text:
crash when chain reorg

version: v1.3.7.2
atomicals  | INFO:electrumx:ElectrumX server starting
atomicals  | INFO:electrumx:logging level: INFO
atomicals  | INFO:Controller:Python version: 3.10.11 (main, May  3 2023, 09:48:29) [GCC 11.2.1 20220219]
atomicals  | INFO:Controller:software version: ElectrumX 1.16.0
atomicals  | INFO:Controller:aiorpcX version: 0.22.1
atomicals  | INFO:Controller:supported protocol versions: 1.4-1.4.3
atomicals  | INFO:Controller:event loop policy: <uvloop.EventLoopPolicy object at 0x7fdb98937d60>
atomicals  | INFO:Controller:reorg limit is 200 blocks
atomicals  | INFO:Daemon:daemon #1 at host.docker.internal:8332/ (current)
atomicals  | INFO:DB:switching current directory to /app/data
atomicals  | INFO:DB:using leveldb for DB backend
atomicals  | INFO:DB:opened UTXO DB (for sync: True)
atomicals  | INFO:DB:UTXO DB version: 8
atomicals  | INFO:DB:coin: Bitcoin
atomicals  | INFO:DB:network: mainnet
atomicals  | INFO:DB:height: 823,226
atomicals  | INFO:DB:tip: 0000000000000000000365e705dbbea406f6e383f510d400fa23e40eae71e056
atomicals  | INFO:DB:tx count: 943,688,366
atomicals  | INFO:DB:atomical count: 140,809
atomicals  | INFO:DB:flushing DB cache at 1,200 MB
atomicals  | INFO:History:history DB version: 1
atomicals  | INFO:History:flush count: 4,871
atomicals  | INFO:Prefetcher:catching up to daemon height 823,261 (35 blocks behind)
atomicals  | INFO:BlockProcessor:chain reorg detected
atomicals  | INFO:BlockProcessor:chain was reorganised replacing 1 block at heights 823,226-823,226
atomicals  | INFO:BlockProcessor:read 1 blocks from disk
atomicals  | INFO:BlockProcessor:backup_txs m=5848
atomicals  | INFO:BlockProcessor:atomicals_undo_info_map={}
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 5718 - count 0 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 5718 1669d42e672f376113b09b34f4046d83a9a829fb7d0fe49a48e2f43dd4d8ea0f000000009d304417368fdcebf51b7e2d2f5c4b7acbd9013d1e170dbebc7aae7f125f3d9200000000ca85d4e89209f9c7477a54c5edffeccbec37a11df7dbe9be3606f551b736055b20a79dc7200afef402fb37e8030000000000000000cf553d3800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 5588 - count 1 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 5588 f1d00c8b690cd6564b5369eecc738476f8e7c2de74d53ee460f50e712fa21ca400000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf025910000000086a3fbbf0fad05291d424ca34809494edc83d4080bd10843b99fe23807e6f0efdc1110e318c182990ca188204e000000000000000030e4373800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 5458 - count 2 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 5458 b3faf1ad79dbbd091e0f50f2997d8535394b166022cccb1873f040e23407c07d000000009d304417368fdcebf51b7e2d2f5c4b7acbd9013d1e170dbebc7aae7f125f3d9200000000cd9c692d3cbaecaed41e58fcf50aa4d221af3fc26acde07e70f84308c914f69796cf57f43bc95760e8d8f8e8030000000000000000cc573d3800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 5328 - count 3 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 5328 5b006345b98be3c1845b87daca7be56eb9cc2662eeae91acdb87bac1e5e9eba9000000009d304417368fdcebf51b7e2d2f5c4b7acbd9013d1e170dbebc7aae7f125f3d920000000037442d9a58501754d65c96d05f63ef5fb6f2067395b48a9625a864b67e576a17ff7fcb2916ff4112a07ad6e8030000000000000000c9df3d3800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 5198 - count 4 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 5198 0bd2e7ac0f644d5dc391312b5daa6fff6dfc5d819ee0613f64fe35ffa4dd1cf9000000009d304417368fdcebf51b7e2d2f5c4b7acbd9013d1e170dbebc7aae7f125f3d92000000005f0b10b75aa092be3bd7fc469e5e54d14d29b34192ea791aa604d819365e5d2d58a47d747cfcc3d359ea2fe803000000000000000039263d3800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 5068 - count 5 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 5068 1551c1d9024b8f2a5e8acd4bcfafdeff6a9ce9a386c8d24c5ffd2f2e4616efe700000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000000d4b65477da43dbd6103706a7644a88803b083e59487073e4761e26e5d9a0a17a093f3e24f185925a2c22d204e0000000000000000b681373800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 4938 - count 6 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 4938 e0b6dd34acdfafc2e8f52b21a510b4ed946399e43d68b7d00356af5507d2ad8e00000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e0000000000000000dd51383800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 4808 - count 7 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 4808 7c57c97ac5de32cbbb0e4bf836bd26ed6805f33b201884d7497662ceb1297e3800000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e00000000000000000ce5363800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 4678 - count 8 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 4678 fe6d361f5af076cdc4affdd49bb9064e694e5e81f7cce37a733a619c972f897400000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e00000000000000000ae5363800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 4548 - count 9 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 4548 20b0fff7999c15c1c5bb0ffcbc17a4a7e1dc83bf0e05dd3b32f815428fc4b6b800000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e0000000000000000deb9363800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 4418 - count 10 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 4418 4ab46d1f7489c565fbac5d9dc0aadf58cf388dddef00c9c10ea8a9e3cf91cae600000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e0000000000000000dcb9363800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 4288 - count 11 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 4288 a80b8165202ac689833878031a39760191eca50af1aec22acf21271da83178d400000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e0000000000000000dab9363800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 4158 - count 12 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 4158 0ba8b5c2bab22e9e0c5b683b6cae6822cababe2fbf767483d790727a52081ec300000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf0259100000000a18fbf0f1b383b7d846a778de3d8ea79b7bf2ecd2dc69ab7d92a40a4d2818eefda952dd29151d8a2f8b74a204e00000000000000002dbb363800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 4028 - count 13 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 4028 4d9009951ad7264789bb74014b792db1f442580f0fe6fe3a38d891f947f4064b00000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf0259100000000a18fbf0f1b383b7d846a778de3d8ea79b7bf2ecd2dc69ab7d92a40a4d2818eefda952dd29151d8a2f8b74a204e0000000000000000e751363800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 3898 - count 14 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 3898 fbe79d7ba5ce104bfa474bded62ff59ecec9e8a60f7888d047997e483d73127e00000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf0259100000000a18fbf0f1b383b7d846a778de3d8ea79b7bf2ecd2dc69ab7d92a40a4d2818eefda952dd29151d8a2f8b74a204e0000000000000000e144363800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 3768 - count 15 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 3768 ebb6ddf7625336a6557aeb3530e98d604caa4842a401881932296a7ad0fba27a00000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf0259100000000a18fbf0f1b383b7d846a778de3d8ea79b7bf2ecd2dc69ab7d92a40a4d2818eefda952dd29151d8a2f8b74a204e00000000000000007444363800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 3638 - count 16 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 3638 e5262d035a92bd3b264e78954234f8c498d1468818d470d19b9690f928508cb400000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf0259100000000a18fbf0f1b383b7d846a778de3d8ea79b7bf2ecd2dc69ab7d92a40a4d2818eefda952dd29151d8a2f8b74a204e00000000000000004244363800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 3508 - count 17 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 3508 ce8f4c2a70d048edc3009f70b62394510db602fa5bdb651167f6fc525f85a65200000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf0259100000000a18fbf0f1b383b7d846a778de3d8ea79b7bf2ecd2dc69ab7d92a40a4d2818eefda952dd29151d8a2f8b74a204e0000000000000000d325363800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 3378 - count 18 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 3378 c4f1874bf18f5fe22c5f6b31c44cda6481cfd0dbf44ef002ac97036fecea271e00000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf0259100000000a18fbf0f1b383b7d846a778de3d8ea79b7bf2ecd2dc69ab7d92a40a4d2818eefda952dd29151d8a2f8b74a204e00000000000000009925363800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 3248 - count 19 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 3248 bf4774bb02f64e9522c61f9e5a16f3abf8e0a09823dbbf1f46688c417cfa98a100000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf0259100000000a18fbf0f1b383b7d846a778de3d8ea79b7bf2ecd2dc69ab7d92a40a4d2818eefda952dd29151d8a2f8b74a204e00000000000000007425363800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 3118 - count 20 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 3118 76c8fdced9f05bd7207ca1fa60ac53d310cf4afe87ef6dbd925ffd3fd52398a6000000009d304417368fdcebf51b7e2d2f5c4b7acbd9013d1e170dbebc7aae7f125f3d92000000006c160d5af100be2b124bcde4b6c5db8d577317c72389bb6e6ccb5e49bb608785524595dae0c85b83c94bc4e803000000000000000036b33d3800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 2988 - count 21 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 2988 4d16de2d17cdffcdde1c7b3c1022a9c7af696dd3b11ee27799572438e97ea0f1000000009d304417368fdcebf51b7e2d2f5c4b7acbd9013d1e170dbebc7aae7f125f3d920000000098f978c6cbdee7849c972e03ad6629acb4f2d812d629c492ebe58dbd35a917bd5619dcdfad4b2fcbbd59f1e8030000000000000000ac4b3d3800
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 2858 - count 22 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 2858 380095bb9ee07ed5cbf36090a215457182e06a75f08efbed13b5b2d0eb80302968ab00000000908ee68352516d76f43f00296a6f91141e57e22b34ca3b2317faafdfaa37675300000000750348df7d09137e5ed2051b8061b36f60e74e7d234863b5b0783f89760c6c622c6ea1c7a3688dca4cf1f048d50000000000004b893a3700
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 2728 - count 23 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 2728 38008c888f847ce2bb87a960b095ef77f6143ecfbcc2fa2df01dae70dd4db9213a560000000041038f27e785606ca0cc1efd8e3aa912a15c72d06f359aeb05243dab2b70a856000000002541d800ca7500b2770a0c0dc18cbbe7acee5d0f3dad1cd915ad30869ae17c5e2ceb75b189b734c0149b5ae80300000000000000000a4b1e
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 2598 - count 24 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 2598 380013909169dad4f6783c2bce0d0cd518a02b8848f335ebbc90a9042abde4b87be00000000072e64078bf0c8e038f19ed5c3ea70d89a0d3638d7efa080b3295cc0c0482d0b10000000054daa08d503c2c00b9a070827948ae5345d74cb2fdb2250ef138e03d1a79d7664fcb8fa923ecf9474283f5e8030000000000000000337819
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 2468 - count 25 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 2468 38009478f3365d19f061c6a263d7742fe318d506998af1543977e5f9d6b543b2108400000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000006fdf2836d43b994f3dd524cdf6170e8bf0dfdf9d3cdea54696f3f9360469c8eb08f455f1d3428b5bf92892204e00000000000000005d5536
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 2338 - count 26 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 2338 38000b3e4860f19eb98c03166dad3e88fdfcfa8c1ec0fcf4f0f76f0df16ddf832a4c00000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000006fdf2836d43b994f3dd524cdf6170e8bf0dfdf9d3cdea54696f3f9360469c8eb08f455f1d3428b5bf92892204e00000000000000005b5536
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 2208 - count 27 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 2208 38006d5146d5ff6099c524a26ede850bdedf20c56e2fcd4af93ca42e54a458ffdc2800000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000006fdf2836d43b994f3dd524cdf6170e8bf0dfdf9d3cdea54696f3f9360469c8eb08f455f1d3428b5bf92892204e00000000000000005c5536
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 2078 - count 28 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 2078 3800ed8b53d36a949f60d8482c1fc24fdd858ea8f63288996168e0a6d56d5b36726600000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e000000000000000097de37
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 1948 - count 29 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 1948 3800ebea12193c790d433c390266d8faf6d850c3c2f9111ac9e3872477f524e3aa3200000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e000000000000000095de37
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 1818 - count 30 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 1818 380003bf9cbd53639c2e768066c201f5d47039d6268d3a0acf0e07e475c29d6be25800000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e000000000000000045de37
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 1688 - count 31 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 1688 38005f1132aaae677c7f2890001916aaa1aa782424959324998143428372600400d700000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e000000000000000043de37
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 1558 - count 32 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 1558 3800d9a07642b919b132f49f14c1b0312e86d03d4a6f3f45d85326bc4575d877618d00000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e0000000000000000b22f37
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 1428 - count 33 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 1428 3800dfcb2c7f557c1b48f7515d191be0520f70951792b6c6c42223d952d108651be200000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e00000000000000000c1a37
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 1298 - count 34 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 1298 38007a7529a734d2b03c4918dfcf2f7f4f2bd4545e39a0d3097668b498813cc3689b00000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e0000000000000000041a37
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 1168 - count 35 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 1168 3800462044380d013a638d53853e89e33c067ba4603ce6d7f275157aee63b689fba000000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e0000000000000000c00b37
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 1038 - count 36 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 1038 3800df7436b48f5acaed90e51263c092fc79b5ea1f123f57897d63f5bcca1cc0123c00000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e000000000000000052f836
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 908 - count 37 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 908 3800662fca5e1bce7704e8fa1375514a11b660e6f4c892bda8968559271c335853b200000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf02591000000002f1aca263336d3976d8a72938866d40400570d3f2c900e412fa87d072adbda03c9d2b1de67d82bcbc58662204e00000000000000004cf836
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 778 - count 38 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 778 380002833dfa23fee4217ccb974318a8700231a24e9e51730a22d8d659566f28098000000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf0259100000000933aed32c6a0855860b8bc806a1a9f619a7a60ef786262be811c3d76070d2fe200ad6dd0c02d45ee48e1e9204e000000000000000088ee35
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 648 - count 39 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 648 3800870f9189780c39b8931e6f2de878d25abc5090694f608167c397a3e82bdf076a00000000666fea477fe0892e6e337c15ed430b1a460be0aeb9621707f62593cf3bf0259100000000933aed32c6a0855860b8bc806a1a9f619a7a60ef786262be811c3d76070d2fe200ad6dd0c02d45ee48e1e9204e000000000000000086ee35
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 518 - count 40 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 518 3800825582bf860a1649aed3949216ad5121d8c43b8e6bc7f8386f43cfa157d241ab000000009d304417368fdcebf51b7e2d2f5c4b7acbd9013d1e170dbebc7aae7f125f3d92000000006c160d5af100be2b124bcde4b6c5db8d577317c72389bb6e6ccb5e49bb608785524595dae0c85b83c94bc4e80300000000000000002cc83d
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 388 - count 41 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 388 380057a024864392b5b97b57d99a0a07c0fda0a240340f4d245e34facc828f4db1ea000000009d304417368fdcebf51b7e2d2f5c4b7acbd9013d1e170dbebc7aae7f125f3d9200000000e98683d8186fb180c8b13982f2523bdcf4a6022d8f55291d13f96c293daa945577b4150253aede6187ced6e80300000000000000005e2a3d
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 258 - count 42 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 258 38002c36a372ec221577fef265053c569b7cf6d27ed905fbb3fe6f86f69b5a61e04000000000afdef5feb85029eaf1905e906aef1de6469072155198e1c524d9e8d0855162ab00000000f45e6167f7f9bf343b60966a6e8e5a8a5024f579e9d06d98154736f4d7a17f0c223f576db885a38ef5a7b9166b9f06000000000000656c3f
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len 128 - count 43 - 130
atomicals  | INFO:BlockProcessor:Reorg undo_info_item 128 38002c36a372ec221577fef265053c569b7cf6d27ed905fbb3fe6f86f69b5a61e04000000000794f82c79db8df571134d60a1c135eb555a67701bcc2753b28f7aa1dac8e39ab00000000f45e6167f7f9bf343b60966a6e8e5a8a5024f579e9d06d98154736f4d7a17f0c223f576db885a38ef5a7b9166b9f06000000000000656c3f
atomicals  | INFO:BlockProcessor:atomicals_undo_entry_len -2 - count 44 - 130
atomicals  | INFO:Prefetcher:cancelled; prefetcher stopping
atomicals  | INFO:Controller:shutting down
atomicals  | INFO:Controller:shutdown complete
atomicals  | ERROR:electrumx:ElectrumX server terminated abnormally
atomicals  | Traceback (most recent call last):
atomicals  |   File "/app/electrumx_server", line 35, in main
atomicals  |     asyncio.run(controller.run())
atomicals  |   File "/usr/local/lib/python3.10/asyncio/runners.py", line 44, in run
atomicals  |     return loop.run_until_complete(main)
atomicals  |   File "uvloop/loop.pyx", line 1517, in uvloop.loop.Loop.run_until_complete
atomicals  |   File "/app/electrumx/lib/server_base.py", line 129, in run
atomicals  |     await server_task
atomicals  |   File "/app/electrumx/lib/server_base.py", line 102, in serve
atomicals  |     await self.serve(shutdown_event)
atomicals  |   File "/app/electrumx/server/controller.py", line 134, in serve
atomicals  |     async with OldTaskGroup() as group:
atomicals  |   File "/usr/local/lib/python3.10/site-packages/aiorpcx/curio.py", line 297, in __aexit__
atomicals  |     await self.join()
atomicals  |   File "/app/electrumx/lib/util.py", line 370, in join
atomicals  |     task.result()
atomicals  |   File "/app/electrumx/server/block_processor.py", line 3580, in fetch_and_process_blocks
atomicals  |     async with OldTaskGroup() as group:
atomicals  |   File "/usr/local/lib/python3.10/site-packages/aiorpcx/curio.py", line 297, in __aexit__
atomicals  |     await self.join()
atomicals  |   File "/app/electrumx/lib/util.py", line 370, in join
atomicals  |     task.result()
atomicals  |   File "/app/electrumx/server/block_processor.py", line 3542, in _process_prefetched_blocks
atomicals  |     await self.check_and_advance_blocks(blocks)
atomicals  |   File "/app/electrumx/server/block_processor.py", line 323, in check_and_advance_blocks
atomicals  |     await self.reorg_chain()
atomicals  |   File "/app/electrumx/server/block_processor.py", line 365, in reorg_chain
atomicals  |     await self.run_in_thread_with_lock(self.backup_blocks, raw_blocks)
atomicals  |   File "/app/electrumx/server/block_processor.py", line 295, in run_in_thread_with_lock
atomicals  |     return await asyncio.shield(run_in_thread_locked())
atomicals  |   File "/app/electrumx/server/block_processor.py", line 294, in run_in_thread_locked
atomicals  |     return await run_in_thread(func, *args)
atomicals  |   File "/usr/local/lib/python3.10/site-packages/aiorpcx/curio.py", line 57, in run_in_thread
atomicals  |     return await get_event_loop().run_in_executor(None, func, *args)
atomicals  |   File "/usr/local/lib/python3.10/concurrent/futures/thread.py", line 58, in run
atomicals  |     result = self.fn(*self.args, **self.kwargs)
atomicals  |   File "/app/electrumx/server/block_processor.py", line 3130, in backup_blocks
atomicals  |     self.backup_txs(block.transactions, is_unspendable)
atomicals  |   File "/app/electrumx/server/block_processor.py", line 3303, in backup_txs
atomicals  |     assert(c >= 0)
atomicals  | AssertionError
atomicals exited with code 0

me too,do you solve is?

no, it look like undo entry length is not match exactly. is there any rollback way? i don't want to resync again.

i have re-synchronized the node. REMEMBER take snapshot periodic.

ok, thanks

We will identify the underlying problem soon.

authors: atomicals joepeak yvvw

repo: atomicals/atomicals-electrumx


text:
Update build goal to check for existing build data as well when using external builds

For external builds - Extend the build goal to also check if some Build event exists on the after sha and set the state of the goal accordingly; if not await the event data.

fixed in #29

source: gharchive/issue

authors: cdupuis ipcrm

repo: atomist/sdm-pack-build

license_type: permissive

license_source: github-api


text:
fix: onboard when the device is offline

- What I did
[Problem]

Onboarding an atSign paired to a device fails when the network is down, This prevents fetching the data from the local storage when the device is offline.

[Root Cause]

During onboarding, the "OnBoardingStatus" is determined for which the encryption public key is fetched from the cloud secondary server. When the network is not reachable, fetching of encryption public key returns an exception causing the onboard process to fail.

- How I did it
[Solution]

Added a try-catch block around the code that fetches the encryption public key from the server. Upon exception, the error is logged and "null" is returned.
Refactored the code in "_getServerEncryptionPublicKey" method as below:

Currently, the lookup verb command is used to fetch the encryption public key. On an authenticated connection, the lookup verb fails to fetch the data and returns "data:null". In this case, llookup verb is used to fetch the encryption public key. In a worst-case scenario, two calls to remote secondary are sent.
Modified the code such that If the connection is authenticated, then set the command to llookup verb, else set to command to lookup verb and run executeCommand to fetch the data.

Modified the condition to check the OnboardingStatus in the "getKeyRestorePolicy" method:

If the encryption public key is NULL on the cloud and local secondary (OR) encryption public key is NULL in cloud secondary and NOT-NULL is local secondary, then Onboarding Status is set to "Activate".
Also, if the encryption public key is NULL in cloud secondary and NOT-NULL is local secondary, then Onboarding Status is set to "SyncToServer".
Since the condition to check "SyncToSever" is the same as the condition after OR in the condition to check "Activate" the "SyncToServer" will not be returned.
Also the condition encryptionPublicKey NOT NULL in local secondary does not seem correct for "ACTIVATE", because if we generate encryption key pair only after activating the atSign. Hence removed the later part of the condition to check the "OnboardingStatus.ACTIVATE"

- How to verify it

Ran wavi app and atmosphere app with the changes and able to onboard the app.
Added a new unit test to onboard an app when remote secondary returns an exception.

- Description for the changelog

Onboard a paired atSign when the device is offline

Please test at_talk

Please test at_talk

@gkc: Sure.

@sitaram-kalluri Is this PR still reviewable, or are we going for an alternative solution?

@gkc: We are going with an alternate solution. So closing this PR.

source: gharchive/pull-request

authors: gkc sitaram-kalluri


text:
Pub.Dev - at_onboarding_flutter

Under the scores tab it looks like null safe is not working.  Please check if something is broken or if this truly the case.  TY

This package depends on hive-flutter in which Flutter seems to block dart:indexed_db   thats why we don't have the null safety 20 points.

Should we remove at_onboarding_flutter? Not consistent with other packages landing pages.

This package depends on hive-flutter in which Flutter seems to block dart:indexed_db  thats why we don't have the null safety 20 points.

Thanks @Intiserahmed

The null safety points can not be claimed without support from hive_flutter package. This can be taken up in future when either we move away from hive or the package supports null safety.

authors: Intiserahmed ksanty sarika01


text:
C SSHNPD binary used with NPT

Describe the bug
I am trying to use NPT with the FreeBSD SSHNPD binary on my OPNsense firewall. Normally I set a timeout value on the CLI of the NPT but I get an error when I use the following command to connect to the OPNsense firewall. The --timeout within the command line to a Linux system running SSHNPD works fine. Should NPT using the "--timeout" variable be supported in the FreeBSD SSHNPD binary?
/Users//.local/bin/npt --from @intense56 --to @55commercial --srvd @rv_am --device opnsense --timeout 90s --remote-port 22 --local-port 65221
--Error message output from the connection process---
Error : This device daemon does not support the 'timeout' value in npt session requests
Steps to reproduce

First I installed the FreeBSD binary on my OPNsense firewall runnversion 24.7.1
Then I used the command "npt --from @intense56 --to @55commercial --srvd @rv_am --device opnsense --timeout 90s --remote-port 22 --local-port 65221"  to connect a NPT session the my OPNsense firewall.
And then I saw the message "Error : This device daemon does not support the 'timeout' value in npt session requests" in the terminal window.

Expected behavior
I expected the npt session to connect as it does when connecting to a Linux running NoPorts 5.5.0 SSHNPD.

@kdimick raised this with me in chat, and I asked him to open this issue.
I think the problem here is that the FreeBSD binary is C sshnpd, which doesn't yet implement the --timeout feature

Yep that's correct, Chris

See #1110 for the dart implementation of this feature.

Closing as there's no actionable work here that isn't covered by another issue

authors: XavierChanth gkc kdimick

repo: atsign-foundation/noports


text:
Transcoding Basis Files Sometimes Fails

Hi!
I have a scene in which I'm trying to download basis textures from urls and apply them to image components in the scene. I've been experiencing problems very similar to the ones indicated in #19, where I have confirmed that the basis texture is properly downloaded with the correct data, but the transcoding fails nonetheless. I'm building for WebGL, and I often find that none of the basis textures load successfully.
I've experimented with a few things that also make me think the issue might be related to CPU load or memory allocation (as in #19 ). I created three WebGL builds that each do something slightly different with respect to texture loading. If you open the developer console you'll be able to see all of the logging for the texture loading, including when an attempt to load begins, when it succeeds, and the actual data in the downloaded basis texture.
Build 1: This is the "control". We attempt to load each texture just once. Textures almost always fail to load in this build. Example:

Build 2: In this build, if a texture fails to load, we keep trying until it succeeds. This one still has a ton of failures but the image textures are rarely left empty; however, sometimes the incorrect texture is loaded in, even though the logging says that the correct texture was loaded in (possibly a memory allocation issue?). This error is a little difficult to recreate so I have a few examples of what it looks like.
Build 3: This was the most successful build. The texture download requests are queued and so only one can happen at a time. I think this reinforces that it might be a memory allocation or CPU load issue.
Other Stats

I'm never loading more than 10-15 textures at a time, although this may change in the future.
Textures are typically 512 x 512, but there are a handful of huge ones (1024 x 1024 or 2048 x 1024)
CPU: Intel i7-9750H 2.6 GHz
16 GB RAM
Windows 10

I would appreciate any insight you can offer on this issue. Thank you!

Thanks for this great, very detailed report. Sorry for not answering sooner.
The demo project contains a benchmark scene that loads batches of files. 50 at a time does not produce any errors here (Firefox 84 macOS; Unity 2019.4 LTS).
Which browser are you using?
Can you provide a simple script that reproduces the errors?
Just to clarify: you don't re-use the BasisUniversalTexture objects, right?
Thanks!

Thanks for this great, very detailed report. Sorry for not answering sooner.
The demo project contains a benchmark scene that loads batches of files. 50 at a time does not produce any errors here (Firefox 84 macOS; Unity 2019.4 LTS).
Which browser are you using?
Can you provide a simple script that reproduces the errors?
Just to clarify: you don't re-use the BasisUniversalTexture objects, right?
Thanks!

I'm using Chrome and we are not reusing the BasisUniversalTexture objects. Actually, we're currently loading the textures from bytes but I noticed you made some updates recently and I was hoping to try loading from URL with your most recent updates (the latest version doesn't require a monobehavior to load from URL, but the version we're using does); however, I don't think the correct version of the package is getting installed. It's still installing 0.9.1, which is from November 2020. Would it be possible to make the latest version of the package available?

I'm using Chrome and we are not reusing the BasisUniversalTexture objects. Actually, we're currently loading the textures from bytes but I noticed you made some updates recently and I was hoping to try loading from URL with your most recent updates (the latest version doesn't require a monobehavior to load from URL, but the version we're using does); however, I don't think the correct version of the package is getting installed. It's still installing 0.9.1, which is from November 2020. Would it be possible to make the latest version of the package available?

...however, I don't think the installer package is installing the correct version of KTXUnity. It's still installing 0.9.1, which is from November 2020. Would it be possible to make the latest version of the package available?

As you've figured out yourself, the latest changes are in the main branch, but not in a release thus far. After some more tests I'll release, but use the latest change via GIT URL for now.

...however, I don't think the installer package is installing the correct version of KTXUnity. It's still installing 0.9.1, which is from November 2020. Would it be possible to make the latest version of the package available?

As you've figured out yourself, the latest changes are in the main branch, but not in a release thus far. After some more tests I'll release, but use the latest change via GIT URL for now.

You can test KtxUnity 1.0.0-preview now (make sure to enable show preview packages in the package mangager settings).
Let me know how it goes.

Thanks for creating the preview package!
It's been working perfectly: originally, we were downloading the .basis files from S3 and then loading them from bytes, but that was frequently failing. Now, we're loading all of the .basis files directly from URL, and they're all working on the first try, and using LoadFromBytes to load them from cache is working as well :)

Oh yeah, great to hear!

authors: atteneder badaminatasha

repo: atteneder/KtxUnity


text:
error

private void start(){
    if (Build.VERSION.SDK_INT >= Build.VERSION_CODES.N){
        new TedPermission(context)
                .setPermissionListener(permissionListener)
                .setDeniedMessage(String.valueOf(denied_message))
                .setDeniedCloseButtonText(android.R.string.ok)
                .setGotoSettingButton(false)
                .setPermissions(Manifest.permission.WRITE_EXTERNAL_STORAGE)
                .check();
    } else {
        update();
    }
}

error on this code. the N is highlited Red

Line still not fixed for me

Hi, update version library
compile 'com.github.atzcx:AppVerUpdater:1.0.2'

Oh thank you :)
On Jan 15, 2017 4:10 PM, "Aleksandr" notifications@github.com wrote:

Hi, update version library
compile 'com.github.atzcx:AppVerUpdater:1.0.2'
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/atzcx/AppVerUpdater/issues/6#issuecomment-272694173,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AXtVH0SahQUkk2JkY9PtQC8rXrdWnyXSks5rShpngaJpZM4Lho13
.

repo: atzcx/AppVerUpdater

license_source: bigquery


text:
IE shows apostrophe as ' on charts.

Tested on IE10/11.
Firefox OK.
v0.2.5 was OK.

@redstreet You run Windows, right? Does this happen for you as well?

Yes, I can confirm I'm seeing this on IE11 running on Cygwin/Windows as well, in 0.2.6. I haven't checked previous versions.
I run Cygwin/Windows + Chrome. It appears fine in Chrome.

@redstreet Thanks for confirming (saved me from setting up another VM).
I think this is a bug in the Chartist.js-library we use for the charts. I simply changed the format from MM 'YY (eg. Mar '16) to MM YYYY (eg. Mar 2016) to avoid this - and it looks cleaner anyway, IMHO.

authors: aumayr miaoluda redstreet

repo: aumayr/fava

license: mit


text:
migrate to gist.run samples

General

[x] load and show gists
[x] update tabs to show code preview
[x] implement run button
[x] fix md-well navigation
[x] fix sidenav navigation

Css

[x] color

Components

[x] badges
[x] buttons
[x] breadcrumbs (looking forward to this one)
[x] cards
[x] chips
[x] collections
[x] footer
[x] navbar
[x] pagination
[x] preloader

Javascript

[x] collapsible
[x] dropdowns
[x] dialogs
[x] media
[x] modals
[x] parallax
[x] pushpin
[x] scrollfire
[x] scrollspy
[x] sidenav
[x] tabs
[x] transitions
[x] waves

Forms

[x] input
[x] select
[x] radio
[x] checkbox
[x] file
[x] range
[x] datepicker
[x] autocomplete

Parallax works in the gist: https://gist.run/?id=586589a99303020b983a5d33b5bf9084
But it doesn't display the images when run in the catalog app.

Scrollfire throws:
Uncaught TypeError: Cannot read property 'overrideContext' of null

The aurelia-validation examples are lacking aurelia-validation. I will have to include it in the bundle.

Fixed parallax by setting z-index: 0; in css.
Fixed scrollfire by not doing anything. 😏 Just works now.
Validation gists need the 1.0 fix as they still load the old version but bundles contain the 1.0.0 version.

Removed breadcrumbs gists because it seems like you cannot have a child-router in a gist.


text:
rename md-card "title" property

If it's used with string interpolation, the element's native tooltip becomes: ${expression}.

I'm running into this very problem with 1.2.11.   and ${something} is appearing on hover of title.

authors: Thanood burkeKoontz


text:
Binding error in value converter causes view not to load and does not report error.

ANY error in value converter will result in the view not loading and no errors appear in the console.  Effectively swallowing the error.  Developer debug experience is poor since even a typo will result in an error that can't be located.
To Repro:
Take any binding that has a converter that has one parameter, just pass: BOGUS as below, the view won’t load.
${myModelProperty | myConverter:BOGUS }
Thanks,
Karl

@jdanyow Important note about this that it's not the BOGUS symbol in the expression that is causing the problem. It's the fact that the myConverter converter attempts to use a parameter which is undefined, resulting in an error inside the toView method of the converter. We probably need some way to ensure that any errors that occur inside converters are logged.

I'm seeing an error in the console here: http://plnkr.co/edit/oHcQSk?p=preview
Will test with the router.

Strange.
This was my scenario that caused the problem, the 1st parameter BOGUS.  Now
it's not.

On Wed, Jan 6, 2016 at 12:24 PM, Jeremy Danyow notifications@github.com
wrote:

I'm seeing an error in the console here:
http://plnkr.co/edit/oHcQSk?p=preview
Will test with the router.
—
Reply to this email directly or view it on GitHub
https://github.com/aurelia/binding/issues/278#issuecomment-169395691.

Jeremy,
Throwing in the converter was not my scenario, probably a good test to see that the router does not quit working.
Karl

Ah- I see what you mean- given a binding expression like this ${message | myConverter:myArgument}, there are no errors in the console when myArgument is not defined (eg the view-model has no myArgument property).
We've got an open issue for this here:  https://github.com/aurelia/binding/issues/30

I think it's two things. One is the bogus parameter not being detected and the thing that really cause stuff to "break" was probably that the converter expected a value and tried to work with that in a way that an exception was thrown.

authors: EisenbergEffect jdanyow kdawg1406

repo: aurelia/binding

license: MIT


text:
fix(property-observation): now detects no change when both oldValue and newValue are NaN

In Javascript the expression "NaN === NaN" always resolves to false.
Aurelia uses the expression "oldValue !== newValue" to detect if a property has changed and change-handlers should be called.
This fails if both oldValue and newValue are NaN.
Therefore an extra comparison was added: "!( isNaN(oldValue) && isNaN(newValue) )".

This is not correct. isNaN('text') is true as well.

typeof NaN === 'number'
Sometimes Javascript can be weird...

Fixed by using Number.isNan
The tests now run correctly again. I forgot to remove the 'f' before 'it' in the text which made me miss this issue.

Will the additional comparison affect performance?

The performance penalty is negligible.
The old comparison: a !== b
Added: && !(Number.isNan(a) && Number.isNan(b))
Number.isNan(n) is implemented as: n !== n  (because NaN !== NaN)
So it becomes: a !== b && !( a !== a && b !== b)
The === or !=== operation is, as far as I know, very cheap.
And even if it wasn't, the change detection is incorrect without the added NaN check. I ran into this issue because of an endless loop of a two-way binding that got the value NaN.

thanks for the PR- there's a whole bunch of places we'd need to add this logic.  I don't think the use case is compelling enough to warrant the changes.
Related to https://github.com/aurelia/binding/issues/269

authors: Gheoan jdanyow nicolasdejong


text:
升级2.5.0后Github Action构建OOM，hexo g命令执行内存溢出

Github Action脚本如下：
name: Deploy Hexo Blog

on:
  push:
    branches:
      - master
      - main

jobs:
  build:
    name: Auto Deploy Hexo Blog
    runs-on: ubuntu-latest

    steps:
      - name: Checkout
        uses: actions/checkout@v4
        with:
          fetch-depth: 0
          token: ${{ secrets.CI_GITHUB_TOKEN }}

      - name: Install Node.js
        uses: actions/setup-node@v3
        with:
          node-version: 18

      - uses: pnpm/action-setup@v2
        name: Install pnpm
        id: pnpm-install
        with:
          version: 8
          run_install: false

      - name: Get pnpm store directory
        id: pnpm-cache
        shell: bash
        run: |
          echo "STORE_PATH=$(pnpm store path --silent)" >> $GITHUB_ENV

      - uses: actions/cache@v3
        name: Setup pnpm cache
        with:
          path: ${{ env.STORE_PATH }}
          key: ${{ runner.os }}-pnpm-store-${{ hashFiles('**/pnpm-lock.yaml') }}
          restore-keys: |
            ${{ runner.os }}-pnpm-store-

      - name: Install dependencies
        run: pnpm install --no-frozen-lockfile

      - name: Clean Hexo
        run: npx hexo clean

      - name: Build Hexo
        run: |
          npx hexo generate

      - name: Deploy Hexo
        run: |
          npx hexo deploy

在2.5.0版本前，此脚本构建和发布没有异常，升级2.5.0后跑到hexo g命令控制台显示OOM，日志如下：

hexo-plugin-aurora 修复了这个问题 https://github.com/auroral-ui/hexo-plugin-aurora/releases/tag/v1.8.1

authors: bennyxguo zjcscut

repo: auroral-ui/hexo-theme-aurora


text:
Простейший счетчик Value делает больше, чем нужно

Модель из визадра, показатель
result Пропускная_способность = new Value([парикмахерская.количество_обслуженных / currentTime * 60]);

В отчете одно число, что ожидается
test.test.Пропускная_способность: Value
	Value: 1.8162890483219594

А на графике вся история наблюдения за значением

Тут что-то нелогичное. Я то думал, что значение считается только в момент завершения модели. А тут получается, что это нет так. Из минусов - мы флудим в трассировку расчетами, которые не показываем в отчете, тратим время компа. Если бы не возможность построить графики, то это был бы мусор. Надо или прекратить их считать по ходу моделировать или выдавать какую-то статистику. Потому что график выглядит норм и может быть полезен. Но тогда нужно расширить отчет. Кажется, что надо свести к двум большим схемам

Считаем показатель только в момент остановки модели, в трассировку приходит только одна строчка, время на расчеты не тратится.
Считаем каждый раз, хоть 2 * 2, хоть наблюдаем за параметром ресурса. На выходе и график и статистика.

Что думаете ?

График слева по трассировке показателя (простейший Value, Карл), справа - по параметру ресурса

Дело в том, что результат и статистика разные сущности. График и трассировка выводятся для результатов, отчет показывается для статистики.

Обсудили, пришли к https://github.com/aurusov/raox/issues/497. Эту закрываю.

authors: AlexChernov aurusov

repo: aurusov/raox


text:
Bug: Assembly with same name is already loaded

When using Az.KeyVault in Combination with Send-MailKiTMessage the command Import-Module throws:
Import-Module: C:\Temp\d5plgr21.aue\484853eb-9c26-4659-ac55-ff53e9138976.ps1:2
Line |
   2 |  Import-Module Az.Keyvault
     |  ~~~~~~~~~~~~~~~~~~~~~~~~~
     | Assembly with same name is already loaded

Tested with PS 7.1, 7.2 and with latest Module Versions.

Yes we are having this problem as well. It was exposed by us using the Microsoft.Powershell.SecretManagement library and registering a KeyVault and when we use Get-Secret it throws Assembly with same name is already loaded
Full repro with output with -verbose here
import-module az.keyvault
import-module Send-MailKitMessage -verbose

Import-Module:
VERBOSE: Loading module from path 'C:\Users\blah\OneDrive\Documents\PowerShell\Modules\Send-MailKitMessage\3.1.0\Send-MailKitMessage.psd1'.
VERBOSE: Loading 'Assembly' from path 'C:\Users\blah\OneDrive\Documents\PowerShell\Modules\Send-MailKitMessage\3.1.0\Libraries\BouncyCastle.Crypto.dll'.
VERBOSE: Loading 'Executable' from path 'C:\Users\blah\OneDrive\Documents\PowerShell\Modules\Send-MailKitMessage\3.1.0\Libraries\BouncyCastle.Crypto.dll'.
VERBOSE: Loading 'Assembly' from path 'C:\Users\blah\OneDrive\Documents\PowerShell\Modules\Send-MailKitMessage\3.1.0\Libraries\MailKit.dll'.
VERBOSE: Loading 'Executable' from path 'C:\Users\blah\OneDrive\Documents\PowerShell\Modules\Send-MailKitMessage\3.1.0\Libraries\MailKit.dll'.
VERBOSE: Loading 'Assembly' from path 'C:\Users\blah\OneDrive\Documents\PowerShell\Modules\Send-MailKitMessage\3.1.0\Libraries\MimeKit.dll'.
VERBOSE: Loading 'Executable' from path 'C:\Users\blah\OneDrive\Documents\PowerShell\Modules\Send-MailKitMessage\3.1.0\Libraries\MimeKit.dll'.
import-module :
PSMessageDetails      :
Exception             : System.IO.FileLoadException: Assembly with same name is already loaded
                           at System.Management.Automation.Runspaces.InitialSessionState.Bind_LoadAssemblies(ExecutionContext context)
                           at System.Management.Automation.Runspaces.InitialSessionState.Bind(ExecutionContext context, Boolean updateOnly, PSModuleInfo module, Boolean noClobber, Boolean local, Boolean setLocation)
                           at Microsoft.PowerShell.Commands.ModuleCmdletBase.LoadModuleManifest(String moduleManifestPath, ExternalScriptInfo manifestScriptInfo, Hashtable data, Hashtable localizedData, ManifestProcessingFlags manifestProcessingFlags, Version minimumVersion, Version maximumVersion, Version requiredVersion, Nullable`1 requiredModuleGuid, ImportModuleOptions& options, Boolean& containedErrors)
TargetObject          :
CategoryInfo          : InvalidOperation: (:) [Import-Module], FileLoadException
FullyQualifiedErrorId : FormatXmlUpdateException,Microsoft.PowerShell.Commands.ImportModuleCommand
ErrorDetails          :
InvocationInfo        : System.Management.Automation.InvocationInfo
ScriptStackTrace      : at <ScriptBlock>, <No file>: line 1
PipelineIterationInfo : {0, 1}

Secrets ultimately more vital than email so we will have to turn off the email features until this is resolved or find an alternative email sending method :(

Unfortunately I think the problem is ultimately this
https://devblogs.microsoft.com/powershell/resolving-powershell-module-assembly-dependency-conflicts/

Hi @Gill-Bates and @o-o00o-o,
Thanks for identitying this.
@o-o00o-o I would agree, I think that will be the way to resolve. In fact in 3.2.0-preview1 where Windows PowerShell support is added I had to use that exact approach to resolve another conflict (https://github.com/austineric/Send-MailKitMessage/blob/eef9fc1319c85692d637b6ccad8f61a07ef61acf/Project/Send_MailKitMessage.cs#L16)
I'll see if I can get an updated version out shortly.

authors: Gill-Bates austineric o-o00o-o

repo: austineric/Send-MailKitMessage


text:
DXCDT-597: Don't require all scopes for client credentials auth

🔧 Changes
As noted by #556, when authenticating to the CLI with client credentials, it is necessary for that client to have a set of required scopes. Doing so ensures that the CLI has full functionality out-the-box, however, this precludes the CLI from adhering to principle of least privilege. As the original Github issue notes, the CLI can be used in automation for specific cases and users should be able to provision only the scopes for those cases.
📚 References
Related Github issue: #556
🔬 Testing
Manual verification; no testing framework in place to test token exchange.
📝 Checklist

[x] All new/changed/fixed functionality is covered by tests (or N/A)
[x] I have added documentation for all new/changed functionality (or N/A)

Confirmed again that this works as expected; no other logic needs to be modified.


text:
Error: secretOrPrivateKey must be an asymmetric key when using ES256

Description
I am unable to sign a jwt by using the private key associated to a Metamask wallet. Ideally I would like to sign a jwt for a verifiable credential by using the private key of the issuer of the credential:
const vcPayload = {
  sub: sub.getDid(),
  nbf: Math.floor(Date.now() / 1000),
  vc: {
    '@context': ['https://www.w3.org/2018/credentials/v1'],
    type: ['VerifiableCredential'],
    credentialSubject: {
      degree: {
        type: 'BachelorDegree',
        name: 'Baccalauréat en musiques numériques'
      }
    }
  }
}

const vcJwt = jwt.sign(vcPayload, issuer.getPrivateKey(), { algorithm: 'ES256' });

const decodedJwt = jwt.decode(vcJwt, { complete: true });
console.log(`Decoded VC: ${JSON.stringify(decodedJwt)}`);

const verifiedJwt = jwt.verify(vcJwt, issuer.getPublicKey(), { algorithms: ['ES256'] });
console.log(`Verified VC: ${JSON.stringify(JSON.stringify(verifiedJwt))}`);

The problem I am encountering is the following one:
Error: secretOrPrivateKey must be an asymmetric key when using ES256
    at module.exports [as sign] (node_modules/jsonwebtoken/sign.js:124:22)
    at main (src/app.ts:151:21)
    at process.processTicksAndRejections (node:internal/process/task_queues:95:5) {stack: 'Error: secretOrPrivateKey must be an asymmetr…ions (node:internal/process/task_queues:95:5)', message: 'secretOrPrivateKey must be an asymmetric key when using ES256'}

Environment
"jsonwebtoken": "9.0.0"

From what I can tell issuer.getPrivateKey() for you likely just returns a buffer with the 32 raw private key bytes.
jsonwebtoken needs to get a PEM P-256 private key string or a crypto.KeyObject instance representing a P-256 private EC key (you can obtain such instance using the crypto.createPrivateKey method to sign using ES256.

Key format conversion is not part of the jsonwebtoken APIs. Also the JWS Algorithm designated for secp256k1 keys is ES256K, not ES256.

Ok, I will close the issue. Is there any resource that you know of that you can share here to parse the key and convert it to a format which is accepted by jwt.sign when the ES256K algorithm is used?

Thanks very much for your help, even if it is not inherent to a bug in the library. I cannot understand why my private/public keypair is not matching the specification you gave: my public key starts with 0xBA..., and when I run const keyObject = crypto.createPrivateKey({ format: 'jwk', key: jwk }) from the code snippet you posted, I get Uncaught TypeError TypeError: Invalid JWK EC key.
The private/public keypair is from a Metamask wallet, and it should be a secp256k1 keypair.

Same problem. I'm following Apple's instructions
My code:
const token = jwt.sign(
      {
        iss: CONSTANTS.ISSUER_ID,
        iat: Math.floor(Date.now() / 1000), // is Seconds
        exp: Math.floor(Date.now() / 1000) + (60 * 30), // is Seconds
        aud: 'appstoreconnect-v1',
        bid: bundleId,
      },
      CONSTANTS.IAP_KEY,
      {
        header: {
          alg: "ES256",
          child: CONSTANTS.IAP_KEY_ID,
          typ: 'JWT',
        },
      },
    );

IAP_KEY:
MIGTAgEAMBMGByqGSM49AgEGCCqGSM49AwEHBHkwdwIBAQQgASaLt9X9vfWGno8O
jzkyvifgBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB0DAQehRANCAAQ+MQPpC9wIgSQb
Cg/Ovrs/NTBo6rzd98xoCk544BfAx3s48dMKPDFFUgogTL/mGSc0v91vZJADeQnh
VjU1rQu2
 -----END PRIVATE KEY-----```

bump.  I have the exact same problem following Apple's instructions.  Has anyone figured out a solution to this?

Try reading the private key file like this
const privateKey = fs.readFileSync(path to private key);
Use this private key to sign the token

bump. I have the exact same problem following Apple's instructions. Has anyone figured out a solution to this?

same problem. Any solution?

Same problem. I'm following Apple's instructions
My code:
const token = jwt.sign(
      {
        iss: CONSTANTS.ISSUER_ID,
        iat: Math.floor(Date.now() / 1000), // is Seconds
        exp: Math.floor(Date.now() / 1000) + (60 * 30), // is Seconds
        aud: 'appstoreconnect-v1',
        bid: bundleId,
      },
      CONSTANTS.IAP_KEY,
      {
        header: {
          alg: "ES256",
          child: CONSTANTS.IAP_KEY_ID,
          typ: 'JWT',
        },
      },
    );

IAP_KEY:
-----BEGIN PRIVATE KEY-----
MIGTAgEAMBMGByqGSM49AgEGCCqGSM49AwEHBHkwdwIBAQQgASaLt9X9vfWGno8O
jzkyvifgBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB0DAQehRANCAAQ+MQPpC9wIgSQb
Cg/Ovrs/NTBo6rzd98xoCk544BfAx3s48dMKPDFFUgogTL/mGSc0v91vZJADeQnh
VjU1rQu2
 -----END PRIVATE KEY-----

P.S.: I realized that Apple gave me one symmetrical key. How do I convert it to asymmetric? Apple's IAP_KEY is defined as secretOrPrivateKey.type: secret
P.P.S.: Or is there any way to disable the key symmetry check in the method parameters?

@kostasoft have you fix it?

Try reading the private key file like this const privateKey = fs.readFileSync(path to private key); Use this private key to sign the token

This worked for me, thank you!

authors: JoeDareZone Keltin42 Oladejiraji francesco-plt kostasoft panva thomas2109 vohrahul


text:
🛑 Geoserver § geoserver1.prahounakole.cz is down

In 14a4057, Geoserver § geoserver1.prahounakole.cz (https://geoserver1.prahounakole.cz) was down:

HTTP code: 502
Response time: 3515 ms

Resolved: Geoserver § geoserver1.prahounakole.cz is back up in c0dd52e after 9 minutes.

repo: auto-mat/automat-statuspage


text:
🛑 Cyklisté sobě § www.cyklistesobe.cz is down

In 8102535, Cyklisté sobě § www.cyklistesobe.cz (https://www.cyklistesobe.cz/) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Cyklisté sobě § www.cyklistesobe.cz is back up in 77bd9c5 after 32 minutes.


text:
🛑 Automat eshop § obchod.auto-mat.cz is down

In 813823a, Automat eshop § obchod.auto-mat.cz (https://obchod.auto-mat.cz/) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Automat eshop § obchod.auto-mat.cz is back up in 488a6b5.


text:
[BUG] Exception during fitting in calibrate_model() when using custom metric with needs_proba=True

[ ] I have checked that this bug exists on the latest stable version of AutoGluon
[ ] and/or I have checked that this bug exists on the latest mainline of AutoGluon via source installation

Describe the bug
At the end of training an exception is raised during calibrate_model() when using a custom metric with needs_proba=True
I'm using version 0.6.0 (I have a different reported issue with 0.6.1).
Expected behavior
No exception
To Reproduce
import numpy as np

from autogluon.core.metrics import make_scorer
from autogluon.tabular import TabularDataset, TabularPredictor

def custom_score(y_true, y_proba):
    pred_true_np  = y_true[y_proba >= 0.6]
    pred_false_np = y_true[y_proba <= 0.4]

    pred_true_correct_count  =                      np.count_nonzero(pred_true_np)
    pred_false_correct_count = pred_false_np.size - np.count_nonzero(pred_false_np)

    pred_count         = pred_true_np.size       + pred_false_np.size
    pred_correct_count = pred_true_correct_count + pred_false_correct_count

    if pred_count == 0:
        return 0.5

    score = pred_correct_count / pred_count
    return score

metric = make_scorer(
    name="custom_score",
    score_func=custom_score,
    optimum=1,
    greater_is_better=True,
    needs_proba=True,
)

train_data = TabularDataset('https://autogluon.s3.amazonaws.com/datasets/Inc/train.csv')
test_data = TabularDataset('https://autogluon.s3.amazonaws.com/datasets/Inc/test.csv')
predictor = TabularPredictor(label='class', eval_metric=metric).fit(train_data=train_data, time_limit=60)

Logs
Beginning AutoGluon training ... Time limit = 60s
AutoGluon Version:  0.6.0
Python Version:     3.9.13
Operating System:   Windows
Platform Machine:   AMD64
Platform Version:   10.0.19045
Train Data Rows:    39073
Train Data Columns: 14
Label Column: class
Preprocessing data ...
AutoGluon infers your prediction problem is: 'binary' (because only two unique label-values observed).
        2 unique label values:  [' <=50K', ' >50K']
        If 'binary' is not the correct problem_type, please manually specify the problem_type parameter during predictor init (You may specify problem_type as one of: ['binary', 'multiclass', 'regression'])
Selected class <--> label mapping:  class 1 =  >50K, class 0 =  <=50K
        Note: For your binary classification, AutoGluon arbitrarily selected which label-value represents positive ( >50K) vs negative ( <=50K) class.
        To explicitly set the positive_class, either rename classes to 1 and 0, or specify positive_class in Predictor init.
Using Feature Generators to preprocess the data ...
Fitting AutoMLPipelineFeatureGenerator...
        Inferring data type of each feature based on column values. Set feature_metadata_in to manually specify special dtypes of the features.
        Stage 1 Generators:
                Fitting AsTypeFeatureGenerator...
                        Note: Converting 1 features to boolean dtype as they only contain 2 unique values.
        Stage 2 Generators:
                Fitting FillNaFeatureGenerator...
        Stage 3 Generators:
                Fitting IdentityFeatureGenerator...
                Fitting CategoryFeatureGenerator...
                        Fitting CategoryMemoryMinimizeFeatureGenerator...
        Stage 4 Generators:
                Fitting DropUniqueFeatureGenerator...
        Types of features in original data (raw dtype, special dtypes):
                ('int', [])    : 6 | ['age', 'fnlwgt', 'education-num', 'capital-gain', 'capital-loss', ...]
                ('object', []) : 8 | ['workclass', 'education', 'marital-status', 'occupation', 'relationship', ...]
        Types of features in processed data (raw dtype, special dtypes):
                ('category', [])  : 7 | ['workclass', 'education', 'marital-status', 'occupation', 'relationship', ...]
                ('int', [])       : 6 | ['age', 'fnlwgt', 'education-num', 'capital-gain', 'capital-loss', ...]
                ('int', ['bool']) : 1 | ['sex']
        0.4s = Fit runtime
        14 features in original data used to generate 14 features in processed data.
Data preprocessing and feature engineering runtime = 0.45s ...
AutoGluon will gauge predictive performance using evaluation metric: 'custom_score'
        This metric expects predicted probabilities rather than predicted class labels, so you'll need to use predict_proba() instead of predict()
        To change this, specify the eval_metric parameter of Predictor()
Automatically generating train/validation split with holdout_frac=0.0639828014229775, Train Rows: 36573, Val Rows: 2500
Fitting 13 L1 models ...
Fitting model: KNeighborsUnif ... Training model for up to 59.55s of the 59.55s of remaining time.
        0.7752   = Validation score   (custom_score)
        1.66s    = Training   runtime
        0.01s    = Validation runtime
Fitting model: KNeighborsDist ... Training model for up to 57.87s of the 57.87s of remaining time.
        0.7932   = Validation score   (custom_score)
        0.05s    = Training   runtime
        0.02s    = Validation runtime
Fitting model: LightGBMXT ... Training model for up to 57.79s of the 57.78s of remaining time.
        0.9151   = Validation score   (custom_score)
        3.95s    = Training   runtime
        0.05s    = Validation runtime
Fitting model: LightGBM ... Training model for up to 53.71s of the 53.7s of remaining time.
        0.919    = Validation score   (custom_score)
        1.21s    = Training   runtime
        0.02s    = Validation runtime
Fitting model: RandomForestGini ... Training model for up to 52.46s of the 52.46s of remaining time.
        0.8937   = Validation score   (custom_score)
        3.86s    = Training   runtime
        0.18s    = Validation runtime
Fitting model: RandomForestEntr ... Training model for up to 47.89s of the 47.89s of remaining time.
        0.8966   = Validation score   (custom_score)
        4.65s    = Training   runtime
        0.18s    = Validation runtime
Fitting model: CatBoost ... Training model for up to 42.59s of the 42.58s of remaining time.
        Ran out of time, early stopping on iteration 487.
        0.9161   = Validation score   (custom_score)
        42.64s   = Training   runtime
        0.02s    = Validation runtime
Fitting model: WeightedEnsemble_L2 ... Training model for up to 59.55s of the -0.13s of remaining time.
        0.9202   = Validation score   (custom_score)
        0.34s    = Training   runtime
        0.0s     = Validation runtime
AutoGluon training complete, total runtime = 60.55s ... Best model: "WeightedEnsemble_L2"
Traceback (most recent call last):
  File "test.py", line 32, in <module>
    predictor = TabularPredictor(label='class', eval_metric=metric).fit(train_data=train_data, time_limit=60)
  File ".venv\lib\site-packages\autogluon\core\utils\decorators.py", line 30, in _call
    return f(*gargs, **gkwargs)
  File ".venv\lib\site-packages\autogluon\tabular\predictor\predictor.py", line 868, in fit
    self._post_fit(
  File ".venv\lib\site-packages\autogluon\tabular\predictor\predictor.py", line 921, in _post_fit
    self._trainer.calibrate_model()
  File ".venv\lib\site-packages\autogluon\core\trainer\abstract_trainer.py", line 2953, in calibrate_model
    temp_scalar = tune_temperature_scaling(y_val_probs=y_val_probs, y_val=y_val,
  File ".venv\lib\site-packages\autogluon\core\calibrate\temperature_scaling.py", line 57, in tune_temperature_scaling
    optimizer.step(temperature_scale_step)
  File ".venv\lib\site-packages\torch\optim\lr_scheduler.py", line 65, in wrapper
    return wrapped(*args, **kwargs)
  File ".venv\lib\site-packages\torch\optim\optimizer.py", line 113, in wrapper
    return func(*args, **kwargs)
  File ".venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File ".venv\lib\site-packages\torch\optim\lbfgs.py", line 311, in step
    orig_loss = closure()
  File ".venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File ".venv\lib\site-packages\autogluon\core\calibrate\temperature_scaling.py", line 52, in temperature_scale_step
    loss = nll_criterion(new_logits, y_val_tensor)
  File ".venv\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
    return forward_call(*input, **kwargs)
  File ".venv\lib\site-packages\torch\nn\modules\loss.py", line 1164, in forward
    return F.cross_entropy(input, target, weight=self.weight,
  File ".venv\lib\site-packages\torch\nn\functional.py", line 3014, in cross_entropy
    return torch._C._nn.cross_entropy_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index, label_smoothing)
RuntimeError: expected scalar type Long but found Int

Installed Versions
autogluon-0.6.0
Additional context
In the actual training I'm doing I get a slightly different exception than above:
Traceback (most recent call last):
  File "ag.py", line 79, in train
    predictor.fit(train_data)
  File ".venv\lib\site-packages\autogluon\core\utils\decorators.py", line 30, in _call
    return f(*gargs, **gkwargs)
  File ".venv\lib\site-packages\autogluon\tabular\predictor\predictor.py", line 868, in fit
    self._post_fit(
  File ".venv\lib\site-packages\autogluon\tabular\predictor\predictor.py", line 921, in _post_fit
    self._trainer.calibrate_model()
  File ".venv\lib\site-packages\autogluon\core\trainer\abstract_trainer.py", line 2953, in calibrate_model
    temp_scalar = tune_temperature_scaling(y_val_probs=y_val_probs, y_val=y_val,
  File ".venv\lib\site-packages\autogluon\core\calibrate\temperature_scaling.py", line 57, in tune_temperature_scaling
    optimizer.step(temperature_scale_step)
  File ".venv\lib\site-packages\torch\optim\lr_scheduler.py", line 65, in wrapper
    return wrapped(*args, **kwargs)
  File ".venv\lib\site-packages\torch\optim\optimizer.py", line 113, in wrapper
    return func(*args, **kwargs)
  File ".venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File ".venv\lib\site-packages\torch\optim\lbfgs.py", line 311, in step
    orig_loss = closure()
  File ".venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File ".venv\lib\site-packages\autogluon\core\calibrate\temperature_scaling.py", line 50, in temperature_scale_step
    temp = temperature_param.unsqueeze(1).expand(logits.size(0), logits.size(1))
IndexError: Dimension out of range (expected to be in range of [-1, 0], but got 1)

Seems to work correctly if I call make_scorer(... needs_threshold=True) as in the docs instead of make_scorer(... needs_proba=True) which I assumed is more correct for my case.

Fixed in 0.6.2

I spoke too soon, it still happens in 0.6.2 if I use make_scorer(... needs_proba=True) but not on the simple repro from above.
As a workaround I use make_scorer(... needs_threshold=True).
Feel free to close if usage of  needs_proba=True is not supported, it's unclear to me what's the correct way to create a scorer which needs proba.
Traceback (most recent call last):
  File "ag.py", line 79, in train
    _PREDICTOR.fit(train_data, **fit_params, **fit_params_extra)
  File "/home/studio-lab-user/.conda/envs/exprun/lib/python3.9/site-packages/autogluon/core/utils/decorators.py", line 30, in _call
    return f(*gargs, **gkwargs)
  File "/home/studio-lab-user/.conda/envs/exprun/lib/python3.9/site-packages/autogluon/tabular/predictor/predictor.py", line 867, in fit
    self._post_fit(
  File "/home/studio-lab-user/.conda/envs/exprun/lib/python3.9/site-packages/autogluon/tabular/predictor/predictor.py", line 920, in _post_fit
    self._trainer.calibrate_model()
  File "/home/studio-lab-user/.conda/envs/exprun/lib/python3.9/site-packages/autogluon/core/trainer/abstract_trainer.py", line 2954, in calibrate_model
    temp_scalar = tune_temperature_scaling(y_val_probs=y_val_probs, y_val=y_val,
  File "/home/studio-lab-user/.conda/envs/exprun/lib/python3.9/site-packages/autogluon/core/calibrate/temperature_scaling.py", line 57, in tune_temperature_scaling
    optimizer.step(temperature_scale_step)
  File "/home/studio-lab-user/.conda/envs/exprun/lib/python3.9/site-packages/torch/optim/lr_scheduler.py", line 65, in wrapper
    return wrapped(*args, **kwargs)
  File "/home/studio-lab-user/.conda/envs/exprun/lib/python3.9/site-packages/torch/optim/optimizer.py", line 113, in wrapper
    return func(*args, **kwargs)
  File "/home/studio-lab-user/.conda/envs/exprun/lib/python3.9/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/home/studio-lab-user/.conda/envs/exprun/lib/python3.9/site-packages/torch/optim/lbfgs.py", line 311, in step
    orig_loss = closure()
  File "/home/studio-lab-user/.conda/envs/exprun/lib/python3.9/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/home/studio-lab-user/.conda/envs/exprun/lib/python3.9/site-packages/autogluon/core/calibrate/temperature_scaling.py", line 52, in temperature_scale_step
    loss = nll_criterion(new_logits, y_val_tensor)
  File "/home/studio-lab-user/.conda/envs/exprun/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/studio-lab-user/.conda/envs/exprun/lib/python3.9/site-packages/torch/nn/modules/loss.py", line 1164, in forward
    return F.cross_entropy(input, target, weight=self.weight,
  File "/home/studio-lab-user/.conda/envs/exprun/lib/python3.9/site-packages/torch/nn/functional.py", line 3014, in cross_entropy
    return torch._C._nn.cross_entropy_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index, label_smoothing)
ValueError: Expected input batch_size (229) to match target batch_size (1116).

@2-5 for the bug present in v0.6.2, could you provide a minimal example of it occurring? Will help me deep dive.

Thanks a ton for the example! I was able to reproduce into a minimal example:
from autogluon.tabular import TabularDataset, TabularPredictor

train_data  = TabularDataset("train.csv")
tuning_data = train_data[:200]

predictor = TabularPredictor(label="y", eval_metric='log_loss')
predictor.fit(
    train_data=train_data,
    tuning_data=tuning_data,
    num_bag_folds=2,
    use_bag_holdout=True,
    hyperparameters={'GBM': {}}
)

Working on a fix currently

Fixed! Thanks again for making an issue!

repo: autogluon/autogluon


text:
n needs to be an int or a list/set/tuple of ints (error)

i got this error when i want to run my code in collab to make it run faster.
train_data = TimeSeriesDataFrame.from_data_frame(             df.reset_index(),             id_column='Brand',             timestamp_column='Date'         ) test_data = train_data.copy() train_data = train_data.slice_by_timestep(slice(None, -prediction_length)) train_data.head()

ıt's worked.Thank you.


text:
add callbacks to train

learning rate scheduler
learning rate plateu
earlystop

I think it will be also good to add ModelCheckpoint, where we would save the best model.

also callbacks for early stopping and reducing lr were added to a daily-dev.

authors: konchokdolma mikkokotila

repo: autonomio/autonomio


text:
how to use intrinsics and extrinsics from colmap ?

Hi ,
I have a custom image dataset, and run colmap to get the instrinsics and extrinsics of all the images. Then , how should I proceed to run monosdf and get the mesh?
Thanks!
Jiakui

Hi, I think you could adapt this script https://github.com/autonomousvision/monosdf/blob/main/preprocess/scannet_to_monosdf.py to prepare the data

Hi, author.
I run colmap and the following code to generate 'cameras.npz'.
    intrin_mat = np.array([
        [fx,  0, cx],
        [ 0, fy, cy],
        [ 0,  0,  1]
    ])
    intrin_mat[0, 2] -= (w - min(w, h)) / 2.
    intrin_mat[1, 2] -= (h - min(w, h)) / 2.
    intrin_mat[:2, :] *= 384. / min(w, h)

    K = np.eye(4, dtype=np.float32)
    K[:3, :3] = intrin_mat

    valid_poses = np.isfinite(poses).all(axis=2).all(axis=1)
    min_vertices = poses[:, :3, 3][valid_poses].min(axis=0)
    max_vertices = poses[:, :3, 3][valid_poses].max(axis=0)
    scale_mat = np.eye(4, dtype=np.float32)
    scale_mat[:3, 3] = - (min_vertices + max_vertices) / 2.
    scale_mat[:3] *= 2. / (np.max(max_vertices - min_vertices) + 3.)
    scale_mat = np.linalg.inv(scale_mat)

    cams = {}
    idx = 0
    for _, (pose, valid) in enumerate(zip(poses, valid_poses)):
        if not valid: continue
        pose = K @ np.linalg.inv(pose)
        cams[f"scale_mat_{idx:d}"] = scale_mat
        cams[f"world_mat_{idx:d}"] = pose
        idx += 1
    np.savez(osp.join(path, "cameras.npz"), **cams)

It seems that the losses are converging, but the mesh is just strange.

The normal train reslut is as follows.

I notice the code in 'scene_dataset.py' and comment it, the result keeping bad.
elif center_crop_type == 'center_crop_for_dtu':
     scale = 384 / 1200
     offset = (1600 - 1200) * 0.5
     intrinsics[0, 2] -= offset
     intrinsics[:2, :] *= scale

I guess the issue lies in the transform process to camera poses.
Do u have any idea?

@CCOSerika Sorry for the late reply.
This line
scale_mat[:3] *= 2. / (np.max(max_vertices - min_vertices) + 3.)

is used for ScanNet (indoor scenes) where the cameras are inside the rooms. In the DTU cases it should be changed to something like
scale_mat[:3] *= 3. / (np.max(max_vertices - min_vertices))

Sorry，I want to ask if pose conversion is only used to generate mesh in the evaluation phase？

@MingRuiye Sorry I missed your messages. Not sure whether I understand your question. The pose conversion is used in evaluation phase because we need to convert the extracted mesh back to original world space.

authors: CCOSerika Jiakui MingRuiye niujinshuchong

repo: autonomousvision/monosdf


text:
refactor(behavior_velocity_planner): use motion_utils and tier4_autoware_utils

Signed-off-by: Takayuki Murooka takayuki5168@gmail.com
Description
use motion_utils and tier4_autoware_utils in behavior velocity planner

Pre-review checklist for the PR author
The PR author must check the checkboxes below when creating the PR.

[x] I've confirmed the contribution guidelines.
[x] The PR follows the pull request guidelines.

In-review checklist for the PR reviewers
The PR reviewers must check the checkboxes below before approval.

[ ] The PR follows the pull request guidelines.

Post-review checklist for the PR author
The PR author must check the checkboxes below before merging.

[ ] There are no open discussions or they are tracked via tickets.

After all checkboxes are checked, anyone who has write access can merge the PR.

Some points to be careful for this PR's changes.

calcClosestIndex in behavior_velocity_planner have some default parameters

When points and pose are given, the threshold is distance and angle.

https://github.com/autowarefoundation/autoware.universe/blob/f83e4897d154e1b5c34fcf59bdc6e848969c9c9c/planning/behavior_velocity_planner/include/utilization/util.hpp#L153-L155

When points and point are given, the threshold is only distance.

https://github.com/autowarefoundation/autoware.universe/blob/f83e4897d154e1b5c34fcf59bdc6e848969c9c9c/planning/behavior_velocity_planner/include/utilization/util.hpp#L157-L159

@takayuki5168
you need static_cast() for blindspot and intersection to compare with possible index -1
  if (static_cast<int>(closest_idx) == pass_judge_line_idx) {


text:
Denormalize AerialPosition, Waypoint, UasTelemetry

Use inheritance rather than foreign keys to simplify editing, and to improve performance (stored together).

Will be easier to work on after #331.

repo: auvsi-suas/interop


text:
Create profile card

Hackathon Git Labs Project PR 🎉🎉
PR contains:

Updated Alissa directory with proper spelling so links work
Updated Alissa/index.html with profile card html
Updated Alissa/style.css with profile card styles
New button on the bottom of the page that links back to main index.html
Note: This page is still in progress, and there is commented out code in these files that will be removed when page is completed

Breaking changes

None

Screenshots

Hi Alissa! Great work here 😄 My only concern is the .DS_Store files? Can they be removed please? 😀 Once done, I'll merge the PR straight away. I've also updated the gitignore file now too to suit.

@auxfuse
I thought this PR was closed because I didn't reload the browser, so I actually deleted this branch. I added those annoying MACOS DS_Store files to the .gitignore on the other branch I made (in the next PR). So we can close this one and merge that other one

repo: auxfuse/hackathon-git-labs


text:
Unrecognized option "knp_menu" under "avanzu_admin_theme"

Hello,
I've got trouble when using the base_layout.
I tried to override it, and it tells me :
Method "knp_menu" for object "Avanzu\AdminThemeBundle\Helper\ContextHelper" does not exist in app/Resources/AvanzuAdminThemeBundle/views/layout/base-layout.html.twig
I tried to add the knp_menu.enabled in the config but it says :
Unrecognized option "knp_menu" under "avanzu_admin_theme"
I think that the twig globals are not passed to my view override. Any idea ?
thanks !

@numerogeek are you using master or 1.3 version? Could you copy your current config ans base-layout override to see if there are something different?

This is since upgrading to the latest beta 7 release. I am suffering from the same issue.

I had to downgrade back to 2.0.0-beta.5 to get my configuration to be accepted.
Are the configuration changes documented anywhere?

@numerogeek @benr77 I push a fix https://github.com/avanzu/AdminThemeBundle/commit/a6afac02b91022a7e27bd98ea0562e1383a6022d related to ContextHelper config in master, please test if you can so this should be fixed

It doesn't seem to have fixed my problem:
In my composer.json
"avanzu/admin-theme-bundle": "dev-master#a6afac02b91022a7e27bd98ea0562e1383a6022d"
then composer update avanzu/admin-theme-bundle
I get the following error
[Symfony\Component\Config\Definition\Exception\InvalidConfigurationException]
  Unrecognized options "knp_menu, theme" under "avanzu_admin_theme"

If I revert back to 2.0.0-beta.5 it works again.
Here is my configuration
avanzu_admin_theme:
  knp_menu:
    enable : true
  theme:
    default_avatar: bundles/avanzuadmintheme/img/avatar.png
    skin: skin-blue  # see skin listing for viable options
    fixed_layout: false      # -------------------------------------------------------
    boxed_layout: false      # these settings relate directly to the "Layout Options"
    collapsed_sidebar: false      # described in the adminlte documentation
    mini_sidebar: false      # -------------------------------------------------------
    control_sidebar: true      # controls whether the right hand panel will be rendered
    widget:
      collapsible: false
      removable: false
      solid: true
      use_footer: false

@benr77 thanks for your testing! I push new updates in master, please test if you can for receive your new feedback

@shakaran Sounds good for knp_menu but if you want to customize the skin it does not work.
In fact, in the ContextHelper, you set the default in :
$resolver->setDefaults([
'use_twig' => true,
'use_assetic' => true,
'options' => [],
'skin' => 'skin-blue',
But in the Configuration, you put the skin option under the "theme" node.
When I try to change the skin:
avanzu_admin_theme:
theme:
skin: skin-black
it does not change anything and {{ dump(avanzu_admin_context.option) }} gives me an empty array.

@numerogeek the skin param don't should appear under avanzu_admin_context.option, if should be under avanzu_admin_context.skin directly
avanzu_admin_theme:
    theme:
        skin: skin-black

Take in mind that avanzu_admin_context is a shorcut to class avanzu_admin_theme.context_helper
All under the "context" should be present:
{{ dump(avanzu_admin_context.skin) }}
Another case could be via the twig function "body_class" which use some default layouts in the bundle templates:
body_class({'skin': 'skin-black'})
The body_class has more params like fixed_layout, boxed_layout, collapsed_sidebar, mini_sidebar . The full config for that is:
body_class({
    'skin': 'skin-black',
    'fixed_layout': 'true',
    'boxed_layout': 'true',
    'collapsed_sidebar': 'true',
    'mini_sidebar': 'true',
})

@shakaran When I try to dump {{ dump(avanzu_admin_context.skin) }}
I got

Method "skin" for object "Avanzu\AdminThemeBundle\Helper\ContextHelper" does not exist

@shakaran I think that the configuration is overwritten with default value when the container builds.

@shakaran Update:
In the AvanzuAdminExtension class :
`    public function load(array $configs, ContainerBuilder $container)
{
$baseConfiguration = new Configuration();
    // Load the configuration from files
    try
    {
        $configs = $container->getExtensionConfig($this->getAlias());
    }
    catch(InvalidConfigurationException $e)
    {
        echo 'AvanzuAdminBundle:' . $e->getMessage() . PHP_EOL;
        $configs = [];
    }

....
`
$configs is resetted with the default value. Why  do you do this  $configs = $container->getExtensionConfig($this->getAlias()); ?

@numerogeek before to this fixes, when you have a invalid config value set (for example an invented key or unexistant). You will get a exception that will avoid render anything.
In your case, it seems that you get a InvalidConfigurationException, that means that your config has some invalid value, and you should see a message with "AvanzuAdminBundle" string in console or printed.
The problem here, is that it should fallback to base config, which I set a $config = [] array value, and probably it should fallback to base configuration instead.
The $container->getExtensionConfig($this->getAlias()); is needed to fetch and validate the current config before to apply or read the values in config. That means, set a base config, override with the values set by the user and after apply the final result.
So, please watch if you are receiving a message with AvanzuAdminBundle previously with the invalid configuration. I will push a fix for the base configuration.

@shakaran
Here is my config:
avanzu_admin_theme:
    bower_bin: %bower_bin% # that's the default value
    use_assetic: true

To reproduce: Try to clear your cache, set a custom bower_bin path (I need it for travis because travis don't store it in /usr/local/bin) and try to print the bower path selected by the load configuration.
I suspect that's exactly the same for the skin option etc...

@numerogeek do you have defined the parameter %bower_bin% ? Are you sure that it is valid without quotes?
I mean:
parameters:
    bower_bin: "your custom bower bin for travis"

avanzu_admin_theme:
    bower_bin: "%bower_bin%" # See the quoting here
    use_assetic: true

Probably the problem come from the invalid parameter or the missing quote of the parameter.
Make a composer update to master, and watch in the update, if you get a warning line starting with the text "AvanzuAdminBundle: invalid config"

I tried using xDebug: I don't fall in the catch. My config is valid.
Have you tried locally ? (don't forget to clear the cache before)
As I said in comment in the PR, I doubt that the $container->getExtensionConfig($this->getAlias()); parses anything.
Check the function content :
    public function getExtensionConfig($name)
    {
        if (!isset($this->extensionConfigs[$name])) {
            $this->extensionConfigs[$name] = array();
        }

        return $this->extensionConfigs[$name];
    }

Please consider reopen my PR.

About the catch. it was set in getExtensionConfig() instead processConfiguration() so you didn't get the warning message properly. Already pushed that change (in that part you have reason, so my apologies since I misstakenly believe that was throwing in getExtensionConfig() instead processConfiguration() ).
Even if I thank you your effort to fix it (I always appreciate help fixing things or improving this), unfortunally, your PR don't solve the problem in the right spot, because the config has to be fetch first from getExtensionConfig(), that value is used for processConfiguration as second argument, that will trigger the InvalidConfiguration if there are one (note, trigger by processConfiguration)
The validation will be improved (note: using validateConfiguration()) when I get a stable and 0 issues of this bundle (that will be after 2.0 release, I expect):
See for example other bundles use this:
        $extension = $this->findExtension($name);

        $extensionAlias = $extension->getAlias();
        $configs = $container->getExtensionConfig($extensionAlias);
        $configuration = $extension->getConfiguration($configs, $container);

        $this->validateConfiguration($extension, $configuration);

        $configs = $container->resolveEnvPlaceholders($container->getParameterBag()->resolveValue($configs));

@shakaran Thank you for your feedback.
Could you please show me which bundle implements this kind of configuration ? Because I don't see  where it loads the user's configuration ?

@numerogeek just var_dump() or use xDebug for see the values and you will see the data received in each part of the config bundle.
About the bundles using that, just grep some vendors in your symfony installation by getExtensionConfig() for example:
/vendor/symfony/symfony/src/Symfony/Bundle/FrameworkBundle/Command/ConfigDebugCommand.php
I notice that the problem was that load() method get the config from an initial array parameter, and prepend needs preload the config array. So I think that now should fix your issue with latest commits. Please let me know with latest master.
If a invalid config is set, for example:
avanzu_admin_theme:
    example: true

The warning should be clear like:
AvanzuAdminBundle: invalid config (prepend): Unrecognized option "example" under "avanzu_admin_theme"
    The config options for the bundle AvanzuAdminBundle were skipped
AvanzuAdminBundle: invalid config (load): Unrecognized option "example" under "avanzu_admin_theme"
    The config options for the bundle AvanzuAdminBundle were skipped

@numerogeek I push more fixes, please let me know when you can test again if it is resolved this issue

it's now good for me. Thank you.

@numerogeek thanks! Happy to see that it is already resolved. Please if you can check other issues where I am waiting your feedback (help to test other issues still opened would help me a lot too). So we can release soon a stable release in benefit for all

I have the same error for KNP integration, i tried both to put it directly under "avanzu_admin_theme" and also under "avanzu_admin_theme.options" both of them say "Unrecognized option "..." under "avanzu_admin_theme":
"name": "avanzu/admin-theme-bundle",
            "version": "1.3.8",
            "source": {
                "type": "git",
                "url": "https://github.com/avanzu/AdminThemeBundle.git",
                "reference": "ed9a11f4c002bbc542adb680bddc5222e11e85a6"
            },
            "dist": {
                "type": "zip",
                "url": "https://api.github.com/repos/avanzu/AdminThemeBundle/zipball/ed9a11f4c002bbc542adb680bddc5222e11e85a6",
                "reference": "ed9a11f4c002bbc542adb680bddc5222e11e85a6",
                "shasum": ""
            },

Here is my config:
# Avanzu Admin Theme Bundle
avanzu_admin_theme:
    options:
        knp_menu:
            enable : true
            main_menu: 'main_menu'
            breadcrumb_menu: 'breadcrumb'

authors: benr77 ekussberg numerogeek shakaran

repo: avanzu/AdminThemeBundle


text:
Flexible Locale-dependent number parsing and formatting

Take code from djunits for number parsing and formatting and make even more flexible for generic usage.

The flexible NumberParser class provides many options to parse Strings to numbers (int, long, float, and double). It allows for the use of different Locales, and it can parse in a strict manner (only allowing the exact format that the Locale prescribes) or in a lenient manner (allowing for leading plus sign for the number and leading plus sign for the exponent, and allowing for the wrong case of the exponent character). Both strict and lenient parsing ignores leading and trailing whitespace. The parser also allows for trailing characters (such as units) and keeps a pointer where the first trailing character begins.

The class has been defined to use two ways of defining a parser: The first is a classical manner with a constructor that defines the settings::
   NumberParser np = new NumberParser(true, true);
   String text = "+1.127E3 m/s";
   double d = np.parseDouble(text);
   String unit = text.substring(np.getTrailingPosition()).trim();

After executing:
d = 1127.0
unit = "m/s"

or, for a simple lenient setting without trailing information:
   double d = new NumberParser().parseDouble(text);

Alternatively, chaining can be used:
   double d = new NumberParser().lenient().locale(Locale.US).noTrailing().parseDouble(text);

An instantiated NumberParser can be used multiple times, but the class is not thread-safe.
Information on how Java handles Locales from version 11 onward can be found at https://www.oracle.com/java/technologies/javase/jdk11-suported-locales.html

In the unit tests, an extensive set of right and wrong cases is tested for the locales en-US, fr-FR, nl-NL, and ar-DZ-u-nu-arab. For the last one, the test
  double d = new NumberParser().strict().noTrailing().locale("ar-DZ-u-nu-arab").parseDouble(""١٢٠٠٠٫١٢"");

returns the number 12000.12.
and
  String ar = "\u061c\u002d\u0661\u0662\u0660\u0660\u0660";
  double d = new NumberParser().strict().noTrailing().locale("ar-DZ-u-nu-arab").parseDouble(ar);

returns the number -12000.

A formatter is not necessary, since the Locale-dependent NumberFormat formatter from Java works fine:
  double d = 386124.76;
  System.out.println(NumberFormat.getInstance(Locale.forLanguageTag("en-US")).format(d));
  System.out.println(NumberFormat.getInstance(Locale.forLanguageTag("nl-NL")).format(d));
  System.out.println(NumberFormat.getInstance(Locale.forLanguageTag("fr-FR")).format(d));
  System.out.println(NumberFormat.getInstance(Locale.forLanguageTag("ar-DZ-u-nu-arab")).format(d));

prints:
386,124.76
386.124,76
386 124,76
٣٨٦٬١٢٤٫٧٦

Parser has been created and extensively tested for four languages.

repo: averbraeck/djutils


text:
表达式优先级错误

在语法定义中表达式优先级计算错误。比如
1+23+4
会被计算成
1+(2(3+4))
在 https://ohmlang.github.io/editor/ 的示例代码中
Exp
  = AddExp

AddExp
  = AddExp "+" MulExp  -- plus
  | AddExp "-" MulExp  -- minus
  | MulExp

MulExp
  = MulExp "*" ExpExp  -- times
  | MulExp "/" ExpExp  -- divide
  | ExpExp

ExpExp
  = PriExp "^" ExpExp  -- power
  | PriExp

PriExp
  = "(" Exp ")"  -- paren
  | "+" PriExp   -- pos
  | "-" PriExp   -- neg
  | ident
  | number

能解决这个问题。

Did you mean #let x = 1 + 2 3 + 4 ( there's a space between 2 and 3 )？
It's not a bug, but a wrong statement, which will cause error in most of programming languages,  ex. Javascript.
Besides, this wrong statement won't be treated as 1+(2(3+4)), but two statement (#let x = 1 + 2 and raw text 3 + 4).
I've added a test case in test/parser.test.js, you will get more detail if you search parse computation.
Thanks for feedback!

I forgot add ` on the statement.
There should be a star between 2 and 3.

Oh...I will check it again

Please also make sure expression 3-2-1 works as intended.

authors: Icemic fanthos

repo: avgjs/storyscript


text:
Adding Profanity Checker

Aim

To make a program that can check for NSFW / Abusive words from audio.

Details

The profanity checker program will have a script that can take MIC or Audio file input and use NLP and APIs to process the audio.
It will give a text format output of what is present in the audio.
It will then check the presence of any abusive or NSFW words.
It will have an accuracy of more than 95% with tried and tested datasets to train on.
This will enable the user to integrate this script in their websites or even platforms like Youtube to make the platforms cleaner for the audience.

GO AHEAD @okaditya84

repo: avinashkranjan/Amazing-Python-Scripts


text:
[Script]: AUTOMATED Software testing using python.

Aim
I want to add automated software testing script using python.
Can you please assign me this task under GSSOC'23 contribution @avi
Details
Adding automatic software testing python script
Record

[X] I agree to follow this project's Code of Conduct
[X] I'm a GSSoC'23 contributor
[X] I want to work on this issue

Go Ahead @Kalivarapubindusree

authors: Kalivarapubindusree avinashkranjan


text:
Thread 'main' panicked at 'Bad Request: can't parse entities

Run avkviring/telegram-github-action@v0.0.8
/usr/bin/docker run --name d0729c12f3e5a5bdea436497326361106a5c36_7f6e8c --label d0729c --workdir /github/workspace --rm -e telegram_to -e telegram_token -e event -e INPUT_TELEGRAM_TO -e INPUT_TELEGRAM_TOKEN -e HOME -e GITHUB_JOB -e GITHUB_REF -e GITHUB_SHA -e GITHUB_REPOSITORY -e GITHUB_REPOSITORY_OWNER -e GITHUB_RUN_ID -e GITHUB_RUN_NUMBER -e GITHUB_RETENTION_DAYS -e GITHUB_ACTOR -e GITHUB_WORKFLOW -e GITHUB_HEAD_REF -e GITHUB_BASE_REF -e GITHUB_EVENT_NAME -e GITHUB_SERVER_URL -e GITHUB_API_URL -e GITHUB_GRAPHQL_URL -e GITHUB_WORKSPACE -e GITHUB_ACTION -e GITHUB_EVENT_PATH -e GITHUB_ACTION_REPOSITORY -e GITHUB_ACTION_REF -e GITHUB_PATH -e GITHUB_ENV -e RUNNER_OS -e RUNNER_TOOL_CACHE -e RUNNER_TEMP -e RUNNER_WORKSPACE -e ACTIONS_RUNTIME_URL -e ACTIONS_RUNTIME_TOKEN -e ACTIONS_CACHE_URL -e GITHUB_ACTIONS=true -e CI=true -v "/var/run/docker.sock":"/var/run/docker.sock" -v "/home/runner/work/_temp/_github_home":"/github/home" -v "/home/runner/work/_temp/_github_workflow":"/github/workflow" -v "/home/runner/work/_temp/_runner_file_commands":"/github/file_commands" -v "/home/runner/work/nft_private/nft_private":"/github/workspace" d0729c:12f3e5a5bdea436497326361106a5c36
thread 'main' panicked at 'Bad Request: can't parse entities: Can't find end of the entity starting at byte offset 630', src/telegram.rs:16:19
note: run with RUST_BACKTRACE=1 environment variable to display a backtrace

/master/src/telegram.rs
match result {
    Ok(result) => println!("{:?}", result),
    Err(e) => panic!("{}", e),
};

@avkviring The process crashes 50% of the time. So I understand the problem in stability, and not in the logic of the component.

Hi, It is depend on commit content. I will add some logs, and you can try again if you want.

@avkviring The commit contains the improvements and fixes of the Rust project (.rs) + part of the json commit of about a dozen files for 70 new lines of code. Yes. Add a debugger, let's check again.

@Antz0x0z Please use avkviring/telegram-github-action@issues-15 for action.

repo: avkviring/telegram-github-action


text:
Build a lakehouse demo via hadoop-testing

The demo refers to hudi's official site: https://hudi.apache.org/docs/docker_demo
It involved:

Kafka
Hudi
Spark
Hive
Trino
Kyuubi (plus)

For consideration of scalability, each component has an ansible Role. And connect them via Ansible Playbook.

cc @pan3793

repo: awesome-kyuubi/hadoop-testing


text:
Prevents error if DoesNotExist 'shop-cart'

This allows to launch django-shop without the fixtures, and blow can load the fixtures later for exemple:

Django Smuggler is a pluggable application for Django Web Framework to easily dump/load fixtures via the automatically-generated administration interface. A fixture is file with model data serialized to e.g. JSON or XML that Django knows how to import to the database.

Thanks.
Haven't been aware of django-smuggler yet.

However, why does this raise an error?
If you call templatetag page_url 'shop-cart' as shop_cart_url this shouldn't raise an error, if that page-id doesn't exist.

This happens when we are in debug mode,
https://github.com/divio/django-cms/blob/1c6d9e05279b067e3c8233f01fe78b9900f6ab7e/cms/templatetags/cms_tags.py#L96

authors: haricot jrief

repo: awesto/django-shop


text:
Suggest adding a Restart Hotkey

In the default Runner you can press Ctrl + R to Restart the game, this is very important when testing a game and making changes in the developer and saving it, then re-run the game in runner to test the changes by pressing Ctrl+R.
Currently in FD Ctrl+R will run Restore, which then opens a window to choose file to load. (I don't quite understand what this does, because the folder for a demo it opens does not show .taf files to open??)
I suggest that remap the Ctrl-R key as a Restart hotkey (because Ctrl+R to restart is the norm in the default Runner, those used to it wont get caught out) and the restore hotkey could be changed to Alt+R?
I know there is a 'restart' command that can be typed but a hot-key is so much faster, especially when in the course of an hour i might restart a game 30 times when testing.

Currently in FD Ctrl+R will run Restore, which then opens a window to choose file to load. (I don't quite understand what this does, because the folder for a demo it opens does not show .taf files to open??)

"Restore" is intended to load back a saved game state (a .tas file). I'll consider adding a shortcut for restart as well.

Okay. I wouldn't have guessed that is what Restore meant. 'Load Save' would have made more sense, i am sure that will catch out a lot of users, perhaps it could be changed to 'Restore Save'? but i think Load Save would be more straight forward. Anyway that is my feedback.

"Restore" is the term used by the Inform library, among others, so I hoped it would be familiar enough. (The ADRIFT Runner also understands when you type restore as a command.) I've changed the wording to "Restore a Saved Game".
I've also added a "Restart Game" option mapped to Ctrl+Shift+R.

repo: awlck/frankendrift


text:
AWS Amplify for React SPA: Build gets stuck when extracting the cache.

Environment information
19 2024-07-22T18:24:05.065Z [INFO]: ---- Setting Up SSM Secrets ----
20 2024-07-22T18:24:05.065Z [INFO]: SSM params {"Path":"/amplify/dgp1n8jvmw3zu/main/","WithDecryption":true}
21 2024-07-22T18:24:05.119Z [WARNING]: !Failed to set up process.env.secrets
22 2024-07-22T18:24:06.187Z [INFO]: No live updates for this build run
23 2024-07-22T18:24:06.190Z [INFO]: # Retrieving cache...
24 2024-07-22T18:25:01.871Z [INFO]: # Extracting cache...

Description
It gets stuck at this step:
2024-07-22T18:24:06.190Z [INFO]: # Retrieving cache...
2024-07-22T18:25:01.871Z [INFO]: # Extracting cache...

I am also facing the same issue.

I'm also getting this issue - nothing has changed our side to cause this. Added $(pnpm store path) as per @Jay2113's comment but still not resolved.
Any help?

@Avinash-Ch-Technicolor can you share your Amplify app id?

@iberth-vantiva @Avinash-Ch-Technicolor We have identified the root cause of the issue. Please find the details below:
Amplify experienced a problem extracting cache artifacts for pnpm builds in the regions ca-central-1, eu-south-1, us-east-2, us-east-1, eu-west-1, and ap-southeast-1. The issue has been resolved and the service is operating normally. You can retry any failed deploys from the Amplify Console.
Can you please retry and confirm if you are now unblocked?

@Jay2113 Confirming that this is back to normal now, we are not experiencing this issue anymore.
Thank you so much for the quick action & resolution.

I am closing this thread since the issue has been resolved.

repo: aws-amplify/amplify-backend


text:
fix fast xml parser

Problem
https://github.com/aws-amplify/amplify-backend/security/dependabot/36

Issue number, if available:
Changes

Corresponding docs PR, if applicable:
Validation

Checklist

[ ] If this PR includes a functional change to the runtime behavior of the code, I have added or updated automated test coverage for this change.
[ ] If this PR requires a change to the Project Architecture README, I have included that update in this PR.
[ ] If this PR requires a docs update, I have linked to that docs PR above.
[ ] If this PR modifies E2E tests, makes changes to resource provisioning, or makes SDK calls, I have run the PR checks with the run-e2e label set.

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

Can you run e2e tests on this PR ?


text:
Amplify status without data

Describe the bug
After crashed publish project to aws I had init new amplify configuration
After that I don't seee any data before added to the project by amplify status
Api
Auth
I have these files at the project dir
Screenshots

Desktop (please complete the following information):

OS: Win 10

amplify publish still do not usable for publish project and that is second problem https://github.com/aws-amplify/amplify-js/issues/2938

Let's track your issues with this single issue: https://github.com/aws-amplify/amplify-cli/issues/1129

authors: UnleashedMind emeryaa

repo: aws-amplify/amplify-cli