NIFI-10356: Create GetHubSpot processor

Summary
NIFI-10356
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[x] Pull Request commit message starts with Apache NiFi Jira issue number, as such NIFI-00000

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[x] Pull Request based on current revision of the main branch
[x] Pull Request refers to a feature branch with one commit containing changes

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[x] Build completed using mvn clean install -P contrib-check

[ ] JDK 8
[ ] JDK 11
[ ] JDK 17

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[ ] New dependencies are compatible with the Apache License 2.0 according to the License Policy
[ ] New dependencies are documented in applicable LICENSE and NOTICE files

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[ ] Documentation formatting appears as expected in rendered files

Thanks for the comments @exceptionfactory . I also added Rate Limit handling to the processor.


Failed Migration from Gogs <IP_ADDRESS>1 to Gitea master

Gitea version (or commit ref): a195c3fabeed4136b326ab641460fc30d6feaf01
Git version: 2.6.2
Operating system: CentOS 6
Database (use [x]):

[ ] PostgreSQL
[x] MySQL
[ ] SQLite

Can you reproduce the bug at https://try.gitea.io:

[ ] Yes (provide example URL)
[ ] No
[X] Not relevant

Log gist: https://gist.github.com/fettlaus/e9b7db4ad7a66c28c17c5facf22b84db

Description
When doing a direct upgrade from Gogs <IP_ADDRESS>1 to Gitea master, the migration failed with the attached errorlog. This doesn't happen when migrating from Gogs to Gitea 1.0.1 and then upgrading to Gitea master.

---
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That maybe a migration method bug, both Gitea and Gogs. But I think you can upgrade v1.0.1 and then to master, It will smooth.
Because when you migrate from v7 to v12, but on v9 column external_tracker_url should be created by x.Sync2(), but that not in migrations list.
So I think we have to ask all database schemas changes should add a migration even if x.Sync2 could do that.

@fettlaus please confirm #929 fix this.

Sorry, I am unable to confirm this. I don't have the gogs backup anymore and thus can't revert to the old installation.


Unknown error

I'm not even sure what the error is, but it fails
[2024-12-11 17:41:18,618] [INFO] [real_accelerator.py:219:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-12-11 17:41:20,616] [WARNING] [runner.py:215:fetch_hostfile] Unable to find hostfile, will proceed with training with local resources only.
[2024-12-11 17:41:20,616] [INFO] [runner.py:607:main] cmd = /home/cubeyai/anaconda/envs/diffusion-pipe/bin/python -u -m deepspeed.launcher.launch --world_info=eyJsb2NhbGhvc3QiOiBbMF19 --master_addr=<IP_ADDRESS> --master_port=29500 --enable_each_rank_log=None train.py --deepspeed --config examples/hunyuan_video.toml
[2024-12-11 17:41:21,477] [INFO] [real_accelerator.py:219:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-12-11 17:41:22,750] [INFO] [launch.py:139:main] 0 NCCL_IB_DISABLE=1
[2024-12-11 17:41:22,751] [INFO] [launch.py:139:main] 0 NCCL_P2P_DISABLE=1
[2024-12-11 17:41:22,751] [INFO] [launch.py:146:main] WORLD INFO DICT: {'localhost': [0]}
[2024-12-11 17:41:22,751] [INFO] [launch.py:152:main] nnodes=1, num_local_procs=1, node_rank=0
[2024-12-11 17:41:22,751] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'localhost': [0]})
[2024-12-11 17:41:22,751] [INFO] [launch.py:164:main] dist_world_size=1
[2024-12-11 17:41:22,751] [INFO] [launch.py:168:main] Setting CUDA_VISIBLE_DEVICES=0
[2024-12-11 17:41:22,751] [INFO] [launch.py:256:main] process 562154 spawned with command: ['/home/cubeyai/anaconda/envs/diffusion-pipe/bin/python', '-u', 'train.py', '--local_rank=0', '--deepspeed', '--config', 'examples/hunyuan_video.toml']
[2024-12-11 17:41:23,623] [INFO] [real_accelerator.py:219:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-12-11 17:41:25,527] [INFO] [comm.py:652:init_distributed] cdb=None
[2024-12-11 17:41:25,527] [INFO] [comm.py:683:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl
The config attributes {'tile_sample_min_size': 256} were passed to AutoencoderKLCausal3D, but are not expected and will be ignored. Please verify your config.json configuration file.
2024-12-11 17:41:26.650 | INFO     | hyvideo.text_encoder:load_text_encoder:28 - Loading text encoder model (llm) from: ./models/HY/llava-llama-3-8b-text-encoder-tokenizer
Loading checkpoint shards: 100%|██████████████████████████████████████████████| 4/4 [00:08<00:00,  2.03s/it]
2024-12-11 17:41:38.619 | INFO     | hyvideo.text_encoder:load_text_encoder:50 - Text encoder to dtype: torch.bfloat16
2024-12-11 17:41:38.622 | INFO     | hyvideo.text_encoder:load_tokenizer:64 - Loading tokenizer (llm) from: ./models/HY/llava-llama-3-8b-text-encoder-tokenizer
2024-12-11 17:41:39.068 | INFO     | hyvideo.text_encoder:load_text_encoder:28 - Loading text encoder model (clipL) from: ./models/HY/clip-vit-large-patch14
2024-12-11 17:41:39.378 | INFO     | hyvideo.text_encoder:load_text_encoder:50 - Text encoder to dtype: torch.bfloat16
2024-12-11 17:41:39.379 | INFO     | hyvideo.text_encoder:load_tokenizer:64 - Loading tokenizer (clipL) from: ./models/HY/clip-vit-large-patch14
using video_clip_mode=single_middle
caching latents: Hakos_Baelz
caching latents: Hakos_Baelz
trainable params: 161,218,560 || all params: 12,982,231,104 || trainable%: 1.2418
SEED_LAYERS=False BASE_SEED=1234 SEED_FN=None
Using topology: {ProcessCoord(pipe=0, data=0): 0}
[2024-12-11 17:41:42,605] [INFO] [module.py:396:_partition_layers] Partitioning pipeline stages with method parameters
stage=0 layers=63
     0: InitialLayer
     1: DoubleBlock
     2: DoubleBlock
     3: DoubleBlock
     4: DoubleBlock
     5: DoubleBlock
     6: DoubleBlock
     7: DoubleBlock
     8: DoubleBlock
     9: DoubleBlock
    10: DoubleBlock
    11: DoubleBlock
    12: DoubleBlock
    13: DoubleBlock
    14: DoubleBlock
    15: DoubleBlock
    16: DoubleBlock
    17: DoubleBlock
    18: DoubleBlock
    19: DoubleBlock
    20: DoubleBlock
    21: concatenate_hidden_states
    22: SingleBlock
    23: SingleBlock
    24: SingleBlock
    25: SingleBlock
    26: SingleBlock
    27: SingleBlock
    28: SingleBlock
    29: SingleBlock
    30: SingleBlock
    31: SingleBlock
    32: SingleBlock
    33: SingleBlock
    34: SingleBlock
    35: SingleBlock
    36: SingleBlock
    37: SingleBlock
    38: SingleBlock
    39: SingleBlock
    40: SingleBlock
    41: SingleBlock
    42: SingleBlock
    43: SingleBlock
    44: SingleBlock
    45: SingleBlock
    46: SingleBlock
    47: SingleBlock
    48: SingleBlock
    49: SingleBlock
    50: SingleBlock
    51: SingleBlock
    52: SingleBlock
    53: SingleBlock
    54: SingleBlock
    55: SingleBlock
    56: SingleBlock
    57: SingleBlock
    58: SingleBlock
    59: SingleBlock
    60: SingleBlock
    61: SingleBlock
    62: OutputLayer
[2024-12-11 17:41:48,020] [INFO] [logging.py:128:log_dist] [Rank 0] DeepSpeed info: version=0.16.1, git-hash=unknown, git-branch=unknown
[2024-12-11 17:41:48,021] [INFO] [config.py:733:__init__] Config mesh_device None world_size = 1
[2024-12-11 17:41:48,089] [INFO] [logging.py:128:log_dist] [Rank 0] DeepSpeed Flops Profiler Enabled: False
[2024-12-11 17:41:48,095] [INFO] [logging.py:128:log_dist] [Rank 0] Using client callable to create basic optimizer
[2024-12-11 17:41:48,095] [INFO] [logging.py:128:log_dist] [Rank 0] Removing param_group that has no 'params' in the basic Optimizer
[2024-12-11 17:41:48,130] [INFO] [logging.py:128:log_dist] [Rank 0] DeepSpeed Basic Optimizer = AdamW
[2024-12-11 17:41:48,130] [INFO] [logging.py:128:log_dist] [Rank 0] DeepSpeed Final Optimizer = AdamW
[2024-12-11 17:41:48,130] [INFO] [logging.py:128:log_dist] [Rank 0] DeepSpeed using configured LR scheduler = None
[2024-12-11 17:41:48,130] [INFO] [logging.py:128:log_dist] [Rank 0] DeepSpeed LR Scheduler = None
[2024-12-11 17:41:48,130] [INFO] [logging.py:128:log_dist] [Rank 0] step=0, skipped=0, lr=[2e-05], mom=[0.0]
[2024-12-11 17:41:48,135] [INFO] [config.py:999:print] DeepSpeedEngine configuration:
[2024-12-11 17:41:48,135] [INFO] [config.py:1003:print]   activation_checkpointing_config  {
    "partition_activations": false,
    "contiguous_memory_optimization": false,
    "cpu_checkpointing": false,
    "number_checkpoints": null,
    "synchronize_checkpoint_boundary": false,
    "profile": false
}
[2024-12-11 17:41:48,135] [INFO] [config.py:1003:print]   aio_config ................... {'block_size': 1048576, 'queue_depth': 8, 'thread_count': 1, 'single_submit': False, 'overlap_events': True, 'use_gds': False}
[2024-12-11 17:41:48,135] [INFO] [config.py:1003:print]   amp_enabled .................. False
[2024-12-11 17:41:48,135] [INFO] [config.py:1003:print]   amp_params ................... False
[2024-12-11 17:41:48,135] [INFO] [config.py:1003:print]   autotuning_config ............ {
    "enabled": false,
    "start_step": null,
    "end_step": null,
    "metric_path": null,
    "arg_mappings": null,
    "metric": "throughput",
    "model_info": null,
    "results_dir": "autotuning_results",
    "exps_dir": "autotuning_exps",
    "overwrite": true,
    "fast": true,
    "start_profile_step": 3,
    "end_profile_step": 5,
    "tuner_type": "gridsearch",
    "tuner_early_stopping": 5,
    "tuner_num_trials": 50,
    "model_info_path": null,
    "mp_size": 1,
    "max_train_batch_size": null,
    "min_train_batch_size": 1,
    "max_train_micro_batch_size_per_gpu": 1.024000e+03,
    "min_train_micro_batch_size_per_gpu": 1,
    "num_tuning_micro_batch_sizes": 3
}
[2024-12-11 17:41:48,135] [INFO] [config.py:1003:print]   bfloat16_enabled ............. False
[2024-12-11 17:41:48,135] [INFO] [config.py:1003:print]   bfloat16_immediate_grad_update  False
[2024-12-11 17:41:48,135] [INFO] [config.py:1003:print]   checkpoint_parallel_write_pipeline  False
[2024-12-11 17:41:48,135] [INFO] [config.py:1003:print]   checkpoint_tag_validation_enabled  True
[2024-12-11 17:41:48,135] [INFO] [config.py:1003:print]   checkpoint_tag_validation_fail  False
[2024-12-11 17:41:48,135] [INFO] [config.py:1003:print]   comms_config ................. <deepspeed.comm.config.DeepSpeedCommsConfig object at 0x7fc13884dcd0>
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   communication_data_type ......  False
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   curriculum_params_legacy ..... False
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   data_efficiency_config ....... {'enabled': False, 'seed': 1234, 'data_sampling': {'enabled': False, 'num_epochs': 1000, 'num_workers': 0, 'curriculum_learning': {'enabled': False}}, 'data_routing': {'enabled': False, 'random_ltd': {'enabled': False, 'layer_token_lr_schedule': {'enabled': False}}}}
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   data_efficiency_enabled ...... False
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   dataloader_drop_last ......... False
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   disable_allgather ............ False
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   dump_state ................... False
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   dynamic_loss_scale_args ...... None
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   eigenvalue_enabled ........... False
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   eigenvalue_gas_boundary_resolution  1
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   eigenvalue_layer_name ........ bert.encoder.layer
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   eigenvalue_layer_num ......... 0
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   eigenvalue_max_iter .......... 100
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   eigenvalue_stability ......... 1e-06
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   eigenvalue_tol ............... 0.01
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   eigenvalue_verbose ........... False
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   elasticity_enabled ........... False
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   flops_profiler_config ........ {
    "enabled": false,
    "recompute_fwd_factor": 0.0,
    "profile_step": 1,
    "module_depth": -1,
    "top_modules": 1,
    "detailed": true,
    "output_file": null
}
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   fp16_auto_cast ............... None
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   fp16_enabled ................. False
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   fp16_master_weights_and_gradients  False
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   global_rank .................. 0
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   grad_accum_dtype ............. None
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   gradient_accumulation_steps .. 4
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   gradient_clipping ............ 1.0
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   gradient_predivide_factor .... 1.0
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   graph_harvesting ............. False
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   hybrid_engine ................ enabled=False max_out_tokens=512 inference_tp_size=1 release_inference_cache=False pin_parameters=True tp_gather_partition_size=8
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   initial_dynamic_scale ........ 65536
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   load_universal_checkpoint .... False
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   loss_scale ................... 0
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   memory_breakdown ............. False
[2024-12-11 17:41:48,136] [INFO] [config.py:1003:print]   mics_hierarchial_params_gather  False
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   mics_shard_size .............. -1
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   monitor_config ............... tensorboard=TensorBoardConfig(enabled=False, output_path='', job_name='DeepSpeedJobName') comet=CometConfig(enabled=False, samples_log_interval=100, project=None, workspace=None, api_key=None, experiment_name=None, experiment_key=None, online=None, mode=None) wandb=WandbConfig(enabled=False, group=None, team=None, project='deepspeed') csv_monitor=CSVConfig(enabled=False, output_path='', job_name='DeepSpeedJobName')
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   nebula_config ................ {
    "enabled": false,
    "persistent_storage_path": null,
    "persistent_time_interval": 100,
    "num_of_version_in_retention": 2,
    "enable_nebula_load": true,
    "load_path": null
}
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   optimizer_legacy_fusion ...... False
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   optimizer_name ............... None
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   optimizer_params ............. None
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   pipeline ..................... {'stages': 'auto', 'partition': 'best', 'seed_layers': False, 'activation_checkpoint_interval': 0, 'pipe_partitioned': True, 'grad_partitioned': True}
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   pld_enabled .................. False
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   pld_params ................... False
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   prescale_gradients ........... False
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   scheduler_name ............... None
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   scheduler_params ............. None
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   seq_parallel_communication_data_type  torch.float32
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   sparse_attention ............. None
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   sparse_gradients_enabled ..... False
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   steps_per_print .............. 1
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   timers_config ................ enabled=True synchronized=True
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   train_batch_size ............. 4
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   train_micro_batch_size_per_gpu  1
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   use_data_before_expert_parallel_  False
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   use_node_local_storage ....... False
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   wall_clock_breakdown ......... False
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   weight_quantization_config ... None
[2024-12-11 17:41:48,137] [INFO] [config.py:1003:print]   world_size ................... 1
[2024-12-11 17:41:48,138] [INFO] [config.py:1003:print]   zero_allow_untested_optimizer  False
[2024-12-11 17:41:48,138] [INFO] [config.py:1003:print]   zero_config .................. stage=0 contiguous_gradients=True reduce_scatter=True reduce_bucket_size=500000000 use_multi_rank_bucket_allreduce=True allgather_partitions=True allgather_bucket_size=500000000 overlap_comm=False load_from_fp32_weights=True elastic_checkpoint=False offload_param=None offload_optimizer=None sub_group_size=1000000000 cpu_offload_param=None cpu_offload_use_pin_memory=None cpu_offload=None prefetch_bucket_size=50000000 param_persistence_threshold=100000 model_persistence_threshold=9223372036854775807 max_live_parameters=1000000000 max_reuse_distance=1000000000 gather_16bit_weights_on_model_save=False module_granularity_threshold=0 use_all_reduce_for_fetch_params=False stage3_gather_fp16_weights_on_model_save=False ignore_unused_parameters=True legacy_stage1=False round_robin_gradients=False zero_hpz_partition_size=1 zero_quantized_weights=False zero_quantized_nontrainable_weights=False zero_quantized_gradients=False mics_shard_size=-1 mics_hierarchical_params_gather=False memory_efficient_linear=True pipeline_loading_checkpoint=False override_module_apply=True
[2024-12-11 17:41:48,138] [INFO] [config.py:1003:print]   zero_enabled ................. False
[2024-12-11 17:41:48,138] [INFO] [config.py:1003:print]   zero_force_ds_cpu_optimizer .. True
[2024-12-11 17:41:48,138] [INFO] [config.py:1003:print]   zero_optimization_stage ...... 0
[2024-12-11 17:41:48,138] [INFO] [config.py:989:print_user_config]   json = {
    "train_micro_batch_size_per_gpu": 1,
    "gradient_accumulation_steps": 4,
    "gradient_clipping": 1.0,
    "steps_per_print": 1
}
[2024-12-11 17:41:48,138] [INFO] [engine.py:105:__init__] CONFIG: micro_batches=4 micro_batch_size=1
[2024-12-11 17:41:48,138] [INFO] [engine.py:146:__init__] is_pipe_partitioned= False is_grad_partitioned= False
[2024-12-11 17:41:48,160] [INFO] [engine.py:165:__init__] RANK=0 STAGE=0 LAYERS=63 [0, 63) STAGE_PARAMS=161218560 (161.219M) TOTAL_PARAMS=161218560 (161.219M) UNIQUE_PARAMS=161218560 (161.219M)
[rank0]: Traceback (most recent call last):
[rank0]:   File "/home/cubeyai/diffusion-pipe/train.py", line 462, in <module>
[rank0]:     loss = model_engine.train_batch().item()
[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "/home/cubeyai/anaconda/envs/diffusion-pipe/lib/python3.12/site-packages/deepspeed/runtime/pipe/engine.py", line 389, in train_batch
[rank0]:     self._exec_schedule(sched)
[rank0]:   File "/home/cubeyai/anaconda/envs/diffusion-pipe/lib/python3.12/site-packages/deepspeed/runtime/pipe/engine.py", line 1422, in _exec_schedule
[rank0]:     self._exec_instr(**cmd.kwargs)
[rank0]:   File "/home/cubeyai/anaconda/envs/diffusion-pipe/lib/python3.12/site-packages/deepspeed/runtime/pipe/engine.py", line 886, in _exec_load_micro_batch
[rank0]:     batch = self._next_batch()
[rank0]:             ^^^^^^^^^^^^^^^^^^
[rank0]:   File "/home/cubeyai/anaconda/envs/diffusion-pipe/lib/python3.12/site-packages/deepspeed/runtime/pipe/engine.py", line 701, in _next_batch
[rank0]:     batch = next(self.data_iterator)
[rank0]:             ^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "/home/cubeyai/diffusion-pipe/utils/dataset.py", line 658, in __next__
[rank0]:     self.next_micro_batch = next(self.data)
[rank0]:                             ^^^^^^^^^^^^^^^
[rank0]: StopIteration
[2024-12-11 17:42:01,124] [INFO] [launch.py:319:sigkill_handler] Killing subprocess 562154
[2024-12-11 17:42:01,170] [ERROR] [launch.py:325:sigkill_handler] ['/home/cubeyai/anaconda/envs/diffusion-pipe/bin/python', '-u', 'train.py', '--local_rank=0', '--deepspeed', '--config', 'examples/hunyuan_video.toml'] exits with return code = 1

The clue seems to be where it logs "caching latents:" but then doesn't go on to log the size buckets it's caching under that. It's like it can't find any images or videos in the directory you pointed it to, or it is skipping those files because it can't open them, or something.
Do media files and caption .txt files exist in the directory you configured in the dataset TOML file?
Is it images, or videos?
Is this training run loaded from cache (i.e. did you previously run it and it cached everything then)? If you ever ran it against an empty directory, it might make empty cache files, which it would always reuse. You would have to delete the cache dir or use --regenerate_cache flag.
I will at least add a check to the code so it errors out with a message that it found no images.

The clue seems to be where it logs "caching latents:" but then doesn't go on to log the size buckets it's caching under that. It's like it can't find any images or videos in the directory you pointed it to, or it is skipping those files because it can't open them, or something.
Do media files and caption .txt files exist in the directory you configured in the dataset TOML file? Is it images, or videos? Is this training run loaded from cache (i.e. did you previously run it and it cached everything then)? If you ever ran it against an empty directory, it might make empty cache files, which it would always reuse. You would have to delete the cache dir or use --regenerate_cache flag.
I will at least add a check to the code so it errors out with a message that it found no images.

sorry as I was away, I found the cause to be that I ran the file once before to test, I think I made a change to the dataset and that caused the error. side question, I have a checkpoint that is saved but I think I made the epoch way too large, is there anyway to convert the checkpoint to a safetensor?

If I try to change the num_repeats, the same issue as above occurs.

In general, changing anything (especially about the dataset and its config) and then trying to resume will cause problems. If you changed something, when in doubt use --regenerate_cache and make it a fresh training run.

is there anyway to convert the model_states to a safetensor

Not easily. If you can code, you can try adapting this: https://github.com/tdrussell/qlora-pipe/blob/main/convert_ds_checkpoint_to_lora.py
Long ago I screwed up my first training runs with another training script and made this to convert the Deepspeed checkpoints to a lora. I highly doubt it works out of the box for this case though, but that's the general technique.

Yeah I can't really so I'll just lose the 4 hours, but thanks for the advice 👍

also, I don't think multiple paths are working, I tried one with two folders and got [rank0]: ValueError: Duplicate keys!

What does your dataset config look like? It should be something like this:
[[directory]]
path = '/path/to/something'
[[directory]]
path = '/path/to/something_else'
I am successfully training with multiple paths like this.


what  is right way handling binary message from client

What operating system are you running?

Windows

Are you running any CPU architechute out of the normal?

I run 64-bit in the year 2017

What platform/language are you using?

C++

Are you using SSL, if so, how?
no
What version of uws are you using?

master

What features of µWS are involved in the issue?

Server support (WebSocket)

How does the issue reproduce?

All the time

Can you show me some short code that triggers your issue or any other important information?

im sending binary massage from HTML5 client
the massage recived fine in the server BUT it reviced as string that include the header
what is the proper way to get only the massage recived from the client in server
for example im receiving the massage in the function :
h.onMessage([](uWS::WebSocket<uWS::SERVER> ws, char *message, size_t length, uWS::OpCode opCode) {
		if (opCode == uWS::OpCode::BINARY)
		{
			printf("%s\n", message);
			char *messageToClient = "{ \"msg\":\"send from server\"}";
			size_t messageLength = strlen(messageToClient);

			uWS::WebSocket<uWS::SERVER>::PreparedMessage *prepared =
									ws.prepareMessage(messageToClient, messageLength, uWS::OpCode::BINARY, false, nullptr);
			ws.sendPrepared(prepared, nullptr);
			ws.finalizeMessage(prepared);

		}

and the printed massage is :
{"msg":"Hello From Client"}┐╛'G   ost:3000
connection: Upgrade
pragma: no-cache
cache-control: no-cache
upgrade: websocket
origin: http://<IP_ADDRESS>:8887
sec-websocket-version: 13
user-agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.87 Safari/537.36
accept-encoding: gzip, deflate, sdch, br
accept-language: en-US,en;q=0.8,he;q=0.6
sec-websocket-key: 1gGIb49pUMGRSLv+246kqg==
sec-websocket-extensions: permessage-deflate; client_max_window_bits

to get the string : {"msg":"Hello From Client"}
Do i need to do my own string manipulation and extract the massage or is there any more officiant way with build in functions ?

Not all char pointers point to 0-terminated strings. You can only read length amount of bytes from the address given in message. You also don't need to prepare a message if you only are to send it once. Just call ws.send directly. Prepared messages are when you send one message to many recipients or send a batch of messages.

Thanks for the fast replay , so if I understand I need to extract the json from the client , am I right ?

This is not an issue with uws

Hey , its not issue i just try to understand what you did .
as i see that you are sending the length of the string massage itself which can be extract from the
massage pointer like this :
std::string(message, length)
but what about other parameters which has been send in the header how can i get them also ? (loop the char ?)
Thanks

Hey meiry, I'm in exactly the same spot right now. Did you end up coming up with a solution? We can discuss further via email if you wish.


GSD Request

--- GSD JSON ---
{
  "vendor_name": "Linux",
  "product_name": "Kernel",
  "product_version": "versions from v5.8 to before v5.15.19",
  "vulnerability_type": "unspecified",
  "affected_component": "unspecified",
  "attack_vector": "unspecified",
  "impact": "unspecified",
  "credit": "",
  "references": [
    "https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git/commit/?id=4259ff7ae509ed880b3a7bb685972c3a3bf4b74b",
    "https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git/commit/?id=8f069f6dde518dfebe86e848508c07e497bd9298"
  ],
  "extended_references": [
    {
      "type": "commit",
      "value": "4259ff7ae509ed880b3a7bb685972c3a3bf4b74b",
      "note": "introduced"
    },
    {
      "type": "commit",
      "value": "8f069f6dde518dfebe86e848508c07e497bd9298",
      "note": "fixed"
    }
  ],
  "reporter": "joshbressers",
  "reporter_id": 1692786,
  "notes": "",
  "description": "drm/msm/dpu: invalid parameter check in dpu_setup_dspp_pcc\n\nThis is an automated ID intended to aid in discovery of potential security vulnerabilities. The actual impact and attack plausibility have not yet been proven.\nThis ID is fixed in Linux Kernel version v5.15.19 by commit 8f069f6dde518dfebe86e848508c07e497bd9298, it was introduced in version v5.8 by commit 4259ff7ae509ed880b3a7bb685972c3a3bf4b74b. For more details please see the references link."
}
--- GSD JSON ---

This issue has been assigned GSD-2022-1000265


Support .ko.yaml while in subdir

Today if I invoke ko apply -f foo/ while in a subdirectory bar/ then it is possible that a .ko.yaml file that's a sibling of bar/ won't be picked up because we (currently) only look at siblings of foo/.
Fortunately, AddConfigPath seems to support multiple invocations, so we can crawl the directory hierarchy from the current working directory to populate the path.
I think we want this here: https://github.com/google/ko/blob/d45c5277500220120e9196f431856c0cdd83e92b/pkg/commands/config.go#L104

Hey @mattmoor I'd like to take this one up but before that I want to clarify with you. Let's say I have this structure:
- foo
- | - .ko.yaml
- | - k8s.yaml
- | - bar
- | - | - k8s_inside_bar.yaml
- | - | - .ko.yaml

Are we expecting to use foo/.ko.yaml for foo/k8s.yaml only and then use foo/bar/.ko.yaml for foo/bar/k8s_inside_bar.yaml?
Or are we using only either one of foo/.ko.yaml or foo/bar/.ko.yaml (if this is the case, which one has higher priority)?

I think this could spiral quickly, so I think as a first increment let's start with three simple pieces:

Log if/where .ko.yaml is being read from,
Support a flag to override that,
Walk up the directory hierarchy and pick the first (vs. today, which only does current dir)

I think this balances clarity and simplicity.  WDYT?

I'm totally behind reading from only one .ko.yaml  as I love to keep things simple. One question though, by "walking up", you mean we search parent directories? If that's the case, I'm seeing some complexity on how we determine when to stop searching?

I'd probably do the simple thing: keep going until you hit the root, or start getting permissions errors 🤷

I'd probably do the simple thing: keep going until you hit the root, or start getting permissions errors 🤷

One edge case that might end up confusing to end users (small problem since we're logging the location out but I'd still like to raise it): Say I have project2 as a subdir in project1, something like:
|- project1
|- .ko.yaml
|- project2
|- |- k8s.yaml

Now if I run ko apply -f k8s.yaml inside project1/project2 with the intention of using environment variables, I would be out of luck because the config (with the above-discussed behavior) would be read from project1/.ko.yaml.
I understand that the above scenario is an extreme one and most likely would not happen for majority of our users, but I'd still like to check if it's small enough for us to ignore. Also, we might need a flag value to indicate not reading from .ko.yaml for the mentioned scenario

I think this could spiral quickly, so I think as a first increment let's start with three simple pieces:

Log if/where .ko.yaml is being read from,
Support a flag to override that,
Walk up the directory hierarchy and pick the first (vs. today, which only does current dir)

I think this balances clarity and simplicity. WDYT?

I'm gonna implemented with this strategy 👍


String data, right truncation

2020-12-03T13:05:09+00:00 - WARN - State: 01000, Native error: 5701, Message: [Microsoft][ODBC Driver 17 for SQL Server][SQL Server]Changed database context to 'master'.
2020-12-03T13:05:09+00:00 - WARN - State: 01000, Native error: 5703, Message: [Microsoft][ODBC Driver 17 for SQL Server][SQL Server]Changed language setting to us_english.
2020-12-03T13:05:09+00:00 - INFO - Batch size set to 100000
2020-12-03T13:05:09+00:00 - DEBUG - ODBC column description for column 1: ColumnDescription { name: [73, 100], data_type: Numeric { precision: 15, scale: 1 }, nullable: Nullable }
2020-12-03T13:05:09+00:00 - DEBUG - ODBC buffer description for column 1: BufferDescription { nullable: true, kind: Text { max_str_len: 17 } }
2020-12-03T13:05:09+00:00 - DEBUG - ODBC column description for column 2: ColumnDescription { name: [70, 105, 114, 115, 116, 78, 97, 109, 101], data_type: Other { data_type: SqlDataType(-9), column_size: 40, decimal_digits: 0 },
nullable: NoNulls }
2020-12-03T13:05:09+00:00 - DEBUG - ODBC buffer description for column 2: BufferDescription { nullable: true, kind: Text { max_str_len: 40 } }
2020-12-03T13:05:09+00:00 - DEBUG - ODBC column description for column 3: ColumnDescription { name: [76, 97, 115, 116, 78, 97, 109, 101], data_type: Other { data_type: SqlDataType(-9), column_size: 40, decimal_digits: 0 },
nullable: NoNulls }
2020-12-03T13:05:09+00:00 - DEBUG - ODBC buffer description for column 3: BufferDescription { nullable: true, kind: Text { max_str_len: 40 } }
2020-12-03T13:05:09+00:00 - DEBUG - ODBC column description for column 4: ColumnDescription { name: [67, 105, 116, 121], data_type: Other { data_type: SqlDataType(-9), column_size: 40, decimal_digits: 0 }, nullable: Nullable }
2020-12-03T13:05:09+00:00 - DEBUG - ODBC buffer description for column 4: BufferDescription { nullable: true, kind: Text { max_str_len: 40 } }
2020-12-03T13:05:09+00:00 - DEBUG - ODBC column description for column 5: ColumnDescription { name: [67, 111, 117, 110, 116, 114, 121], data_type: Other { data_type: SqlDataType(-9), column_size: 40, decimal_digits: 0 },
nullable: Nullable }
2020-12-03T13:05:09+00:00 - DEBUG - ODBC buffer description for column 5: BufferDescription { nullable: true, kind: Text { max_str_len: 40 } }
2020-12-03T13:05:09+00:00 - DEBUG - ODBC column description for column 6: ColumnDescription { name: [80, 104, 111, 110, 101], data_type: Other { data_type: SqlDataType(-9), column_size: 20, decimal_digits: 0 }, nullable:
Nullable }
2020-12-03T13:05:09+00:00 - DEBUG - ODBC buffer description for column 6: BufferDescription { nullable: true, kind: Text { max_str_len: 20 } }
2020-12-03T13:05:09+00:00 - DEBUG - ODBC column description for column 7: ColumnDescription { name: [71, 101, 111, 109, 101, 116, 114, 121], data_type: Other { data_type: SqlDataType(-151), column_size: 0, decimal_digits: 0 },
nullable: Nullable }
2020-12-03T13:05:09+00:00 - DEBUG - ODBC buffer description for column 7: BufferDescription { nullable: true, kind: Text { max_str_len: 0 } }
2020-12-03T13:05:45+00:00 - WARN - State: 01004, Native error: 0, Message: [Microsoft][ODBC Driver 17 for SQL Server]String data, right truncation
2020-12-03T13:05:45+00:00 - WARN - State: 01004, Native error: 0, Message: [Microsoft][ODBC Driver 17 for SQL Server]String data, right truncation

Then I get around 300.000 errors like this
2020-12-03T13:05:45+00:00 - WARN - State: 01004, Native error: 0, Message: [Microsoft][ODBC Driver 17 for SQL Server]String data, right truncation
2020-12-03T13:05:45+00:00 - WARN - State: 01004, Native error: 0, Message: [Microsoft][ODBC Driver 17 for SQL Server]String data, right truncation
2020-12-03T13:05:45+00:00 - WARN - State: 01004, Native error: 0, Message: [Microsoft][ODBC Driver 17 for SQL Server]String data, right truncation
2020-12-03T13:05:45+00:00 - WARN - State: 01004, Native error: 0, Message: [Microsoft][ODBC Driver 17 for SQL Server]String data, right truncation
2020-12-03T13:05:45+00:00 - WARN - State: 01004, Native error: 0, Message: [Microsoft][ODBC Driver 17 for SQL Server]String data, right truncation
2020-12-03T13:05:45+00:00 - WARN - State: 01004, Native error: 0, Message: [Microsoft][ODBC Driver 17 for SQL Server]String data, right truncation
2020-12-03T13:05:45+00:00 - WARN - State: 01004, Native error: 0, Message: [Microsoft][ODBC Driver 17 for SQL Server]String data, right truncation
2020-12-03T13:05:45+00:00 - WARN - State: 01004, Native error: 0, Message: [Microsoft][ODBC Driver 17 for SQL Server]String data, right truncation
2020-12-03T13:05:45+00:00 - WARN - State: 01004, Native error: 0, Message: [Microsoft][ODBC Driver 17 for SQL Server]String data, right truncation

My guess is that it has to do with conversion of the MSSQL data type Geography to Utf8 Byte Array?
Originally posted by @Htorne in https://github.com/pacman82/odbc2parquet/issues/16#issuecomment-737977233

@Htorne , we should find out why this is happening. For once, truncated strings could mean a loss of data and there is also the thing that to transfer that many diagnostic records from server to client takes a long time. How long did it take for you to execute this query?

Since the messages generated by the driver do not contain a column number we could test which column it is, by only Selecting one column at a time.

Let's see what types we have here:

Numeric with scale 1. Wanted to map these properly to decimal anyway
-9: These seem to be Wide Character Columns on the Database. Likely UCS2. Don't have a test for these yet. Maybe the driver does report the length to represent these in characters, rather than in bytes. A UTF-8 char might take up to 6Bytes of space so somthing might be coing on here. I can write a test for this though.
-151: I'd have to look this up. Could you tell me what the type of the last column is?

Column length seems to be reported in characters, rather than in bytes fo the target encoding.

Your suggestion, that it is the geometry column is most likely right. As is visible in the log messages you posted, the driver reported 0, which is MS SQL Server specific to indicate that the user defined type is unlimited in size. The last version of odbc2parquet took the zero litterally however and allocated a buffer which could not fit a single char per row. There is now a new version 0.5.0 which will only log one warning about ignoring this column.
Other improvements which might be interssting to you. The decimal column you have should now be properly mapped to decimal, as support has been increased beyond decimals with scale 0. There is also extra space allocated for text columns, but I doubt you've hit any issues there.
If my local test setup is any indication, the new version might run significantly faster, as the server does no longer need to generate that many diagnostic messages.
If ignoring the "strange" column is not good enough for your use case please open a new issue stating the exact column type and use case.

@Htorne Closing this issue. I do not know the exact type of the column which caused you the warnings, but I know I fixed something ;-)


[release-0.59] Fix VMI status.GuestOSInfo

What this PR does / why we need it:
Manual cherry-pick of PRs #10898 and #10916.
Which issue(s) this PR fixes (optional, in fixes #<issue number>(, fixes #<issue_number>, ...) format, will close the issue(s) when PR gets merged):
Fixes #
Special notes for your reviewer:
Checklist
This checklist is not enforcing, but it's a reminder of items that could be relevant to every PR.
Approvers are expected to review this list.

[ ] Design: A design document was considered and is present (link) or not required
[X] PR: The PR description is expressive enough and will help future contributors
[X] Code: Write code that humans can understand and Keep it simple
[ ] Refactor: You have left the code cleaner than you found it (Boy Scout Rule)
[ ] Upgrade: Impact of this change on upgrade flows was considered and addressed if required
[X] Testing: New code requires new unit tests. New features and bug fixes require at least on e2e test
[ ] Documentation: A user-guide update was considered and is present (link) or not required. You want a user-guide update if it's a user facing feature / API change.
[ ] Community: Announcement to kubevirt-dev was considered

Release note:

Fix VMI status.GuestOSInfo

/cc @Barakmor1 @enp0s3

/cc @Barakmor1 @enp0s3

/retest-required

/approve


Dependency installation error on Ubuntu

Dear Naszilla team,
I am getting this error when I try to install. It seems that pip can no longer find tensorflow 1.14.0 in the standard pathways. This is an Ubuntu 18.04 64 bit system witha P100 gpu.
(base) dedey@ubuntubox:~/naszilla$ cat requirements.txt | xargs -n 1 -L 1 pip install
ERROR: Could not find a version that satisfies the requirement tensorflow-gpu==1.14.0
ERROR: No matching distribution found for tensorflow-gpu==1.14.0
ERROR: Could not find a version that satisfies the requirement tensorflow==1.14.0
ERROR: No matching distribution found for tensorflow==1.14.0

Hi Dey, thanks for your interest.
I believe this repository works for tensorflow-gpu==1.15.4 as well (and likely all versions between 1.14.0 and 1.15.4).
Unfortunately it does not work with tensorflow 2 because the requirement nasbench does not work with tensorflow 2.
I hope that is helpful. One more thing - all code in the naszilla/naszilla repository runs just fine on a CPU, thanks to the NAS-Bench-101/201/301 datasets!


add file for project

Implemented all fuctionality in project please accept my pull/request regarding hacktoberfest.

After reviewing and testing  code of @guptasakshi28  I accepted your pull -request regarding hacktoberfest-accepted


for code coverage we want all log-strings to be created and later discarded.

My first intuition is that this is not a good idea. If the log string is not created because the condition is false, that means there's a code path that's never tested. A real improvement to test coverage would be to extend the tests so this path is executed. This change mostly just covers it up. And as @jsteemann pointed out, it may break things - or it may as well work when the condition is false, but not when its true.
I'm aware that we can't make any universal statement about whether this is a good idea or not, and it will vary in different individual cases. However, I think overall its better to leave it be.

In the end this patch makes them being produced - and tested - hence coverage isn't betrayed.
If something is really wrong here, it will show up in these testruns.
The suggestion was, to also enable this in i.e. ASAN runs, so if it has uninitialized memory access, it will show up.
I modified the IF macro to also always be executed, but log TRACE so it will also be discarded later on.

In the end this patch makes them being produced - and tested - hence coverage isn't betrayed.
If something is really wrong here, it will show up in these testruns.
The suggestion was, to also enable this in i.e. ASAN runs, so if it has uninitialized memory access, it will show up.
I modified the IF macro to also always be executed, but log TRACE so it will also be discarded later on.

That sounds sensible.

http://jenkins01.arangodb.biz:8080/view/PR/job/arangodb-matrix-pr/12801/

testrun blue.


Fix focus behavior and provided thumb and focus color aren't applied Cupertino variant of Switch.adaptive

fixes https://github.com/flutter/flutter/issues/126637
fixes https://github.com/flutter/flutter/issues/126669
To be merged after https://github.com/flutter/flutter/pull/126684
Description

Fix the Cupertino variant of Switch.adaptive requires two tab key presses to focus.
Fix thumbColor & focusColor aren't applied.

Before
Requires two tab presses to focus. and thumbColor & focusColor aren't applied.
https://github.com/flutter/flutter/assets/48603081/24635551-0794-443f-8320-32fdaa5de57a
After
Single tab key to focus (no additional focus node) and thumbColor & focusColor are applied.
https://github.com/flutter/flutter/assets/48603081/9bf42fd8-c7e0-475a-b933-192a94650b0c
Pre-launch Checklist

[x] I read the Contributor Guide and followed the process outlined there for submitting PRs.
[x] I read the Tree Hygiene wiki page, which explains my responsibilities.
[x] I read and followed the Flutter Style Guide, including Features we expect every widget to implement.
[x] I signed the CLA.
[x] I listed at least one issue that this PR fixes in the description above.
[ ] I updated/added relevant documentation (doc comments with ///).
[x] I added new tests to check the change I am making, or this PR is test-exempt.
[x] All existing and new tests are passing.

If you need help, consider asking for advice on the #hackers-new channel on Discord.

@MitchellGoodwin this is good to go now


Question

Thank you for the update for CSS. I have a question about the un-named version. When I do bower update I don't get that version. Does it need to be versioned with a number beyond 0.9.5?
When I run bower info kjvelarde-angular-multiselectsearchtree
I get
Available versions:
-0.9.0
-0.8.5
-0.8.0

That was weird; apparently v1.0/v1.1 wasn't the right way to version it? I had to do a few test with versioning.
The latest should be able in the repo now as v1.1.0.
Thanks for letting me know about the issue.


Enhancement- Audio  for a chapter continues to play even on switching to next chapter

-Enhancement : If an audio file is playing (John1) and if we switch to the next chapter, the audio of John 2 continues to play . (To be discussed in meeting whether we should continue to play the audio or pause whenever user switches the chapter.)

@LijuJacob08  please share the current status of this sisue

Issue is till there.

moving to in progress


Catch exception and report it when making a network request with invalid URL on Android

Currently if you invoke fetch() with an invalid URL ("aaa" for
example) you cannot catch the error in javascript since it's not
reported. Instead the entire app crashes.
Fixes #7436 and #18087
Hopefully.

Motivation
Fix using fetch on Android with user generated input.
Test Plan
Added relevant unit test
./scripts/run-android-local-unit-tests.sh all pass
Release Notes
[ANDROID] [BUGFIX] [fetch] - Allow "unexpected url" exception to be caught on Android when using fetch

@laurent22 I'm not sure that's necessary. We're just testing that the error gets reported and not the actual URL builder itself. If it's any invalid URL it should get reported.

We also want to add check for valid URL on the JS side to synchronously report the error, but this is a good start.
@facebook-github-bot shipit


Fix xsuspender

I wonder how this even worked before.

cc the author @offlinehacker . @fehnomenal please rewrite the commit messages as xsuspender: blabla

@fehnomenal thanks for doing this. I've just tried out the module myself and ended up with the same patch. Was wondering too.

Just reworded the commits

Thanks! Rebased to master in 2029e104d45e291cdcc2609893b026362497f4ce.


Adding MemoryPointer to public API

Feature request

The MemoryPointer class is very useful. However IIUC this is technically part of the private API. It would be useful to have it in the public API (namely documented and easily accessible from numba.cuda).

@esc I think so, in case nbep 7 changes before it is merged (probably not likely to not expose the MemoryPointer in it, but just in case)

@gmarkall 👍

This is resolved by #5328 which added MemoryPointer, AutoFreePointer, PinnedMemory and MappedMemory to the public API as part of NBEP 7, External Memory Management Plugins.


Is PythonCall.jl thread safe?

When having JULIA_NUM_THREADS>1 and call jax from Julia with PythonCall.jl I occasionally get:
2023-02-23 20:56:02.532960: F external/org_tensorflow/tensorflow/compiler/xla/python/py_array.cc:392] Check failed: PyGILState_Check()

signal (6): Aborted
in expression starting at [REDACTED]
pthread_kill at /lib/x86_64-linux-gnu/libc.so.6 (unknown line)
raise at /lib/x86_64-linux-gnu/libc.so.6 (unknown line)
abort at /lib/x86_64-linux-gnu/libc.so.6 (unknown line)
_ZN3tsl8internal15LogMessageFatalD1Ev at /home/circleci/.pyenv/versions/3.11.2/lib/python3.11/site-packages/jaxlib/xla_extension.so (unknown line)
_ZN3xla15PyArray_StorageD2Ev.cold at /home/circleci/.pyenv/versions/3.11.2/lib/python3.11/site-packages/jaxlib/xla_extension.so (unknown line)
PyArray_tp_dealloc at /home/circleci/.pyenv/versions/3.11.2/lib/python3.11/site-packages/jaxlib/xla_extension.so (unknown line)
Py_DecRef at /home/circleci/.julia/packages/PythonCall/ZzOaq/src/cpython/pointers.jl:299 [inlined]
#3 at /home/circleci/.julia/packages/PythonCall/ZzOaq/src/gc.jl:57 [inlined]
with_gil at /home/circleci/.julia/packages/PythonCall/ZzOaq/src/cpython/gil.jl:10 [inlined]
enqueue at /home/circleci/.julia/packages/PythonCall/ZzOaq/src/gc.jl:56
py_finalizer at /home/circleci/.julia/packages/PythonCall/ZzOaq/src/Py.jl:46
unknown function (ip: 0x7f1908135c92)
_jl_invoke at /cache/build/default-amdci4-2/julialang/julia-release-1-dot-8/src/gf.c:2377 [inlined]
ijl_apply_generic at /cache/build/default-amdci4-2/julialang/julia-release-1-dot-8/src/gf.c:2559
jl_apply at /cache/build/default-amdci4-2/julialang/julia-release-1-dot-8/src/julia.h:1843 [inlined]
run_finalizer at /cache/build/default-amdci4-2/julialang/julia-release-1-dot-8/src/gc.c:280
jl_gc_run_finalizers_in_list at /cache/build/default-amdci4-2/julialang/julia-release-1-dot-8/src/gc.c:367
run_finalizers at /cache/build/default-amdci4-2/julialang/julia-release-1-dot-8/src/gc.c:410
jl_gc_run_pending_finalizers at /cache/build/default-amdci4-2/julialang/julia-release-1-dot-8/src/gc.c:423
jl_mutex_unlock at /cache/build/default-amdci4-2/julialang/julia-release-1-dot-8/src/julia_locks.h:131 [inlined]
ijl_task_get_next at /cache/build/default-amdci4-2/julialang/julia-release-1-dot-8/src/partr.c:569
poptask at ./task.jl:921
wait at ./task.jl:930
task_done_hook at ./task.jl:634
unknown function (ip: 0x7f19383d2bb2)
_jl_invoke at /cache/build/default-amdci4-2/julialang/julia-release-1-dot-8/src/gf.c:2377 [inlined]
ijl_apply_generic at /cache/build/default-amdci4-2/julialang/julia-release-1-dot-8/src/gf.c:2559
jl_apply at /cache/build/default-amdci4-2/julialang/julia-release-1-dot-8/src/julia.h:1843 [inlined]
jl_finish_task at /cache/build/default-amdci4-2/julialang/julia-release-1-dot-8/src/task.c:254
start_task at /cache/build/default-amdci4-2/julialang/julia-release-1-dot-8/src/task.c:942
Allocations: 188027855 (Pool: 187968979; Big: 58876); GC: 57

Received "aborted" signal

Thanks for adding the entry into github's FAQ.
Perhaps that's off-topic, but the FAQ you updated is not up-to-date with the one obtained from the one of the documentation.

That's just because I haven't made a release yet. It's in the dev docs.


Could you give me some software installation instructions?

Could you give me some software installation instructions? You didn't provide a read me and this project looks sick.

Hi, thank you. Are you looking for a clarification of something in particular?
The project is targeting a Raspberry Pi Pico so all you need to do to install is to first build the code (use the Makefile provided) and then copy the binary file onto the pico board, connected to your machine through the USB connector. While connecting thePico to your machine you need to keep the white button on the board itself pressed and you can release if after the USB connector is plugged in. This will mount the Pico storage as a drive where you can copy the binary file you just compiled. Very simple :+1:
If you want a simple script to do the above:
# Build the Docker image used as build environment
$ make docker
# Build the code within a Docker container
$ make build
# Copy the binary onto the pico
$ cp build/*.uf2 /media/<username>/RPI-RP2/


http2: client connection lost - is there any possibility of a retry?

Occasionally I am seeing http2: client connection lost in helm install/upgrade operation.
This is more noticeable in long running installs.
helm install is happening within pods inside the cluster but there may be network drops due to cluster size, traffic volume or possible rolling restarts of etcd/api servers, none of which me or my team can control.  Understand these problems are not really helms issue, but would it be possible for helm to retry in this situation, rather than fail?
kubectl v18.2.0
helm v3.9.0

@stuartdrennan run helm install again?

Certainly an option, but an inbuilt retry mechanism would be a lot simpler and cleaner so the install doesn't get into a failed state when the chart itself didn't actually fail :)

@stuartdrennan There is no such retry mechanism at present. Thanks very much.

It looks like https://github.com/helm/helm/pull/11401/files may fix this

This issue was not resolved by PR 11401.
Helm should have better connection handling when monitoring for --atomic or --wait.
An unstable connection to the API server while monitoring the progress of a release should not cause the release to fail.


UITextView.text always with default Values

The font and textColor Properties are not set when PdfFileGenerator.drawPageWithContext(page:UIView, context: CGContextRef) is called. The query always returns false and continues with default Values.

Fixed in commit fca831f


NIFI-3036: When we replay a FlowFile, ensure that we are using the 'g…

Thank you for submitting a contribution to Apache NiFi.
In order to streamline the review of the contribution we ask you
to ensure the following steps have been taken:
For all changes:

[ ] Is there a JIRA ticket associated with this PR? Is it referenced
in the commit message?

[ ] Does your PR title start with NIFI-XXXX where XXXX is the JIRA number you are trying to resolve? Pay particular attention to the hyphen "-" character.

[ ] Has your PR been rebased against the latest commit within the target branch (typically master)?

[ ] Is your initial contribution a single, squashed commit?

For code changes:

[ ] Have you ensured that the full suite of tests is executed via mvn -Pcontrib-check clean install at the root nifi folder?
[ ] Have you written or updated unit tests to verify your changes?
[ ] If adding new dependencies to the code, are these dependencies licensed in a way that is compatible for inclusion under ASF 2.0?
[ ] If applicable, have you updated the LICENSE file, including the main LICENSE file under nifi-assembly?
[ ] If applicable, have you updated the NOTICE file, including the main NOTICE file found under nifi-assembly?
[ ] If adding new Properties, have you added .displayName in addition to .name (programmatic access) for each of the new properties?

For documentation related changes:

[ ] Have you ensured that format looks appropriate for the output in which it is rendered?

Note:
Please ensure that once the PR is submitted, you check travis-ci for build issues and submit an update to your PR as soon as possible.
…olden copy' of the associated Resource Claim, if the claim is still writable.

Hey @markap14, I just tested it and I'm seeing a slightly different error (stacktrace below). It came about by following the same steps (generateFF -> replay event(s) -> let it sit a bit -> attempt to start generateFF). This time though it spews the error only a few times (3) and then properly creates FlowFiles. Let me know if there is any other information you need.
2016-11-15 10:16:50,533 WARN [Timer-Driven Process Thread-3] o.a.n.p.standard.GenerateFlowFile GenerateFlowFile[id=63c8709d-0158-1000-0fce-cb9fc498694f] Processor Administratively Yielded for 1 sec due to processing failure
2016-11-15 10:16:50,533 WARN [Timer-Driven Process Thread-3] o.a.n.c.t.ContinuallyRunProcessorTask Administratively Yielding GenerateFlowFile[id=63c8709d-0158-1000-0fce-cb9fc498694f] due to uncaught Exception: java.lang.NullPointerException
2016-11-15 10:16:50,534 WARN [Timer-Driven Process Thread-3] o.a.n.c.t.ContinuallyRunProcessorTask
java.lang.NullPointerException: null
at org.apache.nifi.controller.repository.FileSystemRepository$2.write(FileSystemRepository.java:907) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.controller.repository.io.DisableOnCloseOutputStream.write(DisableOnCloseOutputStream.java:49) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.controller.repository.io.ByteCountingOutputStream.write(ByteCountingOutputStream.java:46) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.controller.repository.io.ByteCountingOutputStream.write(ByteCountingOutputStream.java:41) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.controller.repository.io.FlowFileAccessOutputStream.write(FlowFileAccessOutputStream.java:78) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.processors.standard.GenerateFlowFile$1.process(GenerateFlowFile.java:192) ~[na:na]
at org.apache.nifi.controller.repository.StandardProcessSession.write(StandardProcessSession.java:2321) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.processors.standard.GenerateFlowFile.onTrigger(GenerateFlowFile.java:189) ~[na:na]
at org.apache.nifi.processor.AbstractProcessor.onTrigger(AbstractProcessor.java:27) ~[nifi-api-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.controller.StandardProcessorNode.onTrigger(StandardProcessorNode.java:1089) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.controller.tasks.ContinuallyRunProcessorTask.call(ContinuallyRunProcessorTask.java:136) [nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.controller.tasks.ContinuallyRunProcessorTask.call(ContinuallyRunProcessorTask.java:47) [nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.controller.scheduling.TimerDrivenSchedulingAgent$1.run(TimerDrivenSchedulingAgent.java:132) [nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) [na:1.8.0_74]
at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308) [na:1.8.0_74]
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180) [na:1.8.0_74]
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294) [na:1.8.0_74]
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) [na:1.8.0_74]
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) [na:1.8.0_74]
at java.lang.Thread.run(Thread.java:745) [na:1.8.0_74]
Suppressed: java.lang.NullPointerException: null
at org.apache.nifi.controller.repository.FileSystemRepository$2.flush(FileSystemRepository.java:923) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.controller.repository.io.DisableOnCloseOutputStream.close(DisableOnCloseOutputStream.java:68) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.controller.repository.io.ByteCountingOutputStream.close(ByteCountingOutputStream.java:61) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.controller.repository.StandardProcessSession.write(StandardProcessSession.java:2322) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
... 13 common frames omitted
Suppressed: java.lang.NullPointerException: null
at org.apache.nifi.controller.repository.FileSystemRepository$2.flush(FileSystemRepository.java:923) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.controller.repository.io.DisableOnCloseOutputStream.close(DisableOnCloseOutputStream.java:68) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.controller.repository.StandardProcessSession.write(StandardProcessSession.java:2322) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
... 13 common frames omitted
Suppressed: java.lang.NullPointerException: null
at org.apache.nifi.controller.repository.FileSystemRepository$2.close(FileSystemRepository.java:962) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
at org.apache.nifi.controller.repository.StandardProcessSession.write(StandardProcessSession.java:2322) ~[nifi-framework-core-1.1.0-SNAPSHOT.jar:1.1.0-SNAPSHOT]
... 13 common frames omitted

@JPercivall fortunately after a few tries i was able to replicate the new issue as well. So the fix that I provided initially addressed the problem only in some cases. I have committed a new patch that I believe should handle the other case.

+1
Visually verified code and did a contrib-check build. In a stand-alone build I tried many different ways to reproduce the bug and it appears @markap14 commits fix it. Thanks @markap14, I will merge it in.


Close Window After Operation Modifier?

Hey there I was wondering if after we choose a main option like downloading bookmarked images, that we can have Y/N option on closing the window after it finishes downloading everything,

this one ==> https://github.com/Nandaka/PixivUtil2/blob/master/readme.txt#L219

I think he wanted a switch, like a tag query for option 4. I think it's horrible for useability.
Better would be closeAfterDone option for config.ini with input either True/False, or, preferably, in number selector format, like 1,4-7,11 so PixivUtil2 gets to exit after completing only options 1, 4, 5, 6, 7 and 11.
-x works perfectly fine by itself, but not when you stop process with Ctrl-C, by the way,

this one ==> https://github.com/Nandaka/PixivUtil2/blob/master/readme.txt#L219

Question. Do I add -X at the very beginning before even doing anything?

No, you add it to startup line. Like, creating a shortcut to the program and then changing properties with -x added to object line.

That's what I mean. The first line when I boot it up.
Here right?
http://prntscr.com/km5ng5

No.
https://i.imgur.com/87mBnUM.png

Ohhh I remember that.
I mean yea I can do that but, wouldn't it be great as a feature?


Fix identation issues

Fix an small indentation issues after latest update.
Fixed
from nai_api_gen import nai_api
      File "G:\stable-diffusion-webui-forge\extensions\sdwebui-nai-api\nai_api_gen\nai_api.py", line 50
        print(f"Request Timed Out after {timeout} seconds, Retrying")
        ^^^^^
    IndentationError: expected an indented block after 'if' statement on line 49

from nai_api_gen import nai_api
      File "G:\stable-diffusion-webui-forge\extensions\sdwebui-nai-api\nai_api_gen\nai_api.py", line 429
        elif isinstance(reference_image,list):
        ^^^^
    SyntaxError: invalid syntax

Thanks, must have had things set to ignore white space changes when I made the last commit.


Good day. How can I put my image?

I understand the images are on the site https://fontawesome.com/icons?d=gallery And how can I place my own so that they would not be on a third-party resource?

These aren't image but css classes. You would include a custom css file, i.e., glyphicons, and then specify the glyphicon class


Discuss nonlinear problems and nonuniform data in the paper

From #426

The authors shall describe how the library could be used in non linear cases. In particular, the contact problem given in the first example is indeed non linear.

Can non uniform coefficients be handled ? To make my question clearer, would I be able to treat:
a linear elastic problem with a non uniform Young Modulus.
a heat transfer equation with a non uniform heat source Those non uniform coefficients are dealt with in UFL using the notion of functions spaces. Is there anything equivalent in scikit-fem ?

Should we discuss these in the paper?

Let's see.  These are all handled easily by scikit-fem as it stands, I believe.  I think the techniques are covered in the suite of examples.  Going back to #24 (2018-08-07), quite new to scikit-fem, I wrote:

It wasn't immediately clear to me how to write forms with variable coefficients so I wrote an example, solving the Legendre equation.

That became ex16 ‘spatially varying coefficient’.  It's a diffusion operator, but the same technique would apply to uneven Lamé coefficients in linear elasticity, nonuniform source terms.
That's for a coefficient that varies with position; for coefficients varying by subdomain, there's ex17, fufilling #89 ‘piecewise-definition of coefficients on subdomains’ (2018-11).
Then there are coefficients that are functions of finite element functions, like the Young–Laplace equation ex10, the Bratu–Gelfand equation ex23, and the Navier–Stokes equation ex27.  I think that covers the kind of nonlinear cases asked about.
The Bratu–Gelfand equation is handled a bit differently; I'm not sure why.  I guess it's simpler so can be, but I think it could be handled in the same way as the others if that was of interest, to have only one way of doing things.
Apart from the Bratu–Gelfand example, the fundamental notion is Basis.interpolate.  The coefficient is defined as a finite element function with degrees of freedom in some Basis and then it's interpolated onto the quadrature points associated with that basis.  These quadrature points have to be the same as those used by the trial and test bases in the bilinear form (or just the test basis in the linear form), and for the bilinear form itself, but the three bases don't have to be the same.  Does that cover it?

It seems to me that u is defined in FunctionSpace(mesh, "Lagrange", 2) and "projected" to Q:
C = project((1.0 + self.u**2), self.Q)

Does it mean that u is interpolated at the quadrature points and that FunctionSpace(mesh, "Q", 2) simply presents functions evaluated at quadrature points, e.g., similar to a DiscreteField?
https://github.com/kinnala/scikit-fem/blob/master/skfem/element/discrete_field.py

Yes, that's it, nothing new.


xemu: 0.7.134 -> 0.7.135

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://repology.org/project/xemu/versions.
meta.description for xemu is: Original Xbox emulator
meta.homepage for xemu is: https://xemu.app/
meta.changelog for xemu is: https://github.com/xemu-project/xemu/releases/tag/v0.7.135
Updates performed

Version update

To inspect upstream changes
Impact
Checks done

built on NixOS
The tests defined in passthru.tests, if any, passed
found 0.7.135 with grep in /nix/store/ww811aha3a4qbn5ay2y0llh8sqg288fw-xemu-0.7.135
found 0.7.135 in filename of file in /nix/store/ww811aha3a4qbn5ay2y0llh8sqg288fw-xemu-0.7.135

Rebuild report (if merged into master) (click to expand)

2 total rebuild path(s)

2 package rebuild(s)

First fifty rebuilds by attrpath

xemu

Instructions to test this update (click to expand)

Either download from the cache:
nix-store -r /nix/store/ww811aha3a4qbn5ay2y0llh8sqg288fw-xemu-0.7.135 \
  --option binary-caches 'https://cache.nixos.org/ https://nixpkgs-update-cache.nix-community.org/' \
  --option trusted-public-keys '
  nixpkgs-update-cache.nix-community.org-1:U8d6wiQecHUPJFSqHN9GSSmNkmdiFW7GW7WNAnHW0SM=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The nixpkgs-update cache is only trusted for this store-path realization.)
For the cached download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A xemu https://github.com/r-ryantm/nixpkgs/archive/71deedcabc3c411d049d6cd39cc674ddbba3886a.tar.gz

Or:
nix build github:r-ryantm/nixpkgs/71deedcabc3c411d049d6cd39cc674ddbba3886a#xemu

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/ww811aha3a4qbn5ay2y0llh8sqg288fw-xemu-0.7.135
ls -la /nix/store/ww811aha3a4qbn5ay2y0llh8sqg288fw-xemu-0.7.135/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
nixpkgs-review result
Generated using nixpkgs-review.
Command: nixpkgs-review

x86_64-linux

:white_check_mark: 2 packages built:

xemu
xemu.debug

Maintainer pings
cc @AndersonTorres for testing.

[!TIP]
As a maintainer, if your package is located under pkgs/by-name/*, you can comment @NixOS/nixpkgs-merge-bot merge to automatically merge this update using the nixpkgs-merge-bot.

Add a :+1: reaction to pull requests you find important.

@NixOS/nixpkgs-merge-bot merge


Feat: --keep-seeds and --generate-functions command line option

Add the command line option --keep-seeds (-k) with default value True.
When set to False, scratch files will not be kept in the scratch folder after the Fuzzer executes, but the files will be created anyway.
Add command line option for Semantic Fusion to generate fusion functions with the fusion function generator: https://github.com/nicdard/fusion-function-generator/pull/78
Use --generate-functions option (int value, the size of the functions) to generate a fusion function on demand to perform the fuse step of semantic fusion.

Can you provide any guidance on why the tests are failing? If I rebase on top of master then the PR contains all the previous commits that are part of new-fusion-functions branch, maybe it would be nice to update that branch first, wdyt? In case I can open a PR for the update and then a PR for this feature afterwards :)

It's now ready :) I also moved the spellcheck on top before the unit tests and integration tests to have immediate feedback from it without waiting long integration tests to complete, we could also add a git commit hook so that it runs automatically locally

I also moved the spellcheck on top before the unit tests and integration tests to have immediate feedback
sounds good to me


Close Browser Not Working!

Hello,

Hello @kurtuluskara ,
can you, please, provide us more information on how to reproduce the issue or how this error is caused by UI5-Inspector?
Thank you!
BR,
Petya Markova.
(UI5 Developer)


Add ws and socket.io-client packages to the Node.js runtime

Resolves #268

@markusthoemmes based on the history of the Dockerfile, you seem like the right person to assign this to. Please re-assign if needed.

PPG 536

@bjustin-ibm need to update refrences.md
FYI @csantanapr

@rabbah @bjustin-ibm created an issue to track change that need to go into bluemix docs.
https://github.com/IBM-Bluemix/docs/issues/273

PG 324

LGTM, is this good to merge documentation wise?

@markusthoemmes yes, this is ready for merge.
Tracking sync to bluemix docs is track i another ready like I mentioned in https://github.com/openwhisk/openwhisk/pull/523#issuecomment-221959461

rebased and merged 364e61ad03372eb80e0ba2b09e18df8b09e8859f


Test

 Thank you for your submission, we really appreciate it. Like many open source projects, we ask that you all sign our Contributor License Agreement before we can accept your contribution.1 out of 2 committers have signed the CLA.:white_check_mark: macfarla:x: bretthendersonYou have signed the CLA already but the status is still pending? Let us recheck it.


API Docs 404

Site appears to be offline.
https://www.nodegit.org/
http://www.nodegit.org/api/

The domain is pending ICANN verification.

Is there any alternative way to visit docs now? Such as http://<ip>:<port>.

@m31271n docs can be accessed at https://nodegit.github.io/ until we can resolve the domain issues.


Remove an unnecessary copy in helm_charts.sh.

/lgtm

[APPROVALNOTIFIER] This PR is APPROVED
This pull-request has been approved by: rkpagadala
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Manually merging so release automation can pick it up, and this PR does not affect production code.


mat-slide-toggle blink with BrowserAnimationsModule

I am working with mat-slide-toggle in a table, when I activate or deactivate it a blink occurs. This happens to me when I include the BrowserAnimationsModule and in the browsers: Chrome, Opera. In Firefox and Safari it works without problems.
Here my stackblitz: https://stackblitz.com/edit/angular-hr7suh

Closing this issue as it does not follow the issue template. Please file a new issue that follows the template, which gives the team the information needed to investigate

How can I follow the template? what template?


Getting ShiningPanda Python location does not work on Windows

As reported on Nov 29th, 2017 in the official Jenkins issue tracker as JENKINS-48276:

The plugin doesn't work correctly using the ShiningPanda tool location:
Matched ShiningPanda tool name: Windows-Python-Default
$ C:\Python27\python -m virtualenv --python=C:\Python27\python C:\jenkins\workspace\Python\pymxf\.pyenv-Windows-Python-Default
Error while creating virtualenv: The path C:\Python27\python (from --python=C:\Python27\python) does not exist

The --python argument expects the full filename (C:\Python27\python.exe in this case). Specifying the full path in the tool configuration still causes this plugin to try to append "python" to the string.

Are there any plans on when this issue is getting fixed?

I apologize for the delay. I will be releasing a fix either later today or tomorrow

@cstarner Thank you very much and no worries about the delay. After all, this is open source :smiley: I'll update and test the plugin on Monday.


Move party info into Character classes

How about Cupid? Does it have party?

Cupid role is in Villager party now.


preferred terminal set to ptyxis, but still launches gnome-terminal instead

Install method (Flatpak/Binary/Other)
Flatpak
Distrobox Version
distrobox: 1.7.0
Your Host OS
Ubuntu 24.10
Describe your Issue
Using BoxBuddy 2.3.1, I've set my preferred terminal to ptyxis. However, clicking "Open Terminal" on a container opens gnome-terminal instead.
Note: I've installed both BoxBuddy and Ptyxis via flatpak.

Hello
https://www.dvlv.co.uk/BoxBuddyRS/faqs#my-preferred-terminal-is-a-flatpak-why-cant-boxbuddy-open-it

Ahh okay, thanks for pointing me there! Sorry, I missed that item in the FAQ.

BoxBuddy is not programmed to be able to launch Flatpaks.
You can get around this by making a wrapper script

The wording there kinda makes it sound like it's a feature that hasn't happened yet, and doesn't make it necessarily clear that it's intended never to be able to do so. If that is your intent (which is totally fair!) then it might be worth clarifying at some point.
Thanks for the nice app!


Update form-data dependency

This should decrease the total footprint of request by ~5.5MB.

Ah, looks like the greenkeeper bot beat me to it in https://github.com/request/request/pull/2377. However, it might be nice to use ^ instead of ~ for the version since form-data seems to follow semver?

Looks like test-pipes isn't that stable. Greenkeeper didn't pass.

:+1:


[Bug]: Unable to generate pydantic-core schema for <class 'prowler.lib.check.compliance_models.CIS_Requirement_Attribute_Profile'>.

Steps to Reproduce
./prowler.py --output-formats {csv,json-asff,json-ocsf,html} -c cis_2.0_aws -w arn:aws:dynamodb:ap-southeast-1:xxxxxxxxxxx:table/prowler_allow_list
Expected behavior
run correctly
Actual Result with Screenshots or Logs
[Container] 2024/05/31 07:03:52.594491 Running command ./prowler.py --output-formats {csv,json-asff,json-ocsf,html} -c cis_2.0_aws -w arn:aws:dynamodb:ap-southeast-1:xxxxxxxxxxx:table/prowler_allow_list
Traceback (most recent call last):
File "/codebuild/output/src513582655/src/prowler/./prowler.py", line 5, in
from prowler.main import prowler
File "/codebuild/output/src513582655/src/prowler/prowler/main.py", line 10, in
from prowler.lib.check.check import (
File "/codebuild/output/src513582655/src/prowler/prowler/lib/check/check.py", line 18, in
from prowler.lib.check.compliance_models import load_compliance_framework
File "/codebuild/output/src513582655/src/prowler/prowler/lib/check/compliance_models.py", line 80, in
class CIS_Requirement_Attribute(BaseModel):
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/_internal/_model_construction.py", line 202, in new
complete_model_class(
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/_internal/_model_construction.py", line 539, in complete_model_class
schema = cls.get_pydantic_core_schema(cls, handler)
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/main.py", line 626, in get_pydantic_core_schema
return handler(source)
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/_internal/_schema_generation_shared.py", line 82, in call
schema = self._handler(source_type)
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/_internal/_generate_schema.py", line 502, in generate_schema
schema = self._generate_schema_inner(obj)
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/_internal/_generate_schema.py", line 753, in _generate_schema_inner
return self._model_schema(obj)
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/_internal/_generate_schema.py", line 580, in _model_schema
{k: self._generate_md_field_schema(k, v, decorators) for k, v in fields.items()},
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/_internal/_generate_schema.py", line 580, in
{k: self._generate_md_field_schema(k, v, decorators) for k, v in fields.items()},
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/_internal/_generate_schema.py", line 916, in _generate_md_field_schema
common_field = self._common_field_schema(name, field_info, decorators)
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/_internal/_generate_schema.py", line 1081, in _common_field_schema
schema = self._apply_annotations(
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/_internal/_generate_schema.py", line 1820, in _apply_annotations
schema = get_inner_schema(source_type)
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/_internal/_schema_generation_shared.py", line 82, in call
schema = self._handler(source_type)
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/_internal/_generate_schema.py", line 1801, in inner_handler
schema = self._generate_schema_inner(obj)
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/_internal/_generate_schema.py", line 758, in _generate_schema_inner
return self.match_type(obj)
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/_internal/_generate_schema.py", line 844, in match_type
return self._unknown_type_schema(obj)
File "/root/.pyenv/versions/3.9.16/lib/python3.9/site-packages/pydantic/_internal/_generate_schema.py", line 405, in _unknown_type_schema
raise PydanticSchemaGenerationError(
pydantic.errors.PydanticSchemaGenerationError: Unable to generate pydantic-core schema for <class 'prowler.lib.check.compliance_models.CIS_Requirement_Attribute_Profile'>. Set arbitrary_types_allowed=True in the model_config to ignore this error or implement __get_pydantic_core_schema__ on your type to fully support it.
If you got this error by calling handler() within __get_pydantic_core_schema__ then you likely need to call handler.generate_schema(<some type>) since we do not call __get_pydantic_core_schema__ on <some type> otherwise to avoid infinite recursion.
How did you install Prowler?
Cloning the repository from github.com (git clone)
Environment Resource
Cloudformation template
OS used
Amazon Linux 2
Prowler version
4.2.1
Pip version
21.1.2
Context
I am using the same cloudformation template that I was using with prowler v2, except for python 3.6->3.9

Hi @oliviermtl, it could also be because the compliance flag is --compliance and not -c. Let us know if that is the issue, thanks for using Prowler! 🚀

Hi @oliviermtl, it could also be because the compliance flag is --compliance and not -c. Let us know if that is the issue, thanks for using Prowler! 🚀

it works fine locally with -c

Hi @oliviermtl could you please share the dependencies you have installed in your environment?

Successfully installed Flask-3.0.3 Jinja2-3.1.4 MarkupSafe-2.1.5 PyJWT-2.8.0 Werkzeug-3.0.3 XlsxWriter-3.2.0 about-time-4.2.1 aiohttp-3.9.5 aiosignal-1.3.1 alive-progress-3.1.5 anyio-4.4.0 attrs-23.2.0 awsipranges-0.3.3 azure-common-1.1.28 azure-core-1.30.1 azure-identity-1.16.0 azure-keyvault-keys-4.9.0 azure-mgmt-applicationinsights-4.0.0 azure-mgmt-authorization-4.0.0 azure-mgmt-compute-31.0.0 azure-mgmt-containerservice-30.0.0 azure-mgmt-core-1.4.0 azure-mgmt-cosmosdb-9.5.0 azure-mgmt-keyvault-10.3.0 azure-mgmt-monitor-6.0.2 azure-mgmt-network-25.4.0 azure-mgmt-rdbms-10.1.0 azure-mgmt-resource-23.1.1 azure-mgmt-security-7.0.0 azure-mgmt-sql-3.0.1 azure-mgmt-storage-21.1.0 azure-mgmt-subscription-3.1.1 azure-mgmt-web-7.2.0 azure-storage-blob-12.20.0 blinker-1.8.2 boto3-1.34.109 botocore-1.34.113 cachetools-5.3.3 cffi-1.16.0 charset-normalizer-3.3.2 click-8.1.7 click-plugins-1.1.1 colorama-0.4.6 cryptography-42.0.7 dash-2.17.0 dash-bootstrap-components-1.6.0 dash-core-components-2.0.0 dash-html-components-2.0.0 dash-table-5.0.0 deprecated-1.2.14 detect-secrets-1.5.0 dnspython-2.6.1 email-validator-2.1.1 frozenlist-1.4.1 google-api-core-2.19.0 google-api-python-client-2.130.0 google-auth-2.29.0 google-auth-httplib2-0.2.0 googleapis-common-protos-1.63.0 grapheme-0.6.0 h11-0.14.0 h2-4.1.0 hpack-4.0.0 httpcore-1.0.5 httplib2-0.22.0 httpx-0.27.0 hyperframe-6.0.1 idna-3.7 importlib-metadata-7.1.0 isodate-0.6.1 itsdangerous-2.2.0 jsonschema-4.22.0 jsonschema-specifications-2023.12.1 kubernetes-29.0.0 microsoft-kiota-abstractions-1.3.3 microsoft-kiota-authentication-azure-1.0.0 microsoft-kiota-http-1.3.1 microsoft-kiota-serialization-form-0.1.0 microsoft-kiota-serialization-json-1.2.0 microsoft-kiota-serialization-multipart-0.1.0 microsoft-kiota-serialization-text-1.0.0 msal-1.28.0 msal-extensions-1.1.0 msgraph-core-1.0.0 msgraph-sdk-1.4.0 msrest-0.7.1 multidict-6.0.5 nest-asyncio-1.6.0 numpy-1.26.4 oauthlib-3.2.2 opentelemetry-api-1.25.0 opentelemetry-sdk-1.25.0 opentelemetry-semantic-conventions-0.46b0 packaging-24.0 pandas-2.2.2 pendulum-3.0.0 plotly-5.22.0 portalocker-2.8.2 proto-plus-1.23.0 protobuf-4.25.3 prowler-4.2.1 py-ocsf-models-0.1.1 pyasn1-0.6.0 pyasn1-modules-0.4.0 pycparser-2.22 pydantic-1.10.15 pyparsing-3.1.2 pytz-2024.1 referencing-0.35.1 requests-2.32.3 requests-file-2.1.0 requests-oauthlib-2.0.0 retrying-1.3.4 rpds-py-0.18.1 rsa-4.9 schema-0.7.7 shodan-1.31.0 slack-sdk-3.27.2 sniffio-1.3.1 std-uritemplate-0.0.57 tabulate-0.9.0 tenacity-8.3.0 time-machine-2.14.1 tldextract-5.1.2 typing-extensions-4.12.0 tzdata-2024.1 tzlocal-5.2 uritemplate-4.1.1 websocket-client-1.8.0 wrapt-1.16.0 yarl-1.9.4 zipp-3.19.0

Solved by using python 3.11 on Amazon-Linux-2023.
This is the BuildSpec from my cloudformation template :
BuildSpec: |
          version: 0.2
          phases:
            install:
              runtime-versions:
                python: 3.11
              commands:
                - echo "Installing Prowler and dependencies..."
                - pip3 install detect-secrets alive_progress colorama jsonschema tabulate pydantic==1.10.15 azure-identity azure.mgmt==4.0.0 schema slack_sdk pytz tzlocal msgraph-core==1.0.0 msgraph-sdk==1.4.0 py_ocsf_models
                - pip3 install --upgrade google-api-python-client
                - yum -y install jq
                - curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
                - unzip awscliv2.zip
                - ./aws/install --update
                - git clone --depth 1 --branch 4.2.1 https://github.com/prowler-cloud/prowler.git

That's great news @oliviermtl 👏
Where did you grab the cloudformation templace? Is it something built by you or present in this repository? If it is the latter it'd be great to include that code into the repository. We can do that or help you to do that.
Thanks!

The template was already here when I took over the position so I cannot confirm where it comes from.
Happy to push a PR with the template.

Awesome! You can include it under contrib/aws. Thanks!

~/Code/prowler cloudformation-template >  git push --set-upstream origin cloudformation-template
remote: Permission to prowler-cloud/prowler.git denied to oliviermtl.
fatal: unable to access 'https://github.com/prowler-cloud/prowler/': The requested URL returned error: 403

What am I missing here ? I git clone, followed all the dev guide, created a branch

You cannot contribute directly to the repository, you have to create a fork, push the code to a branch in your forked repository and then open the pull request from your forked branch to Prowler master.

ok, you might to want to include this information at the top of  the developer guide.

ok, you might to want to include this information at the top of the developer guide.

Sure, good catch!

Hi @oliviermtl, we've just included that in our documentation, thanks!
https://github.com/prowler-cloud/prowler/pull/4238

Hi @oliviermtl are you finally planning to open up a PR with the CodeBuild template? Thanks!

Hi @oliviermtl I'm closing this issue. Please open the PR you mention once is ready, we are looking forward to have that!
Thanks for using Prowler 🚀


one endpoint protected AND public

Hi,
i want to realize a generic endpoint /cities to be public to everyone. The resultset would be [{id: 1, name: "xyz"}...]
But if a token was sent and is correct, the very same endpoint would additionaly return some user-context-specific attributes like {..., is_interesting: true}
Iam using winebouncers protected strategy and setting the endpoint to public by oauth2 false but that disables the token-check logic at all. resource_owner is nil even if the sent token is perfectly valid.
What i want is to check if resource_owner is set and then enhance the resultsets in this case.
Is it somehow possible?

fixed wrong title

Hi @thedarkside ,
The current implementation does not allow to make an endpoint both public and private.
WineBouncer assumes that the endpoint has only one type of access modifier.
What you could do, is to make a separate user context specific endpoint that extends the current endpoint or only shows interesting cities for that user. Whatever your implementation, you will end up with two endpoints.
If you really want one endpoint, your best start is you make an custom strategy in the WineBouncer::AuthStrategies:: namespace. You can always just hardcode true to the endpoint_protected? method as an test. Then the challenge would be to catch the exceptions that doorkeeper_authorize! throws.
I don't know if you are documenting the endpoint for public use. But there could be some issues with the current documentation tools that are around. They are mostly not context aware. Having two context for an endpoint could confuse the consumer of your API.
This is an interesting issue. Please let me know what you are going to consider to do.

closing due, inactivity.

@antek-drzewiecki i ended up with this patch documented here: https://github.com/antek-drzewiecki/wine_bouncer/issues/58#issuecomment-269322386
This way winebouncer will always try to lookup a resource_owner if a token is present. Even if the endpoint is marked as public.
I am aware that this leads to issues with the documentation tools.
A cleaner way would be to create two endpoints with the same url marking one public and the other private (with oauth) and let winebouncer/grape decide which endpoint to use based on the presence of the token. In this scenario the documentation tools could list both endpoints with one marked as public and the other as private.


Repository structure

A couple of minor (subjective) things that would go a bit to helping out others (like me) get started committing.

Rename bin/ to scripts/, node modules normally reserve bin/ for CLIs that the module exposes
Use pre-commit node module and remove bin/git-hook - it would do very similar things in the end, except the pre-commit module just works automatically (by default it'll run the tests, but you can change that if you only want to compile templates - I usually do both in my test script and I made that change with #33)
Make aliases for other scripts in package.json "scripts" - makes script discovery much easier and you can probably remove half the one liners you have in bin/ right now in favour of npm run bundle, npm run pretest, etc.
(Super subjective) Look at using something like standard for linting
Make linting run as part of the test suite so PRs match your style
Add karma tests to the npm test script - I only just discovered that it's even an option and I've glanced over it a dozen times

I can make a PR with these options enabled/disabled - just let me know which you don't want.

I removed npm run build from npm test because tests (especially in travis) should run against compiled dot files in the repo rather then recompile them - many users are likely not to run tests / recompile dot files.
I think linting in script is a good idea - it will prevent some code errors from being comitted - at the moment it only happens in code-climate and there is a file that turns off the rules I intentionally break.
I don't like standard though - although with some things it enforces I agree, it's opinionated differently from me :) and not configurable. I disagree about not using semicolons - not only consistently using them prevents some errors but also, for example, }; vs } helps understand what this brace belongs to. I also disagree about always using '===' - I have many arguments for always using '==' unless you know that you definitely need '==='. I almost never use braces around single statements after if and for - for example, I prefer for (var key in schema) if (rules[key]) return true; to for (var key in schema) { if (rules[key]) { return true; } }... I know that many people think differently and quote Crockford. I prefer Flanagan's approach to JS :)
So I'm happy with any tool as long as it supports options from .jshintrc.

@epoberezkin Fair enough, not sure I agree. Normally I'd avoid checking in any compiled files though and I'd just publish them using the npm prepublish step.
I'll look into a linting solution later for you. Shouldn't be difficult just to use jshint and all the newer projects tend to use eslint now too.

Removing them completely is ok, I think. I didn't understand that it is what you suggest as they were still there. It will guarantee they are not old.
It also makes tracking changes a bit easier too. I will do it.
jshint is ok, definitely.

It's ok, I don't think I had made that suggestion yet. But yeah, I normally just prepublish and run it on build, and keep compiled pieces out of the source code.

@epoberezkin It looks like the current build in npm, 1.1.0, is broken, at least for use with webpack. I got errors like Error: Cannot resolve 'file' or 'directory' ../dotjs... when bundling. Fixed through cd node_modules//ajv/ && npm install. I guess the prepublish script should have done this but instead the dotjs folder had only the readme.

Can confirm. This is a result of, when you don't specify the files to publish, it uses .gitignore. I'll make a PR now with the folder we need.

Fixed with #37.

thank you, I published 1.1.1

@blakeembrey should https://github.com/mulesoft-labs/osprey-method-handler/blob/master/package.json#L41 be changed to 1.1.1? Or what is it better to do with that broken 1.1.0?

@epoberezkin You can unpublish 1.1.0. I'll update that module once I use JSON pointers most likely.

Thanks :+1:

:)


Add UnioStreamType and AnyUnioStream

This PR introduces UnioStreamType, which defines a type with specific Input and Output, and AnyUnioStream as a type-erased wrapper of UnioStreamType.
These changes can be considered purely additive, not breaking.
Background
You can define a generic UnioStream.
The example below defines AdderStream, which works with arbitrary types conform to AdditiveArithmetic:
protocol AdderStreamType: AnyObject {
    associatedtype T: AdditiveArithmetic
    var input: InputWrapper<AdderStream<T>.Input> { get }
    var output: OutputWrapper<AdderStream<T>.Output> { get }
}

final class AdderStream<T: AdditiveArithmetic>: UnioStream<AdderStream>, AdderStreamType {
    struct Input: InputType {
        let lhs = PublishRelay<T>()
        let rhs = PublishRelay<T>()
    }

    struct Output: OutputType {
        let result: PublishRelay<T>
    }

    static func bind(from dependency: Dependency<Input, NoState, NoExtra>, disposeBag: DisposeBag) -> Output {
        let result = PublishRelay<T>()
        Observable
            .combineLatest(dependency.inputObservables.lhs,
                           dependency.inputObservables.rhs,
                           resultSelector: +)
            .bind(to: result)
            .disposed(by: disposeBag)
        return Output(result: result)
    }
}

The problem here is that you cannot use AdderStreamType as an existential, since it is a PAT (Protocol with Associated Types.) Not being able to do this prevents, for example, constructor injection:
init(stream: AdderStreamType) { // <!> Protocol 'AdderStreamType' can only be used as a generic constraint

Solution
This PR introduces UnioStreamType, which defines a type with specific Input and Output, and AnyUnioStream for a type-erased wrapper of UnioStreamType.
These types allows you to define parameters or variables accepting any type which have specific Input and Output.
struct Calc {
    init(stream: AnyUnioStream<AdderStream<Int>.Input, AdderStream<Int>.Output>) { ... }
}

or more legibly with typealias:
struct Calc {
    typealias AnyFooStream<T: AdditiveArithmetic> = AnyUnioStream<AdderStream<T>.Input, AdderStream<T>.Output>

    init(stream: AnyFooStream<Int>) { ... }
}

You need to have a little modification to wrap it with AnyUnioStream in the call site.
Calc(.init(AdderStream())

This PR adds a requirement to typealias UnioStream to be UnioStreamType, but you need no additional work as any PrimitiveStream can automatically conform to the protocol.
You need explicitly mark protocol ___StreamType to conform UnioStreamType as below, but it's not a requirement unless you need to wrap it with AnyUnioStream.
protocol AdderStreamType: UnioStreamType {
     associatedtype T: AdditiveArithmetic
     var input: InputWrapper<AdderStream<T>.Input> { get }
     var output: OutputWrapper<AdderStream<T>.Output> { get }
 }

Hi @marty-suzuki :)
I'm merging this!


Enable just voting

Enable using the tool to just vote for the most recent proposal and optionally pass a proposal ID.

Done.


Rust Hop using ockam::worker

I just went through the Get Started guide and to define a Hop, this is the recommended code:
pub struct Hop;

#[ockam::worker]
impl Worker for Hop {
    type Context = Context;
    type Message = Any;

    /// This handle function takes any incoming message and forwards
    /// it to the next hop in its onward route
    async fn handle_message(&mut self, ctx: &mut Context, msg: Routed<Any>) -> Result<()> {
        println!("Address: {}, Received: {}", ctx.address(), msg);

        let mut msg = msg.into_transport_message();
        msg.onward_route.step()?;
        msg.return_route.modify().prepend(ctx.address());
        ctx.forward(msg).await
    }
}

It is also recommended that ockam is imported like this:
[dependencies]
ockam = { version = "0", features = ["ockam_transport_tcp", "ockam_vault"] }

This assumes that the latest release includes ockam::worker, but it doesn't because that was only recently added in #1220. For the examples to work, I had to use  #[ockam::async_worker]. Maybe adding a minimum version number to the Set Up part could  fix this issue in the future, since I am assuming the API is still being heavily developed.

@jared-s closing this?


Update form_builder_validators to intl ^0.19.0 package

Is there an existing issue for this?

[X] I have searched the existing issues

Package/Plugin version
9.1.0
Platforms

[ ] Android
[ ] iOS
[ ] Linux
[ ] MacOS
[ ] Web
[X] Windows

Flutter doctor

Flutter doctor
Doctor summary (to see all details, run flutter doctor -v):
[√] Flutter (Channel stable, 3.22.0, on Microsoft Windows [Versi¢n 10.0.22631.3527], locale es-ES)
[√] Windows Version (Installed version of Windows is version 10 or higher)
[√] Android toolchain - develop for Android devices (Android SDK version 34.0.0)
[√] Visual Studio - develop Windows apps (Visual Studio Community 2022 17.8.5)
[√] Android Studio (version 2023.2)
[√] VS Code, 64-bit edition (version 1.89.1)
[√] Connected device (1 available)
[√] Network resources

Minimal code example

Code sample
flutter pub update

Current Behavior
flutter_localizations from sdk which depends on intl 0.19.0, intl 0.19.0 is required
form_builder_validators ^9.1.0, version solving failed because dependes on intl ^0.18.0
Expected Behavior
flutter pub update updates to latest packaged using intl 0.19.0
Steps To Reproduce
flutter pub update
Aditional information
No response

duplicate of  #90 which has more info and a workaround

Version 10.0.0 with fix, deployed https://pub.dev/packages/form_builder_validators