90, 1 }, 515 515 + { 1.00f, 2.00f, 1743303600LL, 1761447600LL, 91, 10 }, 516 516 + { 2.00f, 2.00f, 0LL, 0LL, 101, 2 }, 517 517 + { 2.00f, 3.00f, 1743130800LL, 1761444000LL, 103, 1 }, 518 518 + { 2.00f, 3.00f, 1743296400LL, 1761436800LL, 104, 1 }, 519 519 + { 2.00f, 3.00f, 1743303600LL, 1761447600LL, 105, 1 }, 520 520 + { 2.00f, 3.00f, 1743307200LL, 1761451200LL, 106, 6 }, 521 521 + { 2.00f, 3.00f, 1745542800LL, 1761868800LL, 112, 1 }, 522 522 + { 3.00f, 3.00f, 0LL, 0LL, 113, 10 }, 523 523 + { 3.50f, 3.50f, 0LL, 0LL, 123, 10 }, 524 524 + { 4.00f, 4.00f, 0LL, 0LL, 133, 10 }, 525 525 + { 4.50f, 4.50f, 0LL, 0LL, 143, 1 }, 526 526 + { 5.00f, 5.00f, 0LL, 0LL, 144, 10 }, 527 527 + { 5.50f, 5.50f, 0LL, 0LL, 154, 10 }, 528 528 + { 5.75f, 5.75f, 0LL, 0LL, 164, 1 }, 529 529 + { 6.00f, 6.00f, 0LL, 0LL, 165, 1 }, 530 530 + { 6.50f, 6.50f, 0LL, 0LL, 166, 2 }, 531 531 + { 7.00f, 7.00f, 0LL, 0LL, 168, 10 }, 532 532 + { 8.00f, 8.00f, 0LL, 0LL, 178, 10 }, 533 533 + { 8.75f, 8.75f, 0LL, 0LL, 188, 1 }, 534 534 + { 9.00f, 9.00f, 0LL, 0LL, 189, 10 }, 535 535 + { 9.50f, 9.50f, 0LL, 0LL, 199, 3 }, 536 536 + { 9.50f, 10.50f, 1759633200LL, 1743908400LL, 202, 4 }, 537 537 + { 10.00f, 10.00f, 0LL, 0LL, 206, 6 }, 538 538 + { 10.00f, 11.00f, 1759633200LL, 1743908400LL, 212, 4 }, 539 539 + { 10.50f, 11.00f, 1759633200LL, 1743904800LL, 216, 1 }, 540 540 + { 11.00f, 11.00f, 0LL, 0LL, 217, 1 }, 541 541 + { 11.00f, 12.00f, 1759633200LL, 1743908400LL, 218, 1 }, 542 542 + { 12.00f, 12.00f, 0LL, 0LL, 219, 2 }, 543 543 + { 12.00f, 13.00f, 1759028400LL, 1743908400LL, 221, 8 }, 544 544 + { 12.75f, 13.75f, 1759032000LL, 1743912000LL, 229, 1 }, 545 545 + { 13.00f, 13.00f, 0LL, 0LL, 230, 1 }, 546 546 + { 14.00f, 14.00f, 0LL, 0LL, 231, 1 }, 520 547 }; 521 548 522 549 #define AIRPORT_TZ_LIST_COUNT (sizeof(airport_tz_list)/sizeof(airport_tz_list[0]))