how to set the eval part in generation tasks

In face of generation situations, I guess we should set function name to ranking.  And as so we should set function_params. That's not so obvious.
the following not works for me.
Can we have a concrete demo for generation tasks? Thanks in advance
eval:
function_name: 'ranking'
function_params:
prompt: 'prompts/predictor_completion/prediction_generation.prompt'
mini_batch_size: 1
llm:
type: '...'
num_workers: 10
mode: 'verbose'
label_schema:  ["1","2","3","4","5"]

Hi, we have a generation example with all the details:
https://github.com/Eladlev/AutoPrompt/blob/main/docs/examples.md#generating-movie-reviews-generation-task
Let me know if something is not clear

Hi, we have a generation example with all the details: https://github.com/Eladlev/AutoPrompt/blob/main/docs/examples.md#generating-movie-reviews-generation-task
Let me know if something is not clear

Thank you for your instant response. I have already referred to this part of the content before. However, my main point of confusion is whether I should set the eval function name as “ranking” in this generation scenario, as well as any subsequent settings that may be required.
Or should I still leave the eval function name to 'accuracy'?

The short answer is that you should not modify the eval function, because this is done in the run_generation_pipeline.py code itself.
The run_generation_pipeline code consists of two parts:

Optimizing the ranker prompt, where we treat the task as a classification task, so the metric here is still the accuracy
Optimizing the generation prompt. In this part, we are taking the ranking prompt from the first step and define the score function according to this ranking prompt

generation_config_params.eval.function_params = ranker_config_params.predictor.config
generation_config_params.eval.function_params.instruction = best_prompt['prompt']
generation_config_params.eval.function_params.label_schema = ranker_config_params.dataset.label_schema

and I still got an error like others 'Keyerror' related to samples
Here is my default_config:
use_wandb: False
dataset:
name: 'dataset'
records_path: null
initial_dataset: ''
label_schema: ["Yes", "No"]
max_samples: 50
semantic_sampling: False # Change to True in case you don't have M1. Currently there is an issue with faiss and M1
annotator:
method : ''
predictor:
method : 'llm'
config:
llm:
type: 'azure'
name: '...'
num_workers: 5
prompt: 'prompts/predictor_completion/prediction_generation.prompt'
mini_batch_size: 1  #change to >1 if you want to include multiple samples in the one prompt
mode: 'prediction'
meta_prompts:
folder: 'prompts/meta_prompts_generation'
num_err_prompt: 1  # Number of error examples per sample in the prompt generation
num_err_samples: 2 # Number of error examples per sample in the sample generation
history_length: 4 # Number of sample in the meta-prompt history
num_generated_samples: 5 # Number of generated samples at each iteration
num_initialize_samples: 5 # Number of generated samples at iteration 0, in zero-shot case
samples_generation_batch: 5 # Number of samples generated in one call to the LLM
num_workers: 5 #Number of parallel workers
warmup: 4 # Number of warmup steps
eval:
function_name: 'accuracy'
num_large_errors: 4
num_boundary_predictions : 0
error_threshold: 0.5
llm:
type: 'azure'
name: '...'
temperature: 0.8
stop_criteria:
max_usage: 2 #In $ in case of OpenAI models, otherwise number of tokens
patience: 10 # Number of patience steps
min_delta: 0.01 # Delta for the improvement definition
Following is the logging:
Starting step 0
Dataset is empty generating initial samples
Processing samples:   0%|                                                                                | 0/1 [00:00<?, ?it/s]LLM_CHAIN {'num_samples': 5, 'task_description': 'Evaluate how well Assistant, a large language model, performs in generating movie reviews in accordance with its designated task.', 'instruction': 'Rate the quality of the generated movie review on a scale of 1 to 5, with 1 being poor and 5 being excellent. Please ensure that the generated review provides a comprehensive and detailed analysis of the specific movie as requested in the user prompt.'}
Processing samples: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:12<00:00, 12.28s/it]
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
......
/optimization_pipeline.py:192 in
self.config.meta_prompts.samples_gene   │
│   190 │   │                                                                                │
│   191 │   │   samples_batches = self.meta_chain.initial_chain.batch_invoke(batch_inputs, self.   │
│ ❱ 192 │   │   samples_list = [element for sublist in samples_batches for element in sublist['s   │
│   193 │   │   samples_list = self.dataset.remove_duplicates(samples_list)                        │
│   194 │   │   self.dataset.add(samples_list, 0)                                                  │
│   195                                                                                │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
KeyError: 'samples'

and I still got an error like others 'Keyerror' related to samples
Here is my default_config:
use_wandb: False dataset: name: 'dataset' records_path: null initial_dataset: '' label_schema: ["Yes", "No"] max_samples: 50 semantic_sampling: False # Change to True in case you don't have M1. Currently there is an issue with faiss and M1
annotator: method : ''
predictor: method : 'llm' config: llm: type: 'azure' name: '...' num_workers: 5 prompt: 'prompts/predictor_completion/prediction_generation.prompt' mini_batch_size: 1 #change to >1 if you want to include multiple samples in the one prompt mode: 'prediction'
meta_prompts: folder: 'prompts/meta_prompts_generation' num_err_prompt: 1 # Number of error examples per sample in the prompt generation num_err_samples: 2 # Number of error examples per sample in the sample generation history_length: 4 # Number of sample in the meta-prompt history num_generated_samples: 5 # Number of generated samples at each iteration num_initialize_samples: 5 # Number of generated samples at iteration 0, in zero-shot case samples_generation_batch: 5 # Number of samples generated in one call to the LLM num_workers: 5 #Number of parallel workers warmup: 4 # Number of warmup steps
eval: function_name: 'accuracy' num_large_errors: 4 num_boundary_predictions : 0 error_threshold: 0.5
llm: type: 'azure' name: '...' temperature: 0.8
stop_criteria: max_usage: 2 #In $ in case of OpenAI models, otherwise number of tokens patience: 10 # Number of patience steps min_delta: 0.01 # Delta for the improvement definition
Following is the logging:
Starting step 0 Dataset is empty generating initial samples Processing samples: 0%| | 0/1 [00:00<?, ?it/s]LLM_CHAIN {'num_samples': 5, 'task_description': 'Evaluate how well Assistant, a large language model, performs in generating movie reviews in accordance with its designated task.', 'instruction': 'Rate the quality of the generated movie review on a scale of 1 to 5, with 1 being poor and 5 being excellent. Please ensure that the generated review provides a comprehensive and detailed analysis of the specific movie as requested in the user prompt.'} Processing samples: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:12<00:00, 12.28s/it] ╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
...... /optimization_pipeline.py:192 in self.config.meta_prompts.samples_gene │ │ 190 │ │ │ │ 191 │ │ samples_batches = self.meta_chain.initial_chain.batch_invoke(batch_inputs, self. │ │ ❱ 192 │ │ samples_list = [element for sublist in samples_batches for element in sublist['s │ │ 193 │ │ samples_list = self.dataset.remove_duplicates(samples_list) │ │ 194 │ │ self.dataset.add(samples_list, 0) │ │ 195 │ ╰──────────────────────────────────────────────────────────────────────────────────────────────────╯ KeyError: 'samples'

the command is:
run_generation_pipeline.py
--prompt "Write a good and comprehensive movie review about a specific movie."
--task_description "Assistant is a large language model that is tasked with writing movie reviews."

It seems like the model was not able to generate samples.
I'm guessing that it's either issues with the connection to your Azure account, or you are using GPT-3.5 as the base LLM (he is too weak for handling the meta-prompts)
There are log files that are generated in the dump folder that might help to understand the root cause, feel free to reach out in the discord channel if you need help with the debugging process.

It seems like the model was not able to generate samples. I'm guessing that it's either issues with the connection to your Azure account, or you are using GPT-3.5 as the base LLM (he is too weak for handling the meta-prompts)
There are log files that are generated in the dump folder that might help to understand the root cause, feel free to reach out in the discord channel if you need help with the debugging process.

Hi, thank you for your help. I've change the model to GPT-4, and the error remains the same.
Am I using the correct prompt files?
attachment is the log file in the dump folder. Something is weird as I do not have gpt-3.5-turbo model deployment within this endpoint. But the log file contains gpt3.5. Does that come from the code scripts?

log file content:
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2024-07-17 16:22:22,187 - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False
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2024-07-17 16:22:22,225 - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False
2024-07-17 16:22:22,226 - DEBUG - load_verify_locations cafile='/home/tfk/miniconda3/envs/py311/lib/python3.11/site-packages/certifi/cacert.pem'
2024-07-17 16:22:22,236 - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False
2024-07-17 16:22:22,237 - DEBUG - load_verify_locations cafile='/home/tfk/miniconda3/envs/py311/lib/python3.11/site-packages/certifi/cacert.pem'
2024-07-17 16:22:22,249 - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False
2024-07-17 16:22:22,249 - DEBUG - load_verify_locations cafile='/home/tfk/miniconda3/envs/py311/lib/python3.11/site-packages/certifi/cacert.pem'
2024-07-17 16:22:22,260 - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False
2024-07-17 16:22:22,260 - DEBUG - load_verify_locations cafile='/home/tfk/miniconda3/envs/py311/lib/python3.11/site-packages/certifi/cacert.pem'
2024-07-17 16:22:22,271 - INFO - Initialize dataset
2024-07-17 16:22:22,273 - INFO - Load initial dataset from
2024-07-17 16:22:22,274 - WARNING - Dataset dump not found, initializing from zero
2024-07-17 16:22:22,275 - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False
2024-07-17 16:22:22,276 - DEBUG - load_verify_locations cafile='/home/tfk/miniconda3/envs/py311/lib/python3.11/site-packages/certifi/cacert.pem'
2024-07-17 16:22:22,286 - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False
2024-07-17 16:22:22,287 - DEBUG - load_verify_locations cafile='/home/tfk/miniconda3/envs/py311/lib/python3.11/site-packages/certifi/cacert.pem'
2024-07-17 16:22:22,311 - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'headers': {'api-key': ''}, 'files': None, 'json_data': {'messages': [{'role': 'user', 'content': 'Assistant is a large language model designed to generate a task description.\nYou are given a task description phrased as text generation task given some user input. Your task is to rephrase it as a task that suppose to evaluate the quality of the given generative task and how well it adhere to the user input.\n#####\nInput task description: Assistant is a large language model that is tasked with writing movie reviews.\n#####\nRephrased task description:'}], 'model': 'gpt-3.5-turbo', 'n': 1, 'stream': False, 'temperature': 0.8}}
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2024-07-17 16:22:27,887 - INFO - HTTP Request: POST https://tfkgpt4.openai.azure.com//openai/deployments/GPT4/chat/completions?api-version=2024-02-01 "HTTP/1.1 200 OK"
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2024-07-17 16:22:27,890 - INFO - Task description modified for ranking to:
Evaluate the performance of the Assistant, a large language model, in terms of its ability to generate high-quality movie reviews that accurately reflect and adhere to the user's input.
2024-07-17 16:22:27,898 - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'headers': {'api-key': ''}, 'files': None, 'json_data': {'messages': [{'role': 'user', 'content': "Assistant is a large language model designed to generate instructions for every task.\nYou are given a instructions phrased as text generation task.\nYour task is to write an instruction for a classification ranking task that suppose to evaluate the quality of a generated sample given a user prompt for this generative instruction.\nGuidelines:\n1. The classifier labels are ['1', '2', '3', '4', '5']. The result instructions should indicate explicitly that the task is a classification class with the following labels ['1', '2', '3', '4', '5']!\n2. The generated instruction must also evaluate how well the generated sample adhere the user prompt\n#####\nInput generative instruction: Write a good and comprehensive movie review about a specific movie.\n#####\nRephrased classification quality evaluation instruction:"}], 'model': 'gpt-3.5-turbo', 'n': 1, 'stream': False, 'temperature': 0.8}}
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2024-07-17 16:22:38,723 - INFO - HTTP Request: POST https://tfkgpt4.openai.azure.com//openai/deployments/GPT4/chat/completions?api-version=2024-02-01 "HTTP/1.1 200 OK"
2024-07-17 16:22:38,723 - DEBUG - receive_response_body.started request=<Request [b'POST']>
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2024-07-17 16:22:38,725 - INFO - Initial prompt modified for ranking to:
Rate the quality of the provided movie review text based on the following classification labels:

'1': The review text does not match the given prompt, and does not provide an appropriate or comprehensive review of the specified movie.
'2': The review text somewhat aligns with the prompt, but lacks in providing a comprehensive review of the specified movie.
'3': The review text aligns with the prompt to an extent and provides an average level of detail about the movie, but there's room for improvement.
'4': The review text mostly aligns with the prompt, giving a detailed and satisfactory review of the specified movie.
'5': The review text perfectly adheres to the prompt, providing an excellent and comprehensive review of the specified movie.

Please classify the text accordingly, ensuring that the quality of the generated sample is evaluated based on how well it adheres to the given user prompt.
2024-07-17 16:22:38,725 - INFO - Starting step 0
2024-07-17 16:22:38,726 - INFO - Dataset is empty generating initial samples
2024-07-17 16:22:38,735 - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'headers': {'api-key': '*****************'}, 'files': None, 'json_data': {'messages': [{'role': 'user', 'content': "Assistant is a large language model designed to generate challenging samples for every task.\nGenerate a list of 5 challenging samples for the following task.\n### Task description:\nEvaluate the performance of the Assistant, a large language model, in terms of its ability to generate high-quality movie reviews that accurately reflect and adhere to the user's input.\n### Task Instruction:\nRate the quality of the provided movie review text based on the following classification labels:\n\n- '1': The review text does not match the given prompt, and does not provide an appropriate or comprehensive review of the specified movie.\n- '2': The review text somewhat aligns with the prompt, but lacks in providing a comprehensive review of the specified movie.\n- '3': The review text aligns with the prompt to an extent and provides an average level of detail about the movie, but there's room for improvement.\n- '4': The review text mostly aligns with the prompt, giving a detailed and satisfactory review of the specified movie.\n- '5': The review text perfectly adheres to the prompt, providing an excellent and comprehensive review of the specified movie. \n\nPlease classify the text accordingly, ensuring that the quality of the generated sample is evaluated based on how well it adheres to the given user prompt.\n###\n### Requirements for Challenging Samples:\n1. The generated samples must be challenging and diverse such that using the task instruction as a prompt will result in the wrong result.\n2. The generated samples must be only from the top two scores! With equal distribution between the two.\n3. The generated samples should be distinct, realistic, and vary significantly to ensure diversity.\n\nIf the task depends both on a context, or a user input and a generated content then the sample content must include all the relevant parts.\n    -In this case the sample content structure should be as follows:\n        1. First write the require context or user input.\n        2. Then write the generated content of the model on this context or user input.\n     The style of the separation and the indication of the different parts, should be different in each sample."}], 'model': 'gpt-3.5-turbo', 'n': 1, 'stream': False, 'temperature': 0.8}}
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It seems from the log that you are trying to use GPT-3.5.
Can you try to use the default model?
    name: 'gpt-4-1106-preview'

I have changed to mdoel to gpt-4-1106-preview， and error remains the same. Can you please help me check with the prompt files I use?
predictor:
method : 'llm'
config:
llm:
type: 'azure'
name: '...'
num_workers: 5
prompt: 'prompts/predictor_completion/prediction_generation.prompt'
mini_batch_size: 1 #change to >1 if you want to include multiple samples in the one prompt
mode: 'prediction'
meta_prompts:
folder: 'prompts/meta_prompts_generation'
num_err_prompt: 1 # Number of error examples per sample in the prompt generation
num_err_samples: 2 # Number of error examples per sample in the sample generation
history_length: 4 # Number of sample in the meta-prompt history
num_generated_samples: 5 # Number of generated samples at each iteration
num_initialize_samples: 5 # Number of generated samples at iteration 0, in zero-shot case
samples_generation_batch: 5 # Number of samples generated in one call to the LLM
num_workers: 5 #Number of parallel workers
warmup: 4 # Number of warmup steps

perhaps it's related with settings:
annotator:
method  ： ‘’
gegging for a generating example T.T

This is fine since there is no annotator in the generation optimization (only the evaluator uses the ranker).
I'm suggesting to restore all the default parameters (in all the config files) and verify that there are no changes. Also, verify that you delete the dump folder, and then try to rerun the example.

well I restore all the default parameters, use GPT-4, and run classifying task. I still get 'Keyerror' of 'samples'. So I revised the 'optimization_pipeline.py' scripts and added some parse functions to extract 'Sample #' from the 'text'.
However, generation sample remains unsolved. I get the error:
ValueError: Classification metrics can't handle a mix of unknown and binary targets

It seems that the issue was sensitive to lower/upper cases (you used 'azure' and the system expected 'Azure')
This PR should solve this issue:
https://github.com/Eladlev/AutoPrompt/pull/76


[Umbrella] Support Apache Spark 3.4

Code of Conduct

[X] I agree to follow this project's Code of Conduct

Search before asking

[X] I have searched in the issues and found no similar issues.

Describe the proposal
The latest feature release of Apache Spark 3.4.0 is available now
https://spark.apache.org/news/spark-3-4-0-released.html
Task list

#4741
Kyuubi Spark extension for Spark 3.4
Kyuubi Spark Connectors support Spark 3.4
#4867
#4868

Are you willing to submit PR?

[ ] Yes. I would be willing to submit a PR with guidance from the Kyuubi community to improve.
[ ] No. I cannot submit a PR at this time.

@pan3793
Hi. Dear developers.
When will kyuubi be released and support SPARK 3.4.X?

The main spark sql engine already supports Spark 3.4 in 1.7.1, the additional plugin is planned to support Spark 3.4 in 1.8.0

@BsoBird With blocking issues listed above, the plugins for spark engine highly depends on API and details of LogicalPlan of Spark, which contains lots of breaking changes.

Close as completed


Dev server compiles twice in VSCode

Bug report

What is the current behavior?
webpack-dev-server (via webpack serve) compiles twice on every save in VSCode. This doesn't happen when using an other editor such as Sublime.
If the current behavior is a bug, please provide the steps to reproduce.
Create a fresh package with webpack, webpack-cli and webpack-dev-server as devDependencies.
// src/index.js

console.log("Hi");

Launch the server:
webpack serve --mode=production

Open the src/index.js file in VSCode. You'll notice in the console's output that every time you press save, the code gets compiled twice. Try with an other editor (such as Sublime) and you'll see that compilation occurs once, as expected.

What is the expected behavior?
Compilation should occur only once.

Other relevant information:
webpack version:  v5.67.0
Node.js version: v16.13.0
Operating System:  MacOS Monterey
Additional tools: VSCode v1.63.2 (with default settings + no extensions)

I think this is duplicate of https://github.com/webpack/webpack/issues/15206 .

I don't think so, @vankop. First because downgrading doesn't fix the issue and it happens on VSCode not on Sublime.

Check your save mode in VSCode, maybe your IDE create extra files on saving and trigger to run webpack, sorry I can't reproduce it locally

What do you mean by save mode? It occurs even with the default VSCode config (in which formatOnSave is disabled) and no extensions installed. I tried with a fresh install of VScode, still occurs.

Can you provide stats output?

Sure! Here's what a single save causes:

Do you have webpack.config.js? Sounds like something was changed in source

I'm using the default config here, so no webpack.config.js file, just the webpack serve --mode=production command.

The set-up is really minimal here. You can check: https://github.com/tavoyne/webpack-test.

Sorry, I can't reproduce, it happens only in VSCode? Can you try other IDE/editor, just for testing

Sorry for the delay, I didn't see your reply.
Actually, I just tried on TextEdit (v1.17) and it happened there as well. But again, not on Sublime (Build 4126), surprisingly.
What function is used internally by webpack-dev-server to watch for file changes? Maybe it has something to do with that.

Can you try 5.65.0 version?

YES, it fixes the problem. My bad, I did try downgrading before but to v5.66.0 only...
So this indeed is a #15206 duplicate.


Add Support for TensorRT 8.2

Add stub files for TensorRT 8.2
Fix accuracy regression with MobilenetV2 i.e. set dynamic range for (-6, 6)
Limit GPU memory utilization for TFTRT Integration tests
Fix incorrect usage of TRT version to string API
TensorRT model_tests update

Add separate perf tolerance for FP32, FP16, and INT8
Add separate accuracy tolerance for FP32, FP16, and INT8
Add functionality to dump histograms for better accuracy validation

CC: @DEKHTIARJonathan, @tfeher , and @bixia1

I am taking over the TensorRT 8.2-relevant work for @jhalakp-nvidia . Please see the new PR here https://github.com/tensorflow/tensorflow/pull/52932. @jhalakp-nvidia includes  some other features here that either are already covered by separate PRs or can go into a separate PR.

@jhalakp-nvidia Any update on this PR? Please. Thanks!

Hi, Has this PR been rejected? If yes! does this mean that there is no support for TensorRT 8.x?

If there is no support for TensorRT 8.x, please can you recommend the right version of tensorRT to be used with Tensorflow 2.7.0 on UBuntu 20.04?

Same question as amehrish's. Can we have a compatibility matrix for tensorflow and tensorrt. Please correct me if its already there (couldn't find it) and share the link.


RP_BUNDLE multiple values fix

Resolves #3341

Adds appropriate spaces to fix the autogenerated cloud_config.yaml file.
Added some arbritrary rp_bundle values to the build in this repo to ensure it breaks in future if var handling changes

/test

/test-destroy-env

/test-destroy-env


davmail: 4.8.0 -> 4.8.6

Motivation for this change
Things done

[X] Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS)
Built on platform(s)

[X] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nox --run "nox-review wip"
[X] Tested execution of all binary files (usually in ./result/bin/)
[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[ ] Fits CONTRIBUTING.md.

Success on x86_64-linux (full log)
Attempted: davmail
Partial log (click to expand)
'./lib/woodstox-core-asl-4.1.2.jar' -> '/nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6/share/davmail/lib/woodstox-core-asl-4.1.2.jar'
'./lib/xercesImpl-2.8.1.jar' -> '/nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6/share/davmail/lib/xercesImpl-2.8.1.jar'
post-installation fixup
shrinking RPATHs of ELF executables and libraries in /nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6
strip is /nix/store/h0lbngpv6ln56hjj59i6l77vxq25flbz-binutils-2.30/bin/strip
stripping (with command strip and flags -S) in /nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6/bin
patching script interpreter paths in /nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6
/nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6/share/davmail/davmail.sh: interpreter directive changed from "/bin/sh" to "/nix/store/czx8vkrb9jdgjyz8qfksh10vrnqa723l-bash-4.4-p23/bin/sh"
checking for references to /build in /nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6...
/nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6

No attempt on aarch64-linux (full log)
The following builds were skipped because they don't evaluate on aarch64-linux: davmail
Partial log (click to expand)

a) For `nixos-rebuild` you can set
  { nixpkgs.config.allowUnfree = true; }
in configuration.nix to override this.

b) For `nix-env`, `nix-build`, `nix-shell` or any other Nix command you can add
  { allowUnfree = true; }
to ~/.config/nixpkgs/config.nix.

check darwin build
@GrahamcOfBorg build davmail

No attempt on aarch64-linux (full log)
The following builds were skipped because they don't evaluate on aarch64-linux: davmail
Partial log (click to expand)

a) For `nixos-rebuild` you can set
  { nixpkgs.config.allowUnfree = true; }
in configuration.nix to override this.

b) For `nix-env`, `nix-build`, `nix-shell` or any other Nix command you can add
  { allowUnfree = true; }
to ~/.config/nixpkgs/config.nix.

Success on x86_64-linux (full log)
Attempted: davmail
Partial log (click to expand)
'./lib/woodstox-core-asl-4.1.2.jar' -> '/nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6/share/davmail/lib/woodstox-core-asl-4.1.2.jar'
'./lib/xercesImpl-2.8.1.jar' -> '/nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6/share/davmail/lib/xercesImpl-2.8.1.jar'
post-installation fixup
shrinking RPATHs of ELF executables and libraries in /nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6
strip is /nix/store/h0lbngpv6ln56hjj59i6l77vxq25flbz-binutils-2.30/bin/strip
stripping (with command strip and flags -S) in /nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6/bin
patching script interpreter paths in /nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6
/nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6/share/davmail/davmail.sh: interpreter directive changed from "/bin/sh" to "/nix/store/czx8vkrb9jdgjyz8qfksh10vrnqa723l-bash-4.4-p23/bin/sh"
checking for references to /build in /nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6...
/nix/store/smz0a71p979ppb58mpznajd978wkl425-davmail-4.8.6

Success on x86_64-darwin (full log)
Attempted: davmail
Partial log (click to expand)
'./lib/stax-api-1.0.1.jar' -> '/nix/store/phl6sxkqpcax9xkgd8rq92jxfs3179mc-davmail-4.8.6/share/davmail/lib/stax-api-1.0.1.jar'
'./lib/stax2-api-3.1.1.jar' -> '/nix/store/phl6sxkqpcax9xkgd8rq92jxfs3179mc-davmail-4.8.6/share/davmail/lib/stax2-api-3.1.1.jar'
'./lib/woodstox-core-asl-4.1.2.jar' -> '/nix/store/phl6sxkqpcax9xkgd8rq92jxfs3179mc-davmail-4.8.6/share/davmail/lib/woodstox-core-asl-4.1.2.jar'
'./lib/xercesImpl-2.8.1.jar' -> '/nix/store/phl6sxkqpcax9xkgd8rq92jxfs3179mc-davmail-4.8.6/share/davmail/lib/xercesImpl-2.8.1.jar'
post-installation fixup
strip is /nix/store/vvbmqsh5ikrxkiwj71dwfbzcwf4bfav8-cctools-binutils-darwin/bin/strip
stripping (with command strip and flags -S) in /nix/store/phl6sxkqpcax9xkgd8rq92jxfs3179mc-davmail-4.8.6/bin
patching script interpreter paths in /nix/store/phl6sxkqpcax9xkgd8rq92jxfs3179mc-davmail-4.8.6
/nix/store/phl6sxkqpcax9xkgd8rq92jxfs3179mc-davmail-4.8.6/share/davmail/davmail.sh: interpreter directive changed from "/bin/sh" to "/nix/store/dmgydn3x7ayd7rpfdqw8nrw0z93w549d-bash-4.4-p23/bin/sh"
/nix/store/phl6sxkqpcax9xkgd8rq92jxfs3179mc-davmail-4.8.6


Change default inference from arrays to tuples and primitives to literals

I am working on functional project now and I'm getting a lot of errors related to too wide type inference for values. It looks like
function test(a: { data: 1 | 2 }) { return a }
const a = { data: 2 }
// Types of property 'data' are incompatible.
// Type 'number' is not assignable to type '2'.ts(2345)
const b = test(a)

There're really many errors like this, and the main problem is that you can convert type A to type B, but not vice versa.
type A = { data: 2 }
type B = { data: number }

So, I ask you to add a new compiler option (to not break existing code) that will make type checker infer types as narrow as possible. It will be very helpful for functional programming.

Issue #38727 is related

Also related: #16896

It looks like you want as const:
function test(a: { data: 1 | 2 }) { return a }
const a = { data: 2 } as const;
const b = test(a)

@jgbpercy

It looks like you want as const:

Yes, as const works, but I'm asking for type checker mode where all types will be inferred as const by default.
I use TypeScript based type check for jsdoc type declarations in .js files and I can't use <const> or as const there.

See #32758

@RyanCavanaugh no, #32758 is not my proposal. They want, for example, use ReadonlyArray<number> instead of Array<number> for this case
const a = [1, 2, 3]

or use readonly modifier for object properties by default.
I'm asking for a type checker mode where types will be inferred as 'literal' (literals instead of basic types) as possible.
// Got: Array<number>
// Proposal: [1, 2]
const a = [1, 2]

declare function b<T extends Array<unknown>>(...args: T): T

// Got: [number, number, number]
// Proposal: [1, 2, 3]
const c = b(1, 2, 3)

// Got: { data: number }
// Proposal: { data: 2 }
const b = { data: 2 }

etc

@RyanCavanaugh please reopen this issue. It is not duplicate.

@awerlogus I don't see any measurable difference between these issues. Certainly we would implement that flag as applying equally to both arrays and objects - are you saying we would need two different flags, one for arrays, one for objects?

@RyanCavanaugh as I said 2 times before, I don't ask you to add a compiler mode, where all types will be readonly. My proposal is a mode to make type checker prefer inferring entities as literals over basic types when it's possible. Using number literals over number type, string literals over string type, boolean literals over boolean type, tuples over arrays, etc.
Examples are available here: https://github.com/microsoft/TypeScript/issues/38831#issuecomment-643007664

I guess I'd like to understand you think isn't read-only about the type [1, 2]

I think, and correct me if I'm wrong @awerlogus , that you essentially want a mode where every expression has as const implicitly appended to it, in the absence of any explicit wider type?

@jgbpercy the expression as const is being used to solve two different problems in the same time: the first is inferring types as literal as possible (that thing which I'm asking for in this issue), and the second is marking arrays or object properties as readonly (this is not my proposal). We need a new type checker mode to solve the first problem only. Other than that is completely as you said.

@RyanCavanaugh I didn't say that we should or should not mark tuples or objects as readonly. I meant that it doesn't matter in the context of this issue. You may add that readonly mode in parallel. But if we will analyse the problem of mutable/readonly values, we may find that the type [1, 2] is not safe enough. The type of variable a may be easily broken by the code like
const a: [1, 2] = [1, 2]

// Legal
a.push(1)

// [1, 2]
const b = a

Readonly tuple will not allow it
const c: readonly [1, 2] = [1, 2]

// Error
c.push(1)

So, the question becomes: should we have any access to mutating array methods in case of mutable tuples?
Except for this, tuples and readonly tuples will work the same in context of literal elements. But it is not possible to convert readonly tuples to mutable ones, so we should prefer inferring all tuples as mutable by default then. If someone needs exactly readonly tuple, he can perform a safe type cast, it is not a problem.
Almost the same problems with objects:
There're functions like Object.defineProperty that can bypass the type system even if properties are marked as readonly.
const a: { readonly data: 2 } = { data: 2 }

// Should not be valid
Object.defineProperty(a, 'data', { value: 3 })

const b: { data: 2 } = { data: 2 }

// Should not be valid too
Object.defineProperty(b, 'data', { value: 3 })

It should be fixed, I think.
If we will need some mutable object, it will be not possible to get it from readonly one without any hacks, so we should prefer inferring objects by default as mutable too.

I think, good programming language should help developers write the better code. And in the good code all data types and its transformations are managed by functions. There're some types that expected to be passed into and returned from functions. Types of variables and constants should be inferred as narrow as possible to may be correctly passed to as many functions as possible. Let me show an example:
declare function a<T extends { readonly data: number }>(arg: T): T['data']
declare function b<T extends { readonly data: 1 | 2 }>(arg: T): T['data']

// Now: { data: number }
// Proposed: { data: 2 }
const c = { data: 2 }

Now variable c may be passed to the function a only (without of hacking type system). When the new type checker mode will be added, it will be available to pass c to both functions — a and b.
p.s. There's no as const in js

@jgbpercy the expression as const is being used to solve two different problems in the same time: the first is inferring types as literal as possible (that thing which I'm asking for in this issue), and the second is marking arrays or object properties as readonly (this is not my proposal). We need a new type checker mode to solve the first problem only. Other than that is completely as you said.

@awerlogus would you consider editting the description of the issue, adding this info? I think it answers all questions about your proposal.
I also agree it may be nice for them to be two separate flags.
Also may consider renaming suggestion to "implicit as-const for type narrowing flag" or "--strict-type-narrowing flag"?
Question: are there cases in which this flag could be harmful?
Also: now that records and tuples are stage 2, could this (or even both) issues be (partially) addressed by that proposal instead, with no (or little) change to TS?

@lautarodragan

@awerlogus would you consider editting the description of the issue, adding this info? I think it answers all questions about your proposal.

All this conversation is the issue description. So info described in that comment already exists here. I always read comments under issues I'm interested. If someone doesn't do that is means they're not interested enough.

are there cases in which this flag could be harmful?

If you prefer working with mutability it can make you cast types to more general ones too often. For example cast [1, 2] to [number, number] or even Array<number>. But the good part is that it doesn't violate the rules of the type system. Currently we have to use @ts-ignore or as any as ... to make existing types more literal because it is not correct to cast [number, number] to [1, 2].
Also even currently when we modelling function overloading without overloading (because it's designed bad) we may have some problems with types inferred too literally. For example let's try to rewrite this function
function add(a: number, b: number): number
function add(a: bigint, b: bigint): bigint
function add(a: any, b: any) { return a + b }

It will look like
function add<P extends [a: number, b: number] | [a: bigint, b: bigint]>(...data: P): P[0] {
  return data[0] + data[1]
}

If we call it, we will get return type equal to the first argument because P will be inferred as [1, 2]
// Got: 1
const a = add(1, 2)

So it makes us generalize return type of the function and use P[0] extends bigint ? bigint : number instead of just P[0].
I think such cases of generalization necessity will occur more often when using the flag.
This example also produces an error:
function add<P extends [a: number, b: number] | [a: bigint, b: bigint]>(...data: P): P[0] extends bigint ? bigint : number {
  // Operator '+' cannot be applied to types 'number | bigint' and 'number | bigint'.ts(2365)
  return data[0] + data[1]
}

@RyanCavanaugh do we have an issue describing the error above?

now that records and tuples are stage 2, could this (or even both) issues be (partially) addressed by that proposal instead, with no (or little) change to TS?

It's a good question. How about mutable objects containing enums? This example will still not work after adding records and tuples
function test(a: { data: 1 | 2 }) { return a }
const a = { data: 2 }
// Types of property 'data' are incompatible.
// Type 'number' is not assignable to type '2'.ts(2345)
const b = test(a)

I have to say that I would definitely like something like this to exist. My use case involves my most common use of typing functions, namely type Array.prototype.map to be a tuple instead of an array of either type.
Example:
function getOtherData(from:T): R { ... }

const sourceArray: T[] = ...;
...
sourceArray
    .map(elem => [elem, getOtherData(elem)]
    .map([elem, other] => { ... }); // here both `elem` and `other` have type `T | R`

I have to say that I would definitely like something like this to exist. My use case involves my most common use of typing functions, namely type Array.prototype.map to be a tuple instead of an array of either type.
Example:
function getOtherData(from:T): R { ... }

const sourceArray: T[] = ...;
...
sourceArray
    .map(elem => [elem, getOtherData(elem)]
    .map([elem, other] => { ... }); // here both `elem` and `other` have type `T | R`

So, I ask you to add a new compiler option (to not break existing code) that will make type checker infer types as narrow as possible. It will be very helpful for functional programming.

"make type checker infer types as narrow as possible" seems like the idea of immutability. And is discussed at least in one other issue https://github.com/microsoft/TypeScript/issues/32758 .

I'm asking for a type checker mode where types will be inferred as 'literal' (use literals instead of basic types) as possible.
(from https://github.com/microsoft/TypeScript/issues/38831#issuecomment-643007664)

I cannot see the difference between the 'literal' proposed by @awerlogus , and the literal type from 'readonly'. Could you explain more?
I still think this issue can be closed without further information (note that it has been 2 years without reply). @RyanCavanaugh @typescript-bot


Webpack 4

I didn't see any issues relating to webpack 4 (there's one with v3). Is there anyway to get this working with<EMAIL_ADDRESS><EMAIL_ADDRESS>and<EMAIL_ADDRESS>Currently getting these errors:
ERROR in ./node_modules/css-loader??ref--5-1!./node_modules/postcss-loader/lib??postcss!./node_modules/sass-loader/lib/loader.js!./node_modules/sass-resources-loader/lib/loader.js??ref--5-4!./src/components/Views/NotFound/NotFound.scss
Module build failed: TypeError: Cannot read property 'context' of undefined
    at Object.module.exports (/Users/me/code/company/project/static/react/node_modules/sass-resources-loader/lib/loader.js:62:46)

This happens when trying to do a regular import/composes/mixin (this worked fine with webpack v3):
.container {
  @include size(100%, 100%);
  composes: flexyCentered from 'styles/_classes.scss'
}

my bad! just saw a PR that fixes this.. https://github.com/shakacode/sass-resources-loader/pull/59


Cannot enable subscriptions for site

https://github.com/tableau/server-client-python/blob/b7b544e5ef405ca76f9e0c5681b001373811c6b2/tableauserverclient/server/request_factory.py#L285
The condition here means disable_subscriptions will not be written into the request if site_item.disable_subscriptions is not None or site_item.disable_subscriptions != False
Looks like when the value is not None we need to update the site with given value (could be True or False), however, False would be ignored here along with None, which means you can never update site to site.disable_subscriptions = False
Should change to if site_item.disable_subscriptions is not None

@shinchris to close this when the merge is done and this is ready to go.


Proofreading - Set Up Error Handling -and- Error Event

Mainly resize images and fix some small language issues

@Yiyun333 , overall it looks good, I left some minor comments and suggestions.

@Yiyun333 , overall it looks good, I left some minor comments and suggestions.

@MariaShaposhnikova Thanks a lot for the feedback!

You can merge this, as far as I'm concerned. Looks great. Really adds some clarity to a bunch of docs which was not very well structured. Thanks Mark

Thanks, Mark!


Create custom get by id function

Right now, activeresource's GET format for an object with id <id> is:
.../courses/<id>.json

Yet YACS's format is:
/api/v5/courses.json?id=<id>

This makes the show view a lot more complicated than thought.
Create a custom function to get around this in the show function

@kburk1997 I am currently adding support for .../courses/.json. Assume that all standard restful routes will be available :)

@Bad-Science thanks so much!


Web Demo doesn't work on Windows/Chrome 122

Posting for @xStrom

The demo doesn't seem to work for me. I have Chrome 122.0.6261.95 on Windows 11. Other WebGPU sites work.
I saw a comment in a wgpu issue talking about web-sys and stating:
write_timestamp was removed fairly recently, this was before chrome shipped the timestamp feature.
That's exactly the method that is being called by this example but not found.

with_winit_bin.js:1286 Uncaught TypeError: getObject(...).writeTimestamp is not a function
    at imports.wbg.__wbg_writeTimestamp_a36ba108891c9491 (with_winit_bin.js:1286:25)
    at web_sys::features::gen_GpuCommandEncoder::GpuCommandEncoder::write_timestamp::hc04980a6c6c0a560 (with_winit_bin_bg.wasm:0x2be5fd)
    at <T as wgpu::context::DynContext>::command_encoder_write_timestamp::h341843ef2312ba8f (with_winit_bin_bg.wasm:0x2b48b4)
    at wgpu::CommandEncoder::write_timestamp::hdc743a111a19b160 (with_winit_bin_bg.wasm:0x2a985e)
    at <wgpu::CommandEncoder as wgpu_profiler::profiler_command_recorder::ProfilerCommandRecorder>::write_timestamp::h371bed9620e016b4 (with_winit_bin_bg.wasm:0x2bf317)
    at wgpu_profiler::profiler::GpuProfiler::begin_query::h51dd4b508aa26c19 (with_winit_bin_bg.wasm:0x223e0c)
    at vello::wgpu_engine::WgpuEngine::run_recording::h10328973bb07778a (with_winit_bin_bg.wasm:0x47518)
    at vello::Renderer::render_to_texture::h60899975c694b1fd (with_winit_bin_bg.wasm:0x23f437)
    at vello::Renderer::render_to_surface::h1263f84f542bef9c (with_winit_bin_bg.wasm:0x158b90)
    at winit::platform_impl::platform::event_loop::EventLoop<T>::run::{{closure}}::hc5018c790fcf1933 (with_winit_bin_bg.wasm:0x69c94)
imports.wbg.__wbg_writeTimestamp_a36ba108891c9491   @   with_winit_bin.js:1286
$web_sys::features::gen_GpuCommandEncoder::GpuCommandEncoder::write_timestamp::hc04980a6c6c0a560    @   with_winit_bin_bg.wasm:0x2be5fd
$<T as wgpu::context::DynContext>::command_encoder_write_timestamp::h341843ef2312ba8f   @   with_winit_bin_bg.wasm:0x2b48b4
$wgpu::CommandEncoder::write_timestamp::hdc743a111a19b160   @   with_winit_bin_bg.wasm:0x2a985e
$<wgpu::CommandEncoder as wgpu_profiler::profiler_command_recorder::ProfilerCommandRecorder>::write_timestamp::h371bed9620e016b4    @   with_winit_bin_bg.wasm:0x2bf317
$wgpu_profiler::profiler::GpuProfiler::begin_query::h51dd4b508aa26c19   @   with_winit_bin_bg.wasm:0x223e0c
$vello::wgpu_engine::WgpuEngine::run_recording::h10328973bb07778a   @   with_winit_bin_bg.wasm:0x47518
$vello::Renderer::render_to_texture::h60899975c694b1fd  @   with_winit_bin_bg.wasm:0x23f437
$vello::Renderer::render_to_surface::h1263f84f542bef9c  @   with_winit_bin_bg.wasm:0x158b90
$winit::platform_impl::platform::event_loop::EventLoop<T>::run::{{closure}}::hc5018c790fcf1933  @   with_winit_bin_bg.wasm:0x69c94
$winit::platform_impl::platform::event_loop::runner::Shared::handle_event::h75b74ccbc82d1ca4    @   with_winit_bin_bg.wasm:0x186394
$winit::platform_impl::platform::event_loop::runner::Shared::set_listener::hdb653fd17bd31882    @   with_winit_bin_bg.wasm:0x9ffe6
$winit::platform_impl::platform::event_loop::window_target::EventLoopWindowTarget<T>::run::h128045b0a7018bd0    @   with_winit_bin_bg.wasm:0x2bc7b2
$winit::platform_impl::platform::event_loop::EventLoop<T>::run::hae52ee5a18803b96   @   with_winit_bin_bg.wasm:0x2ac765
$with_winit::main::{{closure}}::h25f47348c2844206   @   with_winit_bin_bg.wasm:0x64a8a
$wasm_bindgen_futures::queue::Queue::new::{{closure}}::hd9b5f57ec5224f57    @   with_winit_bin_bg.wasm:0x2193c0
$<dyn core::ops::function::FnMut<(A,)>+Output = R as wasm_bindgen::closure::WasmClosure>::describe::invoke::h22ad83e018fc1110   @   with_winit_bin_bg.wasm:0x2bbdde
__wbg_adapter_68    @   with_winit_bin.js:248
real    @   with_winit_bin.js:209

Since #497 was merged this issue has been resolved. 🎉


Windows enforcer pid allow

Allow enforcer self-traffic

/build - automatically fired by gogo with following PRs and commit SHAs v1.0.0
[
  {
    "project": "windows-enforcer-pid-allow",
    "component": "trireme-lib",
    "pr-id": "1027",
    "commit-sha": "a062851552910d514e622e5577e01011c70fc426",
    "pipeline": "master"
  },
  {
    "project": "windows-enforcer-pid-allow",
    "component": "enforcerd",
    "pr-id": "1824",
    "commit-sha": "37634b92b33a9731df9a3facb370084feacb83bc",
    "pipeline": "master"
  }
]

/build - automatically fired by gogo with following PRs and commit SHAs v1.0.0
[
  {
    "project": "windows-enforcer-pid-allow",
    "component": "enforcerd",
    "pr-id": "1824",
    "commit-sha": "37634b92b33a9731df9a3facb370084feacb83bc",
    "pipeline": "master"
  },
  {
    "project": "windows-enforcer-pid-allow",
    "component": "trireme-lib",
    "pr-id": "1027",
    "commit-sha": "a062851552910d514e622e5577e01011c70fc426",
    "pipeline": "master"
  }
]

/build - automatically fired by gogo with following PRs and commit SHAs v1.0.0
[
  {
    "project": "windows-enforcer-pid-allow",
    "component": "enforcerd",
    "pr-id": "1824",
    "commit-sha": "37634b92b33a9731df9a3facb370084feacb83bc",
    "pipeline": "master"
  },
  {
    "project": "windows-enforcer-pid-allow",
    "component": "trireme-lib",
    "pr-id": "1027",
    "commit-sha": "a062851552910d514e622e5577e01011c70fc426",
    "pipeline": "master"
  }
]

/build - automatically fired by gogo with following PRs and commit SHAs v1.0.0
[
  {
    "project": "",
    "component": "trireme-lib",
    "pr-id": "1027",
    "commit-sha": "a062851552910d514e622e5577e01011c70fc426",
    "pipeline": "master"
  }
]

/build - automatically fired by gogo with following PRs and commit SHAs v1.0.0
[
  {
    "project": "windows-enforcer-pid-allow",
    "component": "enforcerd",
    "pr-id": "1824",
    "commit-sha": "37634b92b33a9731df9a3facb370084feacb83bc",
    "pipeline": "master"
  },
  {
    "project": "windows-enforcer-pid-allow",
    "component": "trireme-lib",
    "pr-id": "1027",
    "commit-sha": "a062851552910d514e622e5577e01011c70fc426",
    "pipeline": "master"
  }
]

/build - automatically fired by gogo with following PRs and commit SHAs v1.0.0
[
  {
    "project": "windows-enforcer-pid-allow",
    "component": "enforcerd",
    "pr-id": "1824",
    "commit-sha": "37634b92b33a9731df9a3facb370084feacb83bc",
    "pipeline": "release-3.14.0"
  },
  {
    "project": "windows-enforcer-pid-allow",
    "component": "trireme-lib",
    "pr-id": "1027",
    "commit-sha": "a062851552910d514e622e5577e01011c70fc426",
    "pipeline": "release-3.14.0"
  }
]

/build - automatically fired by gogo with following PRs and commit SHAs v1.0.0
[
  {
    "project": "windows-enforcer-pid-allow",
    "component": "enforcerd",
    "pr-id": "1824",
    "commit-sha": "37634b92b33a9731df9a3facb370084feacb83bc",
    "pipeline": "release-3.14.0"
  },
  {
    "project": "windows-enforcer-pid-allow",
    "component": "trireme-lib",
    "pr-id": "1027",
    "commit-sha": "a062851552910d514e622e5577e01011c70fc426",
    "pipeline": "release-3.14.0"
  }
]

/build - automatically fired by gogo with following PRs and commit SHAs v1.0.0
[
  {
    "project": "windows-enforcer-pid-allow",
    "component": "enforcerd",
    "pr-id": "1824",
    "commit-sha": "d7f1dde78dbcf610173227796b7cac833942b89e",
    "pipeline": "release-3.14.0"
  },
  {
    "project": "windows-enforcer-pid-allow",
    "component": "trireme-lib",
    "pr-id": "1027",
    "commit-sha": "a062851552910d514e622e5577e01011c70fc426",
    "pipeline": "release-3.14.0"
  }
]

/build - automatically fired by gogo with following PRs and commit SHAs v1.0.0
[
  {
    "project": "windows-enforcer-pid-allow",
    "component": "enforcerd",
    "pr-id": "1824",
    "commit-sha": "d7f1dde78dbcf610173227796b7cac833942b89e",
    "pipeline": "release-3.14.0"
  },
  {
    "project": "windows-enforcer-pid-allow",
    "component": "trireme-lib",
    "pr-id": "1027",
    "commit-sha": "a062851552910d514e622e5577e01011c70fc426",
    "pipeline": "release-3.14.0"
  }
]

/build - automatically fired by gogo with following PRs and commit SHAs v1.0.0
[
  {
    "project": "windows-enforcer-pid-allow",
    "component": "enforcerd",
    "pr-id": "1824",
    "commit-sha": "29a1c5c5e7560e973671acab8874ae57728170bb",
    "pipeline": "release-3.14.0"
  },
  {
    "project": "windows-enforcer-pid-allow",
    "component": "trireme-lib",
    "pr-id": "1027",
    "commit-sha": "a062851552910d514e622e5577e01011c70fc426",
    "pipeline": "release-3.14.0"
  }
]


Go to definition on identifier in macro call fails

In GTest jumping to the fixture class from a test declaration does not work:
class FixtureName ... {
....
};
TEST_F(FixtureN^ame, testname) ...

#define TEST_F(test_fixture, test_name)\
  GTEST_TEST_(test_fixture, test_name, test_fixture, \
              ::testing::internal::GetTypeId<test_fixture>())

#define GTEST_TEST_(test_suite_name, test_name, parent_class, parent_id)      \
...
  class GTEST_TEST_CLASS_NAME_(test_suite_name, test_name) : public parent_class {                                                 \

It jumps to the start of the TEST_F line or to the enclosing namespace.
System information
Output of clangd --version: 10.0.1
Editor/LSP plugin: VSCode

This works for me in the clangd codebase (which also uses GTest).
We'll likely need a complete example to diagnose further.

Actually, this might have been fixed in #234, and that fix just didn't make LLVM 10.
(Not sure how exactly to tell when LLVM 10 branched.)

Ok, I've confirmed that the fix for #234 is not present on the LLVM 10.x branch. And based on the definition of TEST_F, this is definitely the sort of thing that would have been fixed by #234 (macro argument appears in expansion multiple times).
So, I'm going to close this as a dupe of #234 (but feel free to reopen if you still see this bug with clangd 11).


Pass options to the used router

Is there currently any way to pass options to the underlying used router?
I would like to use @tanstack/react-router and pass the beforeLoad option to it. I need this to provide data sequentially to the next matched route, for example auth data, and populate some @tanstack/react-query queries through ensureQueryData, but the queries depend on the results of the ones before them.

@ferretwithaberet You can customize the router options by using the routes export:
const router = createRouter({ routeTree: routes, ...options })
const Routes = () => <RouterProvider router={router} {...options} />

As for the route options, it supports the basic options similar to the other supported routers: Loader and Action functions, Pending and Catch components.
I had planned to update this integration to align more with TanStack but was awaiting first some TanStack APIs changes to make it possible. I'll update this issue once something new comes up.


ARROW-616: [C++] Do not include debug symbols in release builds by default

This reduces binary size on Linux by about 80-90%. If the user wants them, they can enable with -DARROW_CXXFLAGS="-g".

+1


Move test dashboard and visit.llnl.gov site to gh-pages site

Currently, we host VisIt's test results "dashboard" via https from /project at NERSC. Because our subversion repo wasn't hosted via http their as well (or was but that functionality was removed), we took to copying a ton of test result (e.g. baselines) content from our repo to the "dashboard" (as opposed to simply linking to it) for each test run.
On NERSC's /project, that was hugely abusive (due to file block size quantification), each test run taking ~1.5Gb, whereas the same html dir-tree on Linux is ~100Mb. When we include savings due to even modest revision of the way we gen dashboard results, I believe it is possible to cut per-test storage cost < ~10Mb per run (way less when all/most tests pass).
With GitHub limit of 1000Mb on repo and gh-pages served site, that would allow us to host 100+ past results without exceeding GitHub limits. At 3-5 modes per night, thats >20-33 past results which I think is perfectly sufficient for our needs.
Beyond the fact that GitHub pages site is an available resource and we can make it work, I see a number of advantages in moving this aspect of our project to GitHub...

We are no longer dependent on NERSC /project or NERSC servers to host test dashboard
GitHub is a large company with a lot of experience hosting a lot of projects. It doesn't break down.
We don't need special access (ssh proxy with 1 week limits) to publish results
More core developers have more natural/immediate access to affect changes or respond to things when they break
It makes VisIt development more one-stop-shopping @ GitHub instead of a frankenstien of resources (which I see value in getting away from)
We have a lot of tools for controlling look and feel of the dashboard site
We can support test results from multiple user's runs who wouldn't ordinarily have an account on NERSC to scp results to.

I think several similar arguments apply to content on visit.llnl.gov...we should move it to a gh-pages site and have visit.llnl.gov simply re-direct to that new site. Its easier to modify, update, change look and feel, etc.
For an example of what I am talking about, see here...
https://visit-dav.github.io/dashboard/
In particular, follow the "Test" tab to get to very simple brute-force copy of a recent test result. None of the other links there work because I was just trying to stand up a simple demo of what is possible and, in particular, show that emulating the current look-and-feel is totally doable, but that we can easily edit the content ourselves, as I did to add the "Test" tab.

@brugger1 Would you consider this half done with the test suite results on github pages? Are we still considering moving the main visit.llnl.gov site to github pages?

Yes, this is half done and we still want to move our main website to github. I expect we will keep the existing one, greatly reduced with pointers to the GitHub one. I expect the LLNL one wouldn’t need updating very often and definitely not with each new release.

Lets not forget about these pages on llnl wci pages also...
https://wci.llnl.gov/simulation/visualization

Remaining tasks for web-site switch over...

[ ] set correct access permissions on website repo
[ ] set branch protection rules on website repo
[ ] decide/finalize website repo name...that website's native URL is https://visit-dav.github.io/<repo-name>
[ ] contact correct LLNL people to setup redirect of visit.llnl.gov to new web site
[ ] decide what content to remain on WCI web pages

[ ] past binary release
[ ] a page describing VisIt
[ ] Anything else

[ ] contact correct LLNL people to setup a URL alias/redirect for docs.visit.llnl.gov
[ ] Review the WCI visualization tools page

@brugger1 I've made a check list for website items. Please feel free to edit that comment if you need to add more items or you can check/uncheck (which does an edit operation behind the scenes anyways).

FYI...I've reviewed the one page about WCI visualization tools and find...

some useful concepts and verbiage but seems to SND specific. I don't even know what SND is.
Probably a lot of verbiage here is dated.
Only the link to visit works. The other two are broken.
The image is pretty poor quality and not even sure what it is an image of

Some possible ways to go...

can we just delete this page?
we should include a link to PyDV
if we want something to continue, we should mention Ascent, maybe include the corona-virus like picture of spherical RT calc, maybe steal verbiage from visit.llnl.gov (though the page is apparently intended to be about visualization in general and not VisIt specifically

I agree, that page should probably be removed. I don't know what SND is and they don't actually define the term or give anymore information about it. I tried searching for it and found nothing. Since I don't know anything about it, I have no idea who "owns" that content. I will mention it though. It seems like if the page exists, VisIt should be mentioned.

I am completely baffled by how this comment was removed/lost.
It was there earlier and now its gone and no record
"Mark C. Miller" wrote:
Remaining tasks for web-site switch over...
·         set correct access permissions on website repo
·         set branch protection rules on website repo
·         decide/finalize website repo name...that website's native URL is https://visit-dav.github.io/
·         contact correct LLNL people to setup redirect of visit.llnl.gov to new web site
·         decide what content to remain on WCI web pages
o    past binary release
o    a page describing VisIt
o    Anything else
·         contact correct LLNL people to setup a URL alias/redirect for docs.visit.llnl.gov
·         Review the WCI visualization tools page
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHubhttps://github.com/visit-dav/visit/issues/16#issuecomment-746920656, or unsubscribehttps://github.com/notifications/unsubscribe-auth/ABLUUZDA7DVMA2VEUTCHWE3SVEGLVANCNFSM4GR6ULAA.

Ok, putting this check list back in

[ ] set correct access permissions on website repo
[ ] set branch protection rules on website repo
[ ] decide/finalize website repo name...that website's native URL is https://visit-dav.github.io/
[ ] contact correct LLNL people to setup redirect of visit.llnl.gov to new web site
[ ] decide what content to remain on WCI web pages

[ ] past binary release
[ ] a page describing VisIt
[ ] Anything else

[ ] contact correct LLNL people to setup a URL alias/redirect for docs.visit.llnl.gov
[ ] Review the WCI visualization tools page

I saw it there earlier as well.

Yep, all the items in this issue have been addressed


scip interface (first version)

with help of Mark Turner from SCIP.
Now... turns out that @IgnaceBleukx  already worked on a SCIP interface too, about a year ago (e.g. SCIP branch
So maybe Ignace can now make a best of both worlds? : )
(current branch is up to date with current template, but the add part is minimal, e.g. reified linear is not properly tested/supported at the least).

Updated the interface somewhat, it seems SCIP does not have the fancy Min/Max/Abs constraints built-in in its API : /
Added the SOS1 and cardinality constraints to the interface too, these constraints are created when decomposing alldiff for example so definately usefull to have them imho. We should also add them to the Gurobi interface
SolveAll is in a weird state for PySCIPOpt: SCIP does allow for retrieving all feasible solutions, but the Python interface does not seem to allow for collecting the solutions which are found... Added the issues to track in the code so we can add the specialized implementation when these are resolved.
All tests are passing so ready for review I think.

I get an error for optimization problems:
\cpmpy\solvers\scip.py", line 154, in solve
    self.objective_value_ = scip_objective.getObjVal()
AttributeError: 'pyscipopt.scip.Expr' object has no attribute 'getObjVal'

I get an error for optimization problems:
\cpmpy\solvers\scip.py", line 154, in solve
    self.objective_value_ = scip_objective.getObjVal()
AttributeError: 'pyscipopt.scip.Expr' object has no attribute 'getObjVal'

This should now be addressed in one of my points above

@IgnaceBleukx @tias I haven't run anything, and truthfully haven't tried to understand the larger code base, but I've gone through and given comments that I think should make the interface work.
For a final point: While min / max expressions probably won't work, SCIP can handle the absolute value expressions fairly easily. I'm just not sure where to add them in the current code without some guidance.


Updates SendGrid vars and examples

SendGrid was being passed a string in variables.tf while SendGrid_notifiers expected a list.
I could not get SendGrid to fire off email until I updated this variable type and matched the name to dest_email_addresses.
Also updates the tfvars.example files that include SendGrid

Happy to help fix things :) Updated the lambda/tests/data/ggcanary_lambda_parameters.json now, but would love review. I am a little iffy on my lambda testing

Ok the CI checks fail because it's running from a fork - will be ok when it's merged !


Replace del list element removal with remove(), fix #11

$ python3 gcpbucketbrute.py -u -k aa

Generated 1215 bucket permutations.

    EXISTS: 01aa
    EXISTS: aastorage
    EXISTS: aa_staging
    EXISTS: aa-sql
    EXISTS: sqlaa
    EXISTS: backupsaa
    EXISTS: aagcp
    EXISTS: aa_test
    EXISTS: test-aa
    EXISTS: aa01
    EXISTS: bakaa
    EXISTS: aa-web
    EXISTS: testaa
    EXISTS: aa-files

    UNAUTHENTICATED ACCESS ALLOWED: aamobile
...

Hey guys, any chance you can merge in this PR? Thanks!


Can the project be deployed to serverless?

Can the project be deployed to serverless?

do you mean https://serverless.com/ or https://www.cloudflare.com/learning/serverless/what-is-serverless/ ? It is kinda generic word.

@juanpicado
`// @flow
import serverless from 'serverless-http';
import { startVerdaccio } from './lib/bootstrap';
export const submit = async (event, context) => {
const { app } = await new Promise((resolve, reject) => {
startVerdaccio({}, '4873', '', module.exports.version, module.exports.name, (webServer, addr, pkgName, pkgVersion) => {
resolve({
app: webServer,
});
});
});
const handler = serverless(app);
return await handler(event, context);
};
`
This is the handler file. I compiled the project, uploaded the file to serverless, and then responded to the result of 403.

@juanpicado i'd like to know for the latter, the generic case. zeit now, aws lambda, etc, any plans for targeting these kinds of platforms?

hi @acao, unless someone with experience in such platforms and willing to invest time on research, integration, testing and documentation, it will remain like it is. It is possible? I don't know is even is possible with the current design, unfortunately have 0 experience with those.
I'm focused only on Docker and traditional installations.


Some refactor and html input support

I've done some refactoring to support https://www.image-map.net/ html output.
Interested to take over these changes and create a 1.0.0 release?

Thank you for your effort! I really appreciate it!
I will let this PR merge. Also, if you are willing to, can you include a brief introduction about https://www.image-map.net/ and put it in README.md?
Thanks again for your work!


IOS VPN crash without any errors

 DispatchQueue.global(qos: .background).async {
      tun2proxy_with_fd_run("socks5://xx.xx.xx.xx:xx",self.tunnelFileDescriptor!,true,true,1500,Tun2proxyDns_Virtual,Tun2proxyVerbosity_Off);
}

I simply invoke the method like this,  the VPN will automatically crash randomly after about 20 minutes. maybe OOM ???
TEST under 0.6.4

Need more details. you can debug rust code from Xcode. see this.


bump guzzlehttp/guzzle version

Required for usage with Laravel 8 (cfr. https://laravel.com/docs/8.x/upgrade#updating-dependencies). The API is the same, and no other changes are required.

Required for usage with Laravel 8 (cfr. https://laravel.com/docs/8.x/upgrade#updating-dependencies). The API is the same, and no other changes are required.

Ok I understand I will merge your changes when CI tools and checks will be successful.

May thanks @madbob for your contribution.


How to set a max number of particles to show?

After a certain number of particles is reached, the performance of websites is really bad.
I am wondering if there's a way I can set a max number of particles that can be shown, and if there's not one yet, if you could add it in the future.
Thanks in advance.

particles > number > value in the JSON


reproduce results

Hi,
Wanted to try and reproduce the results of the paper, but analysis.py imports RandomMeshGenerator which does not exist anywhere.
Can you help me with the steps the to reproduce results of the paper?
@tailintalent @WillDreamer
thanks in advance

Hi,
I  also encountered an issue when running analysis.py. It tries to use RandomMeshGenerator, but this class or function is not defined anywhere in the project.
Could you please clarify if RandomMeshGenerator was removed or if there is a missing file?
Thanks in advance!

Thanks for your reminder. We have update RandomMeshGenerator in utilities.py.


No need to set total weight anymore

Please provide a description of this PR:
TotalWeight is now an optional field, which defaults to the behavior we added before.

@hzxuzhonghu: The following test failed, say /retest to rerun all failed tests or /retest-required to rerun all mandatory failed tests:

Test name
Commit
Details
Required
Rerun command

unit-tests_istio
bbd27e4c4accb5c0b20124cbbe3eb070872888e9
link
true
/test unit-tests_istio

Instructions for interacting with me using PR comments are available here.  If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository. I understand the commands that are listed here.

Do we need version check for this?

link to envoy PR https://github.com/envoyproxy/envoy/pull/21892

No need to introduce a version check to clean TotalWeight set, which is a small stuff.


Quick access to proxy log with a default docker log driver

When I try to get container log into file by executing this command:
docker logs $(docker ps --filter "name=proxy_proxy*" -q) > proxy.log I get empty file and content of log on screen
Docker version 17.04.0-ce, build 4845c56
docker-compose version 1.11.2, build dfed245
docker info | grep 'Logging Driver'
Logging Driver: json-file

The fix is available in the release 1.386. Can you please try it out and let me know if you experience any problem.

Awesome. It works as expected.


speed / following and friends

Hi,
Hope you are all well !
Would be awesome to create channels (like in golang) for processing more usernames per seconds and to check followers or following accounts. ^^
Cheers

Hey, it's been a while! I'll get back to the project soon and work on that suggestion. Thank you!

I made a version with twint also
https://github.com/x0rzkov/botblocker-twint


current Python "main-workshop" code fails to deploy

:bug: Bug Report
What is the problem?

git clone git@github.com:aws-samples/aws-cdk-intro-workshop.git
cd aws-cdk-intro-workshop/code/python/main-workshop
$ cdk deploy
  File "app.py", line 5
    from cdk-workshop.cdk-workshop_stack import CdkWorkshopStack
            ^
SyntaxError: invalid syntax

Reproduction Steps

Verbose Log

Environment

CDK CLI Version: 1.106.1 (build c832c1b)
Section:
Browser:
Language: Python

Other information

Hey @gliptak :wave:
Thanks for bringing this to our attention and for opening a PR! It looks like you found the issue which seems to be related to using - in the python directories and file names.
I marked this as p2 which means we're unable to work on this immediately but since you've implemented the fix that should expedite the process. By the way here's our contribution guidelines if you have any questions related to contributing.
Thanks!


Update to depend upon showdown

The showdown extensions should depend upon showdown in the bower.json file. This helps task automation tools order the plugins in the right order. These plugins should go after showdown is already defined.

@SyntaxRules The reason we aren't requiring showdown as a dependency is that, currently, extensions are still bundled with showdown. We're still in the process of removing them completely from the core library.
The next release (of showdown and concomitant extensions) will include showdown as a dependency in bower and package json.

Yes, I understand that. Extension being in a separate library is a good thing (in my opinion).
I'm not clear why this pull request can't be accepted now? It won't affect bower user's- only users who are pulling master because they want the bleeding edge.


[Feature] Collapsable left-hand navigation bar

I have checked all the prerequisites below and I'm yet experiencing a problem

[x] Read the README.md
[x] Have the extended version of Hugo installed
[x] Used the exampleSite's config.toml as a reference

Describe the feature
The nav bar on the left-hand side is nice, but for some page content (like tables) you could really use the extra screen width. It'd be helpful if users could optionally collapse that side bar on the left and have the content on the page re-flow across that additional space.
Desktop (please complete the following information):

OS: Mac 10.16.4
Browser: Firefox 93

An example where this would allow for a table to have a better viewing experience on desktop: https://kube-vip.chipzoller.dev/docs/installation/flags/


Is possible Zooming in multiBarChart?

How do I add zoom in a multi- bar chart ?
But you can, you will add this feature in the next version ?
thanks

Need zoom option for multibar chart. Any update ?

Do you have in plan to add zoom option for multibar chart?
Thanks in advance!

The fact that they have not yet done this is destroying me.


As a Data user I want to have access to  species specific estimates of cetacean density, distribution and population trends ..so that I can use these in my work and be reassured that there is one 'official' version of this information

original id#43

Potential data product of the group.