Connection failed on android

Hi All, I'm new on GitHub.
I'd like to use traccar for tracking my smartphone SonyXperia Sola MT27i (with android 2.3.7) on Synology DS213 with DSM 4.2-3211. I have also router Buffalo WZR-HP-G300NH2 with firmware: DD-WRT v24SP2-MULTI
I'v been trying to connect android with synology for last few days but still doesn't work - connection failed on android. That's why I'd like to ask for support.
I suspect I have a problem with correct port forwarding on my router.
I will describe step by step my settings:

I have installed traccar on my synology (during installation I've selected to open all ports) and forwarded ports on buffalo:

For externall access (from work) I use public IP and port 443 which is forwarded by router to local synology address <IP_ADDRESS> and port 7777:
http://my_public_IP:443  ->forwarder by router-> <IP_ADDRESS>:7777
In this way I can open program at work.
I have forwarder also external port 55005 also to <IP_ADDRESS>:7777
http://my_public_IP:55005  ->forwarder by router-> <IP_ADDRESS>:7777

My android settings are:
Server address: http://my_public_IP   (without port, only IP number)
Server port: 443
Location provider: mixed

I have still status:
Location updated
Connection failed
I have attached picture as well.

Thanks in advance for support.
Piotr

Hi, @tananaev  Please can you clear this up below?
I have configured nginx with https proxying so the server web interface works with https from outside.
Currently in the android traccar client it has an option of Encryption Enabled,
If i enable this and put port 443 in the client, and i open port 443 in router, it never shows any error in status updates but at the same time does NOT update the server with gps location.
If i open port 5055 as well in router and put that port in the client and disable encryption then i get updates and it works.

Can you please clarify what the encryption enabled option is in the client? And when can it be used?
Is it not possible to just use ONE port, the https 443 port in the client ??
Why open 2 ports, one for web interface and one for android client? - is that mandatory to have both web interface AND android client working?

Please help clarify this issue.

@2SI3NX, it sounds like you proxied web interface port, but not OsmAnd port.

@tananaev, ok but how do you proxy OsmAnd port?  Any tutorial in the documentation on how to do that?
And after that will I be able to only need to open 443 to work for both client and web interface?

It sounds like you don't fully understand how HTTP and proxying works. I would suggest to research it first.
As for configuring proxy, I don't have any tutorial, but I'm sure there is plenty of information on this topic online.

It would be really nice if you could help by directing me to the correct link to proxy your OsmAnd port to be used as 443, as well as answering the questions in my first post about what the option of 'Encryption Enabled' does exactly in the client if you already can use port 443 as the server port in the client.
Id like to use your software by using the features you provide, such as securing a traccar server and using port 443 for OsmAnd port.  Im sure im not the only one that needs to know about securing a traccar server fully.
Your help would be appreciated

Port for web interface and port for OsmAnd protocol (Traccar Client) are two completely different things. I don't understand how you want them to work on the same port.

@tananaev  What i wanted was to use https (443) ONE SECURE CONNECTION PORT for both the Android app AND the web interface.
Trying to understand your application, it seems when i used nginx to proxy both those to port 443, i could not specify a location block to proxy specific port 8020 for web interface and 5055 for android app at the same time. such as: location /traccar/web { and location /traccar/app {  for example.
I asked the nginx professionals, and they said that a way around this is to use 2 dyndns domains that point to the same ip address to 2 different Server {} blocks.
I have configured this to proxy both ports 8020 and 5055 to 443 secure port. with the following config in nginx example.com  as below:
server {
listen 443;
server_name dyndns8082.example.com;
    root html;
    index index.html index.htm;

    ssl on;
    ssl_certificate /opt/traccar_cert/server8082.crt;
    ssl_certificate_key /opt/traccar_cert/server8082.key;
    ssl_session_timeout 5m;
    ssl_prefer_server_ciphers on;

    location / {
      proxy_redirect off;
      proxy_buffering off;
      proxy_set_header Host $host;
      proxy_set_header X-Real-IP $remote_addr;
      proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
      port_in_redirect off;
      proxy_connect_timeout 900;
      proxy_send_timeout 900;
      proxy_read_timeout 900;
      send_timeout 900;
            proxy_pass http://<IP_ADDRESS>:8082;
            proxy_http_version 1.1;
            proxy_set_header Upgrade $http_upgrade;
            proxy_set_header Connection "upgrade";
    }

}
server {
listen 443;
server_name dyndns5055.example.com;
    root html;
    index index.html index.htm;

    ssl on;
    ssl_certificate /opt/traccar_cert/server5055.crt;
    ssl_certificate_key /opt/traccar_cert/server5055.key;
    ssl_session_timeout 5m;
    ssl_prefer_server_ciphers on;

    location / {
      proxy_redirect off;
      proxy_buffering off;
      proxy_set_header Host $host;
      proxy_set_header X-Real-IP $remote_addr;
      proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
      port_in_redirect off;
      proxy_connect_timeout 900;
      proxy_send_timeout 900;
      proxy_read_timeout 900;
      send_timeout 900;
            proxy_pass http://<IP_ADDRESS>:5055;
            proxy_http_version 1.1;
            proxy_set_header Upgrade $http_upgrade;
            proxy_set_header Connection "upgrade";
    }

}
As far as i know this helps secure both communications between android traccar client AND web interface at the same time.
This is what was needed. However, it would be better to proxy in different location blocks, in other words, being able to specify through nginx to which location the traccar client app is sitting so that it can proxy_pass the correct port, instead of creating multiple dyndns domains for this purpose.
Hope you understand now. and hope this helps someone else.
This way also eliminates opening 2 unnecessary and unsafe ports in the router and only requires opening port 443 for secure communication.
Can you answer my question about what exactly the 'Encryption Enabled' option in the traccar client does?  What is the code behind it?

Now this makes much more sense. You can use virtual hosts like that, but note that not all versions of Android support it. More recent ones do.
Traccar Client always uses root path to send data. You can put the web interface in a different "location block" if you want.

@tananaev Can you answer my question about what exactly the 'Encryption Enabled' option in the traccar client does? What is the code behind it?

It changes protocol from HTTP to HTTPS. That's it.


Skill built on Composer crashes when hosted on Azure

Built a Skill from Bot Framework Composer version 1.4.0.
It runs fine while running locally on composer.
When its pushed to Azure App Service, it crashes the whole skill.
As we were performing RCA we came to 3 files, which are causing the issue.
Putting any one of these files to the App Service crashes it.
Note-Those 3 files seems to be right and are working fine locally on composer when tested on Bot Framework Emulator.
The skill was working perfectly fine until the changes in these files were pushed to App Service.
Below are the changes that we made to those 3 files -
1.

@anmolgandhi007, can you elaborate more on the current Composer version you are on along with the steps you are following to push the changes to Azure? Also, do you get any specific error on Composer(or on the Dev Console)?

Sure, currently I am using 1.4.0.
So, as we are working collaboratively with other developers. We are making use of Azure DevOps, Git for versioning of our Bot.
We are then building and releasing it on MS Azure Hosted App Service. While trying to access the Manifest of our Skill, it shows 502 Gateway error.

Closing due to inactivity.


PLEASE DO NOT APPROVE - bug bounty testing - please ignore. abdzct

PLEASE DO NOT APPROVE - bug bounty testing - please ignore. abdzct

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.


If use TTTAttributedLabel instead of UILabel, app crashed

So everything is working with UILabel attributedText. When replace it with TTTAttributedLabel, the app crashed.

so ?
Do you think your question and UITableView-FDTemplateLayoutCell have any relationship ?


Correct way to extract image features with VinVL

Hi!
How can I extract image features from my dataset with VinVL if it's not in tsv format, but in the form of a folder with image files? What's the correct way to do this?

Hi, I think we must to use the TSV file. We can generate the TSV using https://github.com/microsoft/scene_graph_benchmark/blob/main/tools/mini_tsv/tsv_demo.py .
data_path is directory to your image folder. tsv_file,label_file,hw_file,linelist_file is your output directory and name. You just need to setup the directory you want.
Just run the script up to line 56. It will produce  tsv_file,label_file,hw_file,linelist_filein your destination. But it seems that all the file it produces missing a single config.yaml. See my answer on creating the yaml file.
https://github.com/microsoft/scene_graph_benchmark/issues/6#issuecomment-819352029
After that, you can run the script test_sg_net.py for image features extraction according to the setting in readme.md.
Don't forget that dataset should point to directory that containing tsv_file,label_file,hw_file,linelist_file and rewrite the DATASETS.TEST to the yaml file.

Thanks for the comprehensive answer!

Hi, I think we must to use the TSV file. We can generate the TSV using https://github.com/microsoft/scene_graph_benchmark/blob/main/tools/mini_tsv/tsv_demo.py .
data_path is directory to your image folder. tsv_file,label_file,hw_file,linelist_file is your output directory and name. You just need to setup the directory you want.
Just run the script up to line 56. It will produce tsv_file,label_file,hw_file,linelist_filein your destination. But it seems that all the file it produces missing a single config.yaml. See my answer on creating the yaml file.
#6 (comment)
After that, you can run the script test_sg_net.py for image features extraction according to the setting in readme.md.
Don't forget that dataset should point to directory that containing tsv_file,label_file,hw_file,linelist_file and rewrite the DATASETS.TEST to point the yaml file.

hey friends, In line 37 of the tsv_demo.py file, does the code here need to change? I would be grateful！

Hi, I think we must to use the TSV file. We can generate the TSV using https://github.com/microsoft/scene_graph_benchmark/blob/main/tools/mini_tsv/tsv_demo.py .
data_path is directory to your image folder. tsv_file,label_file,hw_file,linelist_file is your output directory and name. You just need to setup the directory you want.
Just run the script up to line 56. It will produce tsv_file,label_file,hw_file,linelist_filein your destination. But it seems that all the file it produces missing a single config.yaml. See my answer on creating the yaml file.
#6 (comment)
After that, you can run the script test_sg_net.py for image features extraction according to the setting in readme.md.
Don't forget that dataset should point to directory that containing tsv_file,label_file,hw_file,linelist_file and rewrite the DATASETS.TEST to point the yaml file.

hi  I want to get some suggestions about the more object label circumstance. I found the project provides us the labelmap file. But the labelmap only provide 50 objects. It is so smaller. I run the coco2014 , the object label 1370 is far bigger than it . So We should only add some id and name to the labelmap.file  or we should from scratch to train the object detector of the project ? I have the coco 2014 36 box's label. But I don't know how to get bigger object label labelmap file
If you have way, please help me . Thanks

https://github.com/microsoft/scene_graph_benchmark/issues/7#issuecomment-819357369
Dear scholar, do you realise the function which can produce features with your pointed boudingbox, not the proposal from model?

Hi, I think we must to use the TSV file. We can generate the TSV using https://github.com/microsoft/scene_graph_benchmark/blob/main/tools/mini_tsv/tsv_demo.py .
data_path is directory to your image folder. tsv_file,label_file,hw_file,linelist_file is your output directory and name. You just need to setup the directory you want.
Just run the script up to line 56. It will produce tsv_file,label_file,hw_file,linelist_filein your destination. But it seems that all the file it produces missing a single config.yaml. See my answer on creating the yaml file.
#6 (comment)

@vinson2233
Hi there, thanks for your response, as of now I have been able to create the tsv and yaml files. But I would like to have a little bit more of help on the last paragraph, since it is not quite clear how to point to the yaml file and hoy to make dataset to point to the directory containing the other files.

After that, you can run the script test_sg_net.py for image features extraction according to the setting in readme.md.
Don't forget that dataset should point to directory that containing tsv_file,label_file,hw_file,linelist_file and rewrite the DATASETS.TEST to point the yaml file.

Thank you very much in advance.

Hi, I found a way to circumvent using tsv files by modifying scene_graph_benchmark/tools/demo/demo_image.py, and now I only need jpg image dataset, VinVl yaml configuration file and model weight file.  The predictions are saved in dictionary and are stored in pth format. I ran it on Google Colab and it generates predictions at a rate about 2s/image. I hope this helps.
# pretrained models at https://penzhanwu2.blob.core.windows.net/sgg/sgg_benchmark/vinvl_model_zoo/vinvl_vg_x152c4.pth
# the associated labelmap at https://penzhanwu2.blob.core.windows.net/sgg/sgg_benchmark/vinvl_model_zoo/VG-SGG-dicts-vgoi6-clipped.json

import cv2
import os
import os.path as op
import argparse
import json
from PIL import Image

from scene_graph_benchmark.scene_parser import SceneParser
from scene_graph_benchmark.AttrRCNN import AttrRCNN
from maskrcnn_benchmark.data.transforms import build_transforms
from maskrcnn_benchmark.utils.checkpoint import DetectronCheckpointer
from maskrcnn_benchmark.config import cfg
from scene_graph_benchmark.config import sg_cfg
from maskrcnn_benchmark.data.datasets.utils.load_files import \
    config_dataset_file
from maskrcnn_benchmark.data.datasets.utils.load_files import load_labelmap_file
from maskrcnn_benchmark.utils.miscellaneous import mkdir

def cv2Img_to_Image(input_img):
    cv2_img = input_img.copy()
    img = cv2.cvtColor(cv2_img, cv2.COLOR_BGR2RGB)
    img = Image.fromarray(img)
    return img

def detect_objects_on_single_image(model, transforms, cv2_img):
    # cv2_img is the original input, so we can get the height and
    # width information to scale the output boxes.
    img_input = cv2Img_to_Image(cv2_img)
    img_input, _ = transforms(img_input, target=None)
    img_input = img_input.to(model.device)

    with torch.no_grad():
        prediction = model(img_input)[0].to('cpu')
    #     prediction = prediction[0].to(torch.device("cpu"))

    img_height = cv2_img.shape[0]
    img_width = cv2_img.shape[1]

    prediction = prediction.resize((img_width, img_height))

    return prediction

#Setting configuration
cfg.set_new_allowed(True)
cfg.merge_from_other_cfg(sg_cfg)
cfg.set_new_allowed(False)
#Configuring VinVl
cfg.merge_from_file('/scene_graph_benchmark/sgg_configs/vgattr/vinvl_x152c4.yaml')

#This is a list specifying the values for additional arguments, it encompasses pairs of list and values in an ordered manner
#MODEL.WEIGHT specifies the full path of the VinVl weight pth file
#DATA_DIR specifies the directory that contains VinVl input tsv configuration yaml file
argument_list = [
                 'MODEL.WEIGHT', 'vinvl_vg_x152c4.pth',
                 'MODEL.ROI_HEADS.NMS_FILTER', 1,
                 'MODEL.ROI_HEADS.SCORE_THRESH', 0.2,
                 'TEST.IGNORE_BOX_REGRESSION', False,
                 'MODEL.ATTRIBUTE_ON', True
                 ]
cfg.merge_from_list(argument_list)
cfg.freeze()

#     assert op.isfile(args.img_file), \
#         "Image: {} does not exist".format(args.img_file)

output_dir = cfg.OUTPUT_DIR
#     mkdir(output_dir)

model = AttrRCNN(cfg)
model.to(cfg.MODEL.DEVICE)
model.eval()

checkpointer = DetectronCheckpointer(cfg, model, save_dir=output_dir)
checkpointer.load(cfg.MODEL.WEIGHT)

transforms = build_transforms(cfg, is_train=False)

input_img_directory = 'insert your images directory path here'
#need to be pth
output_prediction_file = 'insert your output pth file path here'
dets = {}
for img_name in os.listdir(input_img_directory):
  #Convert png format to jpg format
  if img_name.split('.')[1]=='png' or img_name.split('.')[1]=='PNG':
    im = Image.open(os.path.join(input_img_directory, img_name))
    rgb_im = im.convert('RGB')
    new_name = img_name.split('.')[0]+'.jpg'
    rgb_im.save(os.path.join(input_img_directory, new_name))
    print(new_name)

  img_file_path = os.path.join(input_img_directory,img_name.split('.')[0]+'.jpg')
  print(img_file_path)

  cv2_img = cv2.imread(img_file_path)

  det = detect_objects_on_single_image(model, transforms, cv2_img)

#   prediction contains ['labels',
#  'scores',
#  'box_features',
#  'scores_all',
#  'boxes_all',
#  'attr_labels',
#  'attr_scores']
# box_features are used for oscar

  det_dict ={key : det1[0].get_field(key) for key in det1[0].fields()}

  dets[img_name.split('.')[0]] = det_dict

torch.save(dets, output_prediction_file)

Hi @SPQRXVIII001, I don't understand how you can extract the box features from the demo_image.py file without using the TSV files. I tried to run your code with some modifications because there are some errors and when I print the list of fields extracted by prediction there is not the field you call 'box_features'; in fact running print("fields:", prediction.fields()) there are only the fields:  ['labels', 'scores', 'attr_labels', 'attr_scores'].

Hi, @GabrieleFerrario, I think TSV files are unncessary. You need to modify your configuration yaml files at scene_graph_benchmark/sgg_configs/vgattr/vinvl_x152c4.yaml to add new field. I think you need to set the TEST entry to  as follows:
TEST:     IMS_PER_BATCH: 1     OUTPUT_FEATURE: True     OUTPUT_RELATION_FEATURE: True     SKIP_PERFORMANCE_EVAL: True     SAVE_PREDICTIONS: True     SAVE_RESULTS_TO_TSV: True     TSV_SAVE_SUBSET: ['rect', 'class', 'conf', 'feature', 'relation_feature ']     GATHER_ON_CPU: True

@GabrieleFerrario, you may also look at  https://github.com/microsoft/scene_graph_benchmark/issues/8#issue-857781982 for some ideas.

Hi, I think we must to use the TSV file. We can generate the TSV using https://github.com/microsoft/scene_graph_benchmark/blob/main/tools/mini_tsv/tsv_demo.py . data_path is directory to your image folder. tsv_file,label_file,hw_file,linelist_file is your output directory and name. You just need to setup the directory you want.
Just run the script up to line 56. It will produce tsv_file,label_file,hw_file,linelist_filein your destination. But it seems that all the file it produces missing a single config.yaml. See my answer on creating the yaml file. #6 (comment)
After that, you can run the script test_sg_net.py for image features extraction according to the setting in readme.md. Don't forget that dataset should point to directory that containing tsv_file,label_file,hw_file,linelist_file and rewrite the DATASETS.TEST to point the yaml file.

How can I get the label_file? My dataset doesn't have a list of dictionary  where each box with at least "rect" (xyxy mode) and "class" fields. Thank you very much!
This is marked in the original code：Here is just a toy example of labels. The real labels can be generated from the annotation files given by each dataset. The label is a list of dictionary  where each box with at least "rect" (xyxy mode) and "class" fields. It can have any other fields given by the dataset.

Hi, I found a way to circumvent using tsv files by modifying scene_graph_benchmark/tools/demo/demo_image.py, and now I only need jpg image dataset, VinVl yaml configuration file and model weight file. The predictions are saved in dictionary and are stored in pth format. I ran it on Google Colab and it generates predictions at a rate about 2s/image. I hope this helps.
# pretrained models at https://penzhanwu2.blob.core.windows.net/sgg/sgg_benchmark/vinvl_model_zoo/vinvl_vg_x152c4.pth
# the associated labelmap at https://penzhanwu2.blob.core.windows.net/sgg/sgg_benchmark/vinvl_model_zoo/VG-SGG-dicts-vgoi6-clipped.json

import cv2
import os
import os.path as op
import argparse
import json
from PIL import Image

from scene_graph_benchmark.scene_parser import SceneParser
from scene_graph_benchmark.AttrRCNN import AttrRCNN
from maskrcnn_benchmark.data.transforms import build_transforms
from maskrcnn_benchmark.utils.checkpoint import DetectronCheckpointer
from maskrcnn_benchmark.config import cfg
from scene_graph_benchmark.config import sg_cfg
from maskrcnn_benchmark.data.datasets.utils.load_files import \
    config_dataset_file
from maskrcnn_benchmark.data.datasets.utils.load_files import load_labelmap_file
from maskrcnn_benchmark.utils.miscellaneous import mkdir

def cv2Img_to_Image(input_img):
    cv2_img = input_img.copy()
    img = cv2.cvtColor(cv2_img, cv2.COLOR_BGR2RGB)
    img = Image.fromarray(img)
    return img

def detect_objects_on_single_image(model, transforms, cv2_img):
    # cv2_img is the original input, so we can get the height and
    # width information to scale the output boxes.
    img_input = cv2Img_to_Image(cv2_img)
    img_input, _ = transforms(img_input, target=None)
    img_input = img_input.to(model.device)

    with torch.no_grad():
        prediction = model(img_input)[0].to('cpu')
    #     prediction = prediction[0].to(torch.device("cpu"))

    img_height = cv2_img.shape[0]
    img_width = cv2_img.shape[1]

    prediction = prediction.resize((img_width, img_height))

    return prediction

#Setting configuration
cfg.set_new_allowed(True)
cfg.merge_from_other_cfg(sg_cfg)
cfg.set_new_allowed(False)
#Configuring VinVl
cfg.merge_from_file('/scene_graph_benchmark/sgg_configs/vgattr/vinvl_x152c4.yaml')

#This is a list specifying the values for additional arguments, it encompasses pairs of list and values in an ordered manner
#MODEL.WEIGHT specifies the full path of the VinVl weight pth file
#DATA_DIR specifies the directory that contains VinVl input tsv configuration yaml file
argument_list = [
                 'MODEL.WEIGHT', 'vinvl_vg_x152c4.pth',
                 'MODEL.ROI_HEADS.NMS_FILTER', 1,
                 'MODEL.ROI_HEADS.SCORE_THRESH', 0.2,
                 'TEST.IGNORE_BOX_REGRESSION', False,
                 'MODEL.ATTRIBUTE_ON', True
                 ]
cfg.merge_from_list(argument_list)
cfg.freeze()

#     assert op.isfile(args.img_file), \
#         "Image: {} does not exist".format(args.img_file)

output_dir = cfg.OUTPUT_DIR
#     mkdir(output_dir)

model = AttrRCNN(cfg)
model.to(cfg.MODEL.DEVICE)
model.eval()

checkpointer = DetectronCheckpointer(cfg, model, save_dir=output_dir)
checkpointer.load(cfg.MODEL.WEIGHT)

transforms = build_transforms(cfg, is_train=False)

input_img_directory = 'insert your images directory path here'
#need to be pth
output_prediction_file = 'insert your output pth file path here'
dets = {}
for img_name in os.listdir(input_img_directory):
  #Convert png format to jpg format
  if img_name.split('.')[1]=='png' or img_name.split('.')[1]=='PNG':
    im = Image.open(os.path.join(input_img_directory, img_name))
    rgb_im = im.convert('RGB')
    new_name = img_name.split('.')[0]+'.jpg'
    rgb_im.save(os.path.join(input_img_directory, new_name))
    print(new_name)

  img_file_path = os.path.join(input_img_directory,img_name.split('.')[0]+'.jpg')
  print(img_file_path)

  cv2_img = cv2.imread(img_file_path)

  det = detect_objects_on_single_image(model, transforms, cv2_img)

#   prediction contains ['labels',
#  'scores',
#  'box_features',
#  'scores_all',
#  'boxes_all',
#  'attr_labels',
#  'attr_scores']
# box_features are used for oscar

  det_dict ={key : det1[0].get_field(key) for key in det1[0].fields()}

  dets[img_name.split('.')[0]] = det_dict

torch.save(dets, output_prediction_file)

Hello,

Hi @SPQRXVIII001, I don't understand how you can extract the box features from the demo_image.py file without using the TSV files. I tried to run your code with some modifications because there are some errors and when I print the list of fields extracted by prediction there is not the field you call 'box_features'; in fact running print("fields:", prediction.fields()) there are only the fields: ['labels', 'scores', 'attr_labels', 'attr_scores'].

Hi,
I am having some errors. I change det1 to det. Still I got
"bbox should have 2 dimensions, got {}".format(bbox.ndimension())
ValueError: bbox should have 2 dimensions, got 1

Could you please share your updated code.
Thanks,
Abhidip


Bandit errors out when summing issues

A bug was introduced in a refactor that causes bandit to fail summing results after processing.

Issue: subprocess call - check for execution of untrusted input.
Severity: Low   Confidence: High
Location: /Users/travismcpeak/Documents/projects/OpenStack_projects/keystone/tools/install_venv_common.py:64
63
64              proc = subprocess.Popen(cmd, cwd=self.root, stdout=stdout)
65              output = proc.communicate()[0]

Traceback (most recent call last):
File "/usr/local/bin/bandit", line 10, in
sys.exit(main())
File "/usr/local/lib/python2.7/site-packages/bandit/bandit.py", line 243, in main
conf_filter=args.confidence - 1) > 0:
File "/usr/local/lib/python2.7/site-packages/bandit/core/manager.py", line 95, in results_count
return sum(i.filter(sev_filter, conf_filter) for i in self.results)
File "/usr/local/lib/python2.7/site-packages/bandit/core/manager.py", line 95, in
return sum(i.filter(sev_filter, conf_filter) for i in self.results)
File "/usr/local/lib/python2.7/site-packages/bandit/core/issue.py", line 50, in filter
return (rank.index(self.severity) >= rank.index(severity) and
ValueError: 0 is not in list

Launchpad bug to Github issue import error


Hierarchical graph datasets?  Graph of graphs.

Thanks for your hard work on Geometric!
I'm interested in how we could implement a model where the data is a graph of graphs.
Perhaps something like Fig 3. in this paper:
https://arxiv.org/abs/1904.05003
I currently have an InMemoryDataset, subG, of, say, 100 graphs that have the same number of features, but differing number of nodes.  I consider each of these "sub-graphs" to be a node in the "master graph", G.  I imagine that G could also be Data object.
I would like to do some operations to each graph in subG, pool, and use this output as the feature for that corresponding node in G.
Can I initialize G at the beginning of training and then update its x and edge_index at each step?  Perhaps I'm missing something simple?

As far as I understand, you need to create an assignment vector in Data which maps each node to its respective subgraph. Then you can perform message passing in each subgraph in parallel, and global pool each subgraph afterwards.


CLI testing: Support module and e2e tests

This modifies the directory structure to support two types of tests that share common utility code. There are no logic changes.

e2e tests are executed on pre-compiled binaries. They validate that modules are combined correctly, and that common scenarios work as expected.
module tests exercise a single module, typically with live dependencies. They are typically faster than e2e tests, allowing for increased coverage at a lower cost.

Directory layoout
Previous
cli_tools_e2e_test
├── common
│   ├── assert
│   ├── compute
│   ├── logging
│   ├── storage
│   └── utils
├── diskinspect
│   ├── disk_inspect_test.go
│   ├── go.mod
│   ├── go.sum
│   └── README.md
├── gce_image_import_export
│   ├── main.go
│   └── test_suites
├── gce_ovf_import
│   ├── main.go
│   ├── scripts
│   └── test_suites
├── gce_windows_upgrade
│   ├── main.go
│   └── test_suites
├── go.mod
└── go.sum

This PR:
cli_tools_tests
├── e2e
│   ├── assert.go
│   ├── gce_image_import_export
│   ├── gce_ovf_import
│   ├── gce_windows_upgrade
│   └── utils.go
├── go.mod
├── go.sum
└── module
    ├── diskinspect
    └── README.md
common
├── gcp
│   ├── image.go
│   ├── instance.go
│   └── storage.go
├── go.mod
├── go.sum
├── logging
│   └── logging.go
└── runtime
    └── config.go

Testing

Presubmits updated to reflect new directory structure: https://github.com/GoogleCloudPlatform/oss-test-infra/pull/524
Built prowjobs_cloudbuild.yaml: https://pantheon.corp.google.com/cloud-build/builds/49e6f867-ba7a-4a0b-9758-c4332d1c11ff?project=edens-test
Executed tests using the three test binaries (image import/export, OVF, and windows upgrade)

Would you summarize the impl of this change?

package renaming?
new directory & file moved?
other actual code change?

It's hard to find where are #3 located (which needs to be reviewed) since there are too many #1 and #2 files.
The correctness of #1 and #2 should be guaranteed by compiler.

Hey @dntczdx

package renaming?
new directory & file moved?

cli_tools_e2e_test is split into two packages cli_tools_test and common.

cli_tools_test has a directory for e2e tests, and a directory for module tests. In addition to tests, there are two files that contain utility code that's only used by the e2e tests.
common includes code from cli_tools_e2e_test that could be used elsewhere. Eventually cli_tools/common should get consolidated here as well.

other actual code change?

There are no logic changes; all changes are related to moving, renaming, or package changes.

common includes code from cli_tools_e2e_test that could be used elsewhere. Eventually cli_tools/common should get consolidated here as well.

I believe these files (image.go, instance.go, storage/file.go, etc) will only be used by test code, since they are just a very simple wrapper of api lib, in order to call google API without injecting a existing compute/storage client. Also, it used "replace ...daisy" so it shouldn't be a dev module


Document how to reset the parser after using feed

const parser = new Parser(commandGrammar.ParserRules, commandGrammar.ParserStart);

const results = parser.feed(command).results;

How to reset the parser after feeding it some data?

The easiest way is to just make a new parser.

Now the most efficient way, though.
It would be nice to have a simple "reset" function.

Now the most efficient way, though.

It's actually very cheap.


Put perl modules in their own namespace.

So, this is the second attempt to put modules in their own namespace.  This patch includes the appropriate changes in illumina_pipeline.pl that were missing in the previous version of this patch.
I performed a test hitting IAP::prestats::runPreStats, which works fine.  So I believe this change will work for the other modules too.
Thanks!

Hi Roel, thanks for the PR. I have merged it with a feature branch coming from develop. This makes testing a bit easier. I'll will merge it with develop after I have done some tests.

Thanks! If there are any problems, let me know.


Upgrade to golang 1.19, k8s 1.24.6

Signed-off-by: David Tesar<EMAIL_ADDRESS>Description
Move to latest version of golang and 1.24.6 version for e2e K8s testing.
Type of change

[ ] New feature (non-breaking change which adds functionality)

How Has This Been Tested?
CI/CD tests pass
Checklist:
N/A

seems to be waiting for the old k8 version of e2e test to run. Not sure why this is the case @dtzar

@akashsinghal - I can fix this.  It's because GitHub policy is looking for a YAML file with that name, but that file no longer exists because it is updated in this PR.  You can see that one passes.  If you approve the PR, then I'll fix that to use the new one here.

@dtzar I see that makes sense. I think you'll have to manually merge this into main


EResult.LookbehindOverrun and EResult.InputOverrun

I wanted to bump ubi_reader to v0.8.8 for a project, but I'm getting errors for all of my UBIFS test files, which make it impossible to extract files from the image. If I change ubi_reader to use python-lzo instead, no errors. This is with ubi_reader v0.8.8 and lzallright v0.2.2. Here's a test file. Just run ubireader_extract_files 07_app.bin. I'm obviously not gonna post the 139 images but my guess is that this is the same error(s) for all of them so hopefully one is enough.

It could be an implementation quirk that lzokay doesn't support reading the uncompressed length at the begining of the buffer.
Can you test, if this works for you?
diff --git a/ubireader/ubifs/misc.py b/ubireader/ubifs/misc.py
index 0368369..3cbfa31 100755
--- a/ubireader/ubifs/misc.py
+++ b/ubireader/ubifs/misc.py
@@ -62,7 +62,7 @@ def decompress(ctype, unc_len, data):
     """
     if ctype == UBIFS_COMPR_LZO:
         try:
-            return lzo.decompress(b''.join((b'\xf0', struct.pack('>I', unc_len), data)))
+            return lzo.decompress(data, output_size_hint=unc_len)
         except Exception as e:
             error(decompress, 'Warn', 'LZO Error: %s' % e)
     elif ctype == UBIFS_COMPR_ZLIB:

That worked, with and without the size hint. I also checked that all calls give the same result as lzo.decompress(data, False, unc_len) from python-lzo. I should have thought about trying this first before opening the issue.

I'm looking at the same issue. Is there a PR for resolving this?

I'm looking at the same issue. Is there a PR for resolving this?

Opened https://github.com/onekey-sec/ubi_reader/pull/86

Fixed in ubi_reader 0.8.9


new package: ui5-antares

@marianfoo Hi, could you please review the pull request and merge?

Sorry it took so long. Thank you!


Building haskell doesn't work with docker-compose

Building haskell-x509
Step 1 : FROM ouspg/libfuzzer-base-haskell
Pulling repository docker.io/ouspg/libfuzzer-base-haskell
ERROR: Service 'haskell-x509' failed to build: Error: image ouspg/libfuzzer-base-haskell not found

Image repo for libfuzzer-base-haskell did not exist.
Created autobuild for the image.


How does it compare to MiMalloc?

https://github.com/microsoft/mimalloc

Thanks for your reply, the mimalloc should be more stable and generalised. For performance, I'll do some benchmark later on.


fix(core): fix printf causing ub due to a non null terminated str

fix printf causing ub due to a non null terminated str, it printed random stuff after the value. I also switched %d to %ld as it is the correct format specifier for long ints.
It also adds the dev dependency pretty_assertions, i believe it is really helpful to see the difference in the generated llvm ir on tests.

Pull Request type
Please check the type of change your PR introduces:

[x] Bugfix
[ ] Feature
[ ] Code style update (formatting, renaming)
[ ] Refactoring (no functional changes, no API changes)
[ ] Build-related changes
[ ] Documentation content changes
[ ] Testing
[ ] Other (please describe):

What is the current behavior?
UB due to malformed printf call
Issue Number: N/A
What is the new behavior?
Correct printf call.
Does this introduce a breaking change?

[ ] Yes
[x] No

The bc file seem to be different depending on the cpu architecture (that's why it's removed from the tests)


Add missing error message to the syntax_diagnostic_message.properties

Purpose
$subject.
Fixes #27502
Approach
N/A
Samples
N/A
Remarks
N/A
Check List

[x] Read the Contributing Guide
[ ] Updated Change Log
[ ] Checked Tooling Support (#)
[ ] Added necessary tests

[ ] Unit Tests
[ ] Spec Conformance Tests
[ ] Integration Tests
[ ] Ballerina By Example Tests

[ ] Increased Test Coverage
[ ] Added necessary documentation

[ ] API documentation
[ ] Module documentation in Module.md files
[ ] Ballerina By Examples

Shall we add a negative test for this scenario?

Shall we add a negative test for this scenario?

Closing this PR as changes are addressed in PR #27516.

Shall we add a negative test for this scenario?

A negative test has been added there.

Closing this PR as changes are addressed in PR #27516.

Shall we add a negative test for this scenario?

A negative test has been added there.


Build proto using dotnet cli

When building coreclr use dotnet cli as the lkg.
update dotnet cli to the latest preview.
(for now there will be two until we can move off of project.json)

@dotnet-bot test Windows_NT Release_ci_part1 Build please


Moved AppLifecycle samples out of Quarantine

Looks like there is a merge conflict. Think you'll have to pull from main first.

/azp run

/azp run

/azp run

/azp run


Setting up the new landing page

Remaining:

live updating of project table
add full graph list based on the MANIFEST
include validation details

Going to push this for now just to ensure it's visible - further edits will go in a new PR


Errors when running samples

Hi,
I've followed the "getting started" guide to the letter, but keep getting the following critical errors when the build script gets to the native image generation:
Warning: class initialization of class org.springframework.boot.validation.MessageInterpolatorFactory failed with exception java.lang.NoClassDefFoundError: javax/validation/ValidationException. This class will be initialized at run time because option --allow-incomplete-classpath is used for image building. Use the option --initialize-at-run-time=org.springframework.boot.validation.MessageInterpolatorFactory to explicitly request delayed initialization of this class.
Number of types dynamically registered for reflective access: #839
[commandlinerunner:329806]     analysis:  10,379.69 ms,  1.69 GB
Error: Classes that should be initialized at run time got initialized during image building:
org.springframework.util.ConcurrentReferenceHashMap$ReferenceManager was unintentionally initialized at build time. To see why org.springframework.util.ConcurrentReferenceHashMap$ReferenceManager got initialized use -H:+TraceClassInitialization
........................................................................................... (additional Spring classes initialized at build time)
Any ideas?

My guess is that you are using GraalVM native 20.0.0 not 20.1-dev, see instructions on https://github.com/spring-projects-experimental/spring-graal-native#baseline for building samples against master using GraalVM dev builds or containers.


fix dev building

@stephenandrews does this fix npm start for you? I was able to repro npm start hanging and this fixes it for me while keeping the production build healthy.

Prevent chunking in dev mode.
Don't polyfill Node.js crypto module for frontend. We never import it (same as the stream module which also is ignored in the config override.)

Note that production builds didn't complain about it missing so this is fine. No need to increase bundle size.

Ignore missing source maps from node_modules since we can't do much about that.

stale


Fix squeeze state machine and squeeze indicator coloring

Fixes squeeze state-machine for first/last
Consider equality for first and last character of a line.
If the first or last character of a line is not equal to previous character,
the state machine should be set back to probe as the line should not be
squeezed.
The unit tests has been expanded for testing the use case described in #62.
Further the body of all unit tests has been simplified.
Fixes #62

Consider color when printing squeeze indicator
When color option has been set to never, the squeeze indicator
character asterisk '*' should not be printed in color.
Fixes #63

Thank you so much!


terminated call error when run /libtorch-yolov5

i sure  "model.model[-1].export = False" in export.py

i sure  "model.model[-1].export = False" in export.py

Can you help? @yasenh
Which yolov5 release did you use? https://github.com/ultralytics/yolov5/releases

Can you help? @yasenh
Which yolov5 release did you use? https://github.com/ultralytics/yolov5/releases

I tested it on v3.0 and v3.1 @alikarimi120 , are you using v4.0? And which version of libtorch are you using?

I tested it on v3.0 and v3.1 @alikarimi120 , are you using v4.0? And which version of libtorch are you using?

libortch :
https://download.pytorch.org/libtorch/cu102/libtorch-cxx11-abi-shared-with-deps-1.6.0.zip
i tested it on v2.0 , v3.1 and v4 but I get this error (picture above)

libortch :
https://download.pytorch.org/libtorch/cu102/libtorch-cxx11-abi-shared-with-deps-1.6.0.zip
i tested it on v2.0 , v3.1 and v4 but I get this error (picture above)

Can you send me a yolov5s.torchscript.pt? of course, I think the problem is with the pytorch version, not the model conversion؟
@yasenh

Can you send me a yolov5s.torchscript.pt? of course, I think the problem is with the pytorch version, not the model conversion؟
@yasenh

I tested it on v3.0 and v3.1 @alikarimi120 , are you using v4.0? And which version of libtorch are you using?

libortch :
https://download.pytorch.org/libtorch/cu102/libtorch-cxx11-abi-shared-with-deps-1.6.0.zip
i tested it on v2.0 , v3.1 and v4 but I get this error (picture above)

I tested it on v3.0 and v3.1 @alikarimi120 , are you using v4.0? And which version of libtorch are you using?

libortch :
https://download.pytorch.org/libtorch/cu102/libtorch-cxx11-abi-shared-with-deps-1.6.0.zip
i tested it on v2.0 , v3.1 and v4 but I get this error (picture above)

Can you send me a yolov5s.torchscript.pt? of course, I think the problem is with the pytorch version, not the model conversion?
@yasenh

Can you send me a yolov5s.torchscript.pt? of course, I think the problem is with the pytorch version, not the model conversion?
@yasenh

I've tried nigthly version of libtorch and error dissapear
command:
wget https://download.pytorch.org/libtorch/nightly/cu101/libtorch-cxx11-abi-shared-with-deps-latest.zip
look it :
https://github.com/pytorch/pytorch/issues/17054

I've tried nigthly version of libtorch and error dissapear
command:
wget https://download.pytorch.org/libtorch/nightly/cu101/libtorch-cxx11-abi-shared-with-deps-latest.zip
look it :
https://github.com/pytorch/pytorch/issues/17054

libtorch >= 1.6.0 should work

libtorch >= 1.6.0 should work


Improve axis range and ticmark handling

I've noticed that the handling of the y axis range and the choice of tic marks are often a bit strange. For example:

For linear axes the "pretty values" are often not all that pretty. I don't think a human would usually choose tic marks like [0, 12.5, 25, 37.5, ...]; one would use [0, 10, 20, 30, ...]. And surely nobody would choose [0, 22.5, 45, 67.5, 90, ...] when [0, 20, 40, 60, 80, ...] is so close by.

The handling of yMax="max" is totally broken.

There are several places where rounding errors could cause labels to be omitted.

Logarithmic tic marks are totally broken, too.

So I've completely rewritten the axis-handling code while retaining backwards compatibility of the parameters. The new code restricts the mantissas of tic mark steps to be [..., 0.1, 0.2, 0.5, 1, 2, 5, 10, ...], which (in my opinion) is adequate to give really convenient tic marks without wasting too much space on the edges of the graph. I've rewritten the algorithm for optimizing (step, divisor) for the tic marks from scratch (documented in the docstring for _LinearAxisTics.chooseStep(). I've eliminated some places where rounding errors could cause problems. And I have fixed the logarithmic tic marks.
I've tested the new _AxisTics classes in isolation to some degree and they seem to work. But I haven't tested them together with the LineGraph class because I don't have a test setup. (I think the design is sound but there are surely typos and other minor problems.) If somebody could help me figure out some idiot-proof steps and the bare minimum configuration to run tests locally without becoming a django expert or figuring out how to feed data into the system, that would be really helpful.

WOW. Didn't check patch yet, just want to say that is look MASSIVE! Much appreciated!
Not sure if I can help with testing... My testing skills are weak. :(

I forgot to mention one thing I'm unsure about..._LogAxisTics sets self.step to None because that parameter is ignored and unneeded. That value later gets copied to LineGraph.yStep, which eventually can get incorporated into the output of Graph.output here. Does anybody know whether None is permissible there, or whether we maybe have to record some sensible fake value as the step for logarithmic axes, or whether maybe Graph.output should get smarter about omitting that key/value pair altogether?

I just pushed some more commits that have to do with how the data range and user options are combined, especially in the case that they are inconsistent with each other. This fixes a bug that sometimes the "rounding up" behavior for maxValue sometimes made it exceed axisLimit.

I've done quite a bit of manual testing of the AxisTics classes in isolation, fixed some edge cases, and added more input validation. I think these classes are pretty solid now.
I still haven't done any integration testing because I'm not set up for it. So this still could be terribly broken, though hopefully only in trivial ways (plus possibly the point mentioned above).
I'm going to stop pushing now to give people a chance to look over the changes.

I have noticed that the Y-Axis has an alignment issue between the 0 and other listed values:

@cbowman0, thanks for the testing and the feedback.
I suspect it comes down to a one-character difference that I noticed between two versions of makeLabel in the code before my changes: here vs. here. The discrepancy originated in 53bfcd04389054b439503be21ae6eea9d11fee25. I took it to be a mistake in that commit that the two functions were not adjusted in the same way. I added a space to one version of the function in e1dde2d7815d9ff82c594654a645c04c16585f33 because it looked like the space was forgotten from that version. After that the two versions of the function were identical, so I unified them.
It's easy to take that space back out here, and I expect that would fix your problem. What I'm not sure of is whether the other version of makeLabel really needed the space. @nleskiw, you wrote 53bfcd04389054b439503be21ae6eea9d11fee25; can you shed some light on the situation?

I tried to boil down the differences in label layout before/after this change.
No patch:

With patch:

Existing has some inconsistencies:

In graph a between <1 and >=1 values.
In graph b when the label has a prefix and when it doesn't.
In graph d, the prefix has no spacing after the prefix.

I think there's an opportunity to normalize the spacing between the label and the graph.
With these changes to your makeLabel:
--- glyph.py	2016-05-12 14:29:26.415428819 +0000
+++ glyph.py.bak	2016-05-12 14:28:22.361647434 +0000
@@ -226,19 +226,17 @@
   def makeLabel(self, value):
     value, prefix = format_units(value, self.step, system=self.unitSystem)
     span, spanPrefix = format_units(self.span, self.step, system=self.unitSystem)
-    if (prefix != ''):
-      prefix = "%s " % prefix
     if value < 0.1:
       return "%g %s" % (float(value), prefix)
     elif value < 1.0:
       return "%.2f %s" % (float(value), prefix)
     if span > 10 or spanPrefix != prefix:
       if type(value) is float:
-        return "%.1f %s" % (value, prefix)
+        return "%.1f %s " % (value, prefix)
       else:
-        return "%d %s" % (int(value), prefix)
+        return "%d %s " % (int(value), prefix)
     elif span > 3:
-      return "%.1f %s" % (float(value), prefix)
+      return "%.1f %s " % (float(value), prefix)
     elif span > 0.1:
       return "%.2f %s " % (float(value), prefix)
     else:

The labels now look like:

@cbowman0: thanks for the testing! (I don't have a graphite-web setup that I can use for testing, so I've been testing the input/output as text.)
Regarding graph (a): I take it that the inputs are all exactly zero? If so, I personally don't see a strong reason to prefer [-1..1] or [0..1]. If the latter is preferred, let me know and I will implement it (the place is _AxisTics.reconcileLimits() here).
Regarding graph (b): there is also an aesthetic difference in the choice of axis labels. I personally think that the new version looks better.
Regarding graph (c): here, to me, the new choice of y axis endpoints and tic marks is clearly better than the old. In fact it was examples like this that led me to start work on this PR.
Thanks for your proposed change to makeLabel. I'd be happy to make this change in my name or to pull the change from your fork, whichever you prefer.
However, taking a step back, I have to question why makeLabel has to add whitespace at the right side of label strings in the first place. Wouldn't it make more sense for the labels to be generated without padding, and for the rendering part of the code to position the labels more intelligently? And when there is no unit string, surely the extra space (which would otherwise separate the number from the label) should be omitted, too? I don't know that part of the code, though, so take this suggestion with a grain of salt.
If it were up to me, I would also omit the .0 on label values when none of the labels' numbers have fractional parts. For example, instead of
"0", "5.0 k", "10.0 k", "15.0 k"

, why not
"0", "5 k", "10 k", "15 k"

? I'd be happy to implement that, too (though preferably as part of a separate PR).
Thanks again for the feedback, and let me know how you would like to proceed.

@mhagger @cbowman0 invited you both to the organization, really appreciate all the effort you've been putting into this. 🍰

Thanks @obfuscurity .
Can you weigh in on @mhagger most recent questions about presentation?

I don't have any feedback on the code itself right now. The glyph stuff is so hairy it'll take me a bit of time to ramp up on it again. Or did you just mean afa aesthetic preferences?

I was asking about the aesthetics preferences on the graph images.

Frankly they're all improvements as far as I'm concerned. The rendering stuff is hard to get perfect for all scenarios but I think this is generally better than where we started. Specifically wrt "should we present floats or integers" I think the current behavior is ok. I would typically argue in favor of consistency ("either all floats or none at all") but here we're using K units where I think it makes sense to be show some significant digits.
Does that address everything? 😛

I think that changing where padding is implemented and whether to omit trailing zeros from label values should be addressed in separate PRs.
I just pushed a commit that should fix the spacing problem pointed out by @cbowman0, using more or less his suggested change.
If there's anything else that people would like to see changed in this PR, please let me know. Otherwise, as far as I know, I've addressed all points that have been brought up.

Thanks for all your work on this @mhagger it's greatly appreciated. 🍰 ❤ 🔥 🍦


ENH: Non-Legacy Piecewise Linear Interpolation

Is your feature request related to a problem? Please describe.
The interp1d docs state:

This class is considered legacy and will no longer receive updates. This could also mean it will be removed in future SciPy versions. For a guide to the intended replacements for interp1d see 1-D interpolation.

However, the 1D interpolation docs then just point to numpy.interp for piecewise linear interpolation:

If all you need is a linear (a.k.a. broken line) interpolation, you can use the numpy.interp routine. It takes two arrays of data to interpolate, x, and y, and a third array, xnew, of points to evaluate the interpolation on.

However, np.interp is not a replacement for interp1d.
It lacks the equivalent options for the bounding conditions and extrapolation and it always requires sorted input.
It would also make it much easier to compare interpolations using different methods if all would share the same API.
Describe the solution you'd like.
A non-legacy version of interp1d following the same API as the other new classes for piece-wise interpolation.
Describe alternatives you've considered.
No response
Additional context (e.g. screenshots, GIFs)
No response

Note that the dev version has an additional suggestion: https://scipy.github.io/devdocs/tutorial/interpolate/1D.html
Making it more discoverable is definitely in the card, happy to hear suggestions or ---preferably!--- review PRs.
Adding yet another way of doing linear interpolation is not something we would do really.
Legacy code may keep using legacy functions, new code can either keep using interp1d (we do not recommend it, but you can full well not follow the recommendation, it's really up to you), or use what we believe are better alternatives.

Also it looks like we should consider tweaking the wording of the legacy clause. This "may be removed in the future" seems to be misleading.

No follow-up, so I'm going to close this. Thank you @maxnoe for the suggestion regardless!
Documentation improvements are very welcome either way, both for making the "slinear" interpolation more discoverable and for the legacy note wording.


Ban top level t function call as well

Hi!
Thanks for the awesome plugin.
I would like to report a missing case for rule t-call-in-function
It seems the rule only apply to template calls but not a function call, while the function call in such case is also only evaluated making the translation not updated after activating a locale

I made a PR for it, @thekip could you take a look at it please?
Thank you.


Composite unique field validation rule only returns error message for the last field being evaluated

Laravel Version: 5.7.17
PHP Version: 7.3.2
Database Driver & Version: MySQL 5.7.25

Description:
When creation a form request object with a composite unique validation rules like this:
            'name' => [
                Rule::unique('participants')->where(function ($query) {
                    $query->where('country_code', $this->country)
                        ->where('birth_year', $this->birth_year)
                        ->where('location', $this->location);
                }),
            ],
            'country_code' => [
                Rule::unique('participants')->where(function ($query) {
                    $query->where('name', $this->name)
                        ->where('birth_year', $this->birth_year)
                        ->where('location', $this->location);
                }),
            ],
            'birth_year' => [
                Rule::unique('participants')->where(function ($query) {
                    $query->where('country_code', $this->country)
                        ->where('name', $this->name)
                        ->where('location', $this->location);
                }),
            ],
            'location' => [
                Rule::unique('participants')->where(function ($query) {
                    $query->where('country_code', $this->country)
                        ->where('birth_year', $this->birth_year)
                        ->where('name', $this->name);
                }),
            ],

and with corresponding form fields, the validation error message only shows for the last field in the validation list, location in this case. It should really display the unique validation error message for all the fields in the form, when they are attached to the fields using $errors->first('field_name'), not only the last one being evaluated. Is this intended behaviour?
Steps To Reproduce:
Create a form object like the one above with corresponding form fields, add per-field validation messages and submit the form.

Heya, unfortunately we don't support this version anymore. Please check out our support policy on which versions we are currently supporting. Can you please try to upgrade to the latest version and see if your problem persists? If so feel free to reply and we'll try to have a look.


Inventory

Hi bros! Can you help me set up this script without steamapi.com ? I need upload inv on my bot and taking prices from csgofast. Pls, i dont't know js...
I need change inv.js and prices.js right? On what i need change it?

Hey can u help me set up the bot on a vps?
On 17-Jun-2017 8:47 PM, "hermanse"<EMAIL_ADDRESS>wrote:
Hi bros! Can you help me set up this script without steamapi.com ? I need
upload inv on my bot and taking prices from csgofast. Pls, i dont't know
js...
I need change inv.js and prices.js right? On what i need change it?
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/pepzwee/node-csgo-web-tradebot/issues/50, or mute the
thread
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.

I can help, add me on Stram. (Can be found on my github profile.)

me too


Paginagion:When I clicked dot, the picture was switched, but the timer did not start again.

⚠ You did not follow the contributing guidelines!
As stated in these:

You need to fill out the issue template. This step is mandatory! Not doing so will result in your issue getting closed. Don't take this personally if this happens, and feel free to open a new issue once you've gathered all the information required by the template.

Unless you provide a Snack example that reproduces the issue, we won't be able to help you and the thread will be closed.

Closing as no further feedback has been provided.


Feature: TX-Builder - Make it work on xDai

Closes #53.

@dasanra should we request a new environment?

https://safe-apps.dev.gnosisdev.com
https://safe-apps.staging.gnosisdev.com
https://apps.gnosis-safe.io

None of these environments allow us to test the TX-builder on xDai. Another alternative is to remove the env var and handle it in the code as we are doing in safe-react (src/config), the drawback of it is that we need to hardcode the URLs (infura and https://rpc.xdaichain.com).


Wifi OBD no longer working

I own a Veepeak VP-01 Wi-fi OBD reader, purchased exclusively for use with OpenStreetCam. I used the app and OBD reader together for several months without issue, only to have the app stop detecting the reader for no apparent reason. I am still able to use other OBD diagnostics apps on my iPhone, but OSC no longer indicated that it has a connection with my OBD reader. This leads me to believe that the issue is with the OSC app itself. I have attempted to use the connect option in settings with no luck.
App version 1.4.7
iPhone 6S Plus, iOS 10.1.1.

Please check again with the lates version (2.0). We made some fixes for your problem awhile ago.


Docker extension error: Cannot read property 'registerDebugConfigurationProvider'

Issue Type: Bug
Repro steps:
Pretty simple to repro, just download the Docker .VSIX file ( https://marketplace.visualstudio.com/items?itemName=PeterJausovec.vscode-docker ) and load it up into ADS.
Please let me know if there's any more information I can provide?
( Probably fastest to just ping me on twitter: @SQLvariant )
Action: docker.activate
Error type: TypeError
Error Message: Cannot read property 'registerDebugConfigurationProvider' of undefined
Version: 0.5.2
OS: win32
Azure Data Studio version: azuredatastudio 1.4.5 (887f4e8985023602e599cf86bdb44df48bb28569, 2019-02-12T06:20:08.633Z)
OS version: Windows_NT x64 10.0.17763

System Info

Item
Value

CPUs
Intel(R) Core(TM) i7-8650U CPU @ 1.90GHz (8 x 2112)

GPU Status
2d_canvas: enabledchecker_imaging: disabled_offflash_3d: enabledflash_stage3d: enabledflash_stage3d_baseline: enabledgpu_compositing: enabledmultiple_raster_threads: enabled_onnative_gpu_memory_buffers: disabled_softwarerasterization: enabledvideo_decode: enabledvideo_encode: enabledwebgl: enabledwebgl2: enabled

Memory (System)
15.93GB (1.21GB free)

Process Argv
C:\Program Files\Azure Data Studio\azuredatastudio.exe

Screen Reader
no

VM
0%

Extensions (9)

Extension
Author (truncated)
Version

admin-pack
Mic
0.0.1

agent
Mic
0.36.1

import
Mic
0.5.0

profiler
Mic
0.6.0

server-report
Mic
0.1.4

sql-vnext
Mic
0.10.2

PowerShell
ms-
1.11.0

vscode-docker
Pet
0.5.2

sql-search
Red
0.3.0

@SQLvariant this is same error I expect to see when getting the PowerShell extension working (per issue https://github.com/Microsoft/azuredatastudio/issues/3929).  Once PS loads, I expect Docker will work too.  I'll test both.

OK, thanks for having a look.  Since the error message I received was different, I couldn't tell if it was the same.

Docker extension should be working with the latest build.  Please let me know if issues persist.


Dimeehan/log scrubber: accept MatchEvaluator for custom regex replacement logic

Updating this logic to accept matchevaluator for log scrubbing in Omex. Currently, it scrubs the entire key and value with REDACTED which makes it difficult to read and debug.
Scrub q1 and q2 query params:
Input: https://api.host.com/appinstall?q1=abc&p1=444&p2=555&q2=def
Current post-scrub: https://api.host.com/appinstall?REDACTED_PARAMETER&p1=444&p2=555&REDACTED_PARAMETER
Wanted post-scrub: https://api.host.com/appinstall?q1=REDACTED&p1=444&p2=555&q2=REDACTED
TMS new repo will be updated to consume this after this PR has been merged.
PBI: https://dev.azure.com/Office/OC/_boards/board/t/OMEX Liffey/Backlog Items/?workitem=5824879

Unit test profiler from VS2022


fps and getFrameByTime enhancements

Great project! I'm using it to generate stills and thumbnails from video. I ran into a couple of issues and these changes solved them.

getFPS was returning 300 for the videos I am using. Video with multiple slices will not have a tbr that matches the fps. Fortunately ffmpeg info included 'fps' so I made REGEX_FRAME_RATE match fps if present otherwise fallback to tbr.

I use seconds rather than frame numbers and want to be sure I am setting -ss directly. For this reason I made getFrameByTime the primary method for grabbing an image/frame. getFrame is still there with the same interface. The only cavait is that in the latest ffmpeg, -s expects width x height, not height x width. I made the correction only in getFrameByTime. getFrame should continue to work exactly as it did before.

Thanks Rob, I'll take a look at it during christmas


Build gem against multiple ruby versions

I think it would be a good idea to use GitHub actions to test gem against multiple versions of ruby. I'm thinking ruby 2.6.5, 2.7 and ruby 3.0

fixed. now using Github actions to build against ruby v.2.6, 2.7, 3.0


AES CBC produce encrypted data with double length compared to Cryptodome and C mbedtls

NOTE: Please use stackoverflow for support questions.
This repository's issues are reserved for feature requests and bug reports.
I am submitting a …

[x] bug report
[ ] feature request

Description
16 byte input data should produce 16 byte encrypted data. Cryptodome and mbedtls on my ESP32 micro controller are behaving like that. But python-mbedtls produces 32 byte encrypted data.
Here is the sample of my source code for ESP32
  mbedtls_aes_context aes;
  const unsigned char key[16] = "My 16-bytes key";
  unsigned char iv[16] = "My 16-bytes iv.";
  size_t length = 16;
  unsigned char in[length], out[length*2];
  for (size_t i = 0; i < length; i++) in[i] = 0;
  for (size_t i = 0; i < length*2; i++) out[i] = 0;

  mbedtls_aes_setkey_enc(&aes, key, 16*8);
  mbedtls_aes_crypt_cbc(&aes, MBEDTLS_AES_ENCRYPT, length,iv,in, out);

  delay(500);
  Serial.print("Encrypted from ESP32 : ");
  for (size_t i = 0; i < length*2; i++){
    Serial.printf("%d, ",(char)out[i]);
  }
  Serial.println();

That program print:
Encrypted from ESP32 : 98, 203, 172, 171, 204, 8, 236, 28, 167, 205, 120, 72, 12, 242, 72, 164, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,

As you can see, there are 16 non zero data in output byte array of length 32.
Current behavior
16 byte input data produces 32 byte encrypted data. The problem is python-mbedtls refuse to decrypt 16 byte encrypted data from Cryptodome and ESP32 mbedtls while giving this error
  File "desktop/simetrikRemote.py", line 12, in <module>
    print([int(x) for x in d.decrypt(dec_byte[:16])])
  File "src/mbedtls/cipher/_cipher.pyx", line 289, in mbedtls.cipher._cipher.Cipher.decrypt
  File "src/mbedtls/cipher/_cipher.pyx", line 276, in mbedtls.cipher._cipher.Cipher._crypt
  File "src/mbedtls/exceptions.pyx", line 54, in mbedtls.exceptions.check_error
  File "src/mbedtls/exceptions.pyx", line 57, in mbedtls.exceptions.check_error
mbedtls.exceptions.TLSError: TLSError([0x6200] 'CIPHER - Input data contains invalid padding and is rejected')`

Expected behavior
16 byte input data produces 16 byte encrypted data and python-mbedtls can decrypt encryption from another AES implementation.
Steps to reproduce

Encrypt using AES CBC

Minimal demo of the problem
from Cryptodome.Cipher import AES
from mbedtls import cipher

key = b'My 16-bytes key\0'
iv = b"My 16-bytes iv.\0"
raw = bytearray(16) #list of zeros

d1 = AES.new(key, AES.MODE_CBC, iv)
enc1 = d1.encrypt(raw)
print("length of encrypted data using cryptodome: ", len(enc1))
print([int(x) for x in enc1])

d2 = cipher.AES.new(key, cipher.MODE_CBC, iv)
enc2 = d2.encrypt(raw)
print("length of encrypted data using python-mbedtls: ", len(enc2))
print([int(x) for x in enc2])

The program above prints:
length of encrypted data using cryptodome:  16
[98, 203, 172, 171, 204, 8, 236, 28, 167, 205, 120, 72, 12, 242, 72, 164]
length of encrypted data using python-mbedtls:  32
[98, 203, 172, 171, 204, 8, 236, 28, 167, 205, 120, 72, 12, 242, 72, 164, 204, 133, 178, 79, 207, 47, 52, 158, 254, 38, 43, 177, 175, 127, 252, 6]

From where that additional 16 byte come from?
Other information
python-mbedtls : 1.4.0
OS                    : Arch Linux

Thank you for the report. I will have a look.

I am using mbedtls_cipher_crypt from the high-level API. That is at least one difference from your example in C. I have to investigate further.

Well, it really looks like a problem upstream. I have tried to translate your C program to the high-level API and obtain the 32 bytes cipher that you reported as well. This is with libmbedtls 2.16.8. Are you interested in reporting/fixing upstream? If not, I could have a look.
Below is the full program and its output:
#include <stdio.h>
#include <string.h>
#include "mbedtls/cipher.h"

int main() {
  const unsigned char key[16] = "My 16-bytes key";
  const unsigned char iv[16] = "My 16-bytes iv.";
  size_t length = 16;

  unsigned char in[length];
  memset(in, 0, sizeof in);

  mbedtls_cipher_context_t ctx;
  mbedtls_cipher_init(&ctx);
  mbedtls_cipher_setup(&ctx, mbedtls_cipher_info_from_string("AES-128-CBC"));
  mbedtls_cipher_setkey(&ctx, key, 8 * sizeof key, MBEDTLS_ENCRYPT);

  puts(ctx.cipher_info->name);
  printf("IV size: %i\n", ctx.cipher_info->iv_size);
  printf("Block size: %i\n", ctx.cipher_info->block_size);

  unsigned char out[length + ctx.cipher_info->block_size];
  size_t olen;
  mbedtls_cipher_crypt(&ctx, iv, sizeof iv, in, sizeof in, out, &olen);

  printf("got: %zu bytes\n", olen);

  for (size_t i = 0; i < olen; i++) {
    printf("%d, ", (unsigned char)out[i]);
  }
  printf("\n");

  mbedtls_cipher_free(&ctx);
  return 0;
}

AES-128-CBC
IV size: 16
Block size: 16
got: 32 bytes
98, 203, 172, 171, 204, 8, 236, 28, 167, 205, 120, 72, 12, 242, 72, 164, 204, 133, 178, 79, 207, 47, 52, 158, 254, 38, 43, 177, 175, 127, 252, 6,

Thanks, I understand C/C++ and Python but I think I am incompetent to make or improve C/C++ based Python library.

Sure, no problem. I'll keep you updated.

After some more investigation: The high-level API adds a PKCS7 padding block for CBC in mbedtls_cipher_finish(). With mbedtls_aes_context, it looks like you have the possibility to do it yourself.
Actually, libmbedtls has the option to not pad with mbedtls_cipher_set_padding_mode( &ctx, MBEDTLS_PADDING_NONE ) but I have not bound this method yet so it is not directly available from Python.
I can add the option to set the padding, libmbedtls has PKCS7, ISO/IEC 7816-4, ANSI X.923, zero-padding, and no padding. Is this interesting to you?
Otherwise, you could as well use ECB, which is simpler and has no padding.

Also, it looks like the padding functions are private in libmbedtls (static in library/cipher.c) so it does not seem like I can make the padding option as nice as pycrypto. I will have to double check but I can probably only make it an option to the ciphers or to the encryption/decryption functions.

Sᴇᴄᴜʀɪᴛʏ ᴅɪsᴄʟᴀɪᴍᴇʀ: I do not encourage you to go ECB, it all depends on your application: CFB, or another cipher/mode might as well give n bytes out for n bytes in with better security 😅


Fix some TLSv1.3 alert issues

Ensure that the certificate required alert actually gets sent (and doesn't
get translated into handshake failure in TLSv1.3).
Ensure that proper reason codes are given for the new TLSv1.3 alerts.
Remove an out of date macro for TLS13_AD_END_OF_EARLY_DATA. This is a left
over from an earlier TLSv1.3 draft that is no longer used.
Fixes #6804

Pushed. Thanks.


support automatically hydrating nested domain objects when instantiating

for example:
    user.directories.some((userDir) => serialize(getUniqueIdentifier(new Directory(userDir))) === serialize(getUniqueIdentifier(directory))),

we are required to do new Directory(userDir) in order to use getUniqueIdentifier(), since otherwise userDir is just an object, not an instanceof DomainObject, because when user was instantiated it was instantiated as new User(dbObject)
--
we are told about the DomainObject that each User.directories[number] is - but we are not told about that at run time. Only type defs know that - and those get compiled away :(
is there another way to get the type definitions at run time?

potentially could use transformer to do this for us: https://github.com/woutervh-/typescript-is

note: per #6, if we have a function that is able to make the type definitions accessible at runtime, we should be able to solve this problem
options:

perhaps we can use that to "analyze self" -> in runtime code, have it self analyze to determine what the dependencies are and then hydrate them
perhaps we ask the user to generate the definition and leave it somewhere, and then define DomainObject.dependencies=DomainObjectRuntimeTypeDefinition.dependencies

yeah! that works!
import { ClientAccess } from './ClientAccess';

ClientAccess.unique = ['a', 'b', 'c'];

so we can have domain-objects generate type-decorations code, which repeats all the good stuff we have in the TS types in a run time accessible way for the object. (e.g., dependencies, UniqueIdentifier (#2), etc)
it wouldn't even have to generate the full DomainObjectTypeInformation - it can just generate the TypeDecorations. (e.g., /src/models/domainObjects/.generated/decorations.ts) - and then the user just has to make sure they import that one file whenever they use the domain object they're interested in
(e.g., in the /src/models/domainObjects/index.ts)

a problem could arise when users accidentally import domain objects directly, instead of from the index.ts directory. Wonder if there is a way to put "fences" on those exports. (cause if they do that, the decorations wont be imported)

alternatively, we can import the decorations in each model file. (it does suck that its getting a little "magical" now though - since there is an import that is globally affecting other things...)

we could also have
import { ClientAccessTypeInformation } from './generated/typeinfo';

class ClientAccess ... {
  public static typeinfo = ClientAccessTypeInformation;
}
```
and now `typeinfo` is used directly, but that wont help #2 - since we _want_ to have `ClientAccess.UniqueIdentifier = X` set

what if the contract was, to still be explicit:
import { decorate } from 'domain-objects';
-vs-
import { decorate } from './generated/decorations';
export class ClientAccess ... {
  public static unique = [];
}
decorate(ClientAccess); // mutates the ClientAccess class; very explicit about mutating. add whatever additional features we want to expose

-vs-
class ClientAccess ... {

}

const ClientAccessDecorated = withDecorations(ClientAccess); // <-- immutable, just extends and assigns... but more confusing and weirder syntax...

export ClientAccessDecorated;

so, effectively, decorate would simply automate the process of setting the public static variables such as dependencies and UniqueIdentifier, and whatever else that we could figure out from type defs, but dont have access to at runtime - or could define alternatively, but can't get the types right at run time.

note: we want to make sure that the error thrown has full context of object. i.e.,: validate, THEN hydrate.

before the decorate solution is out, we still can support this feature by asking the user to manually define the "nested" domain objects. 75045c1 does that for us

done w/ tag v0.5.0


Event bus + plugin architecture proof of concept

What is the purpose of this change? What does it change?
Add an event bus to be able to have decoupled extensions implemented as listeners of events produced at different stages of command execution. Commands would thus be able to push events during different stages of their execution (e.g. pre-run, post-complete, post-validate, post-run). The bus will allow interested third parties to register listeners to react to events and possibly interrupt the command processing based on this (by returning a specific error type, which will allow the bus to abort the command processing and notify listeners that might have already performed some process based on the event to revert their work).
Was the change discussed in an issue?
#1173
How to test changes?
In progress.

:white_check_mark: odo build 849 completed and artifacts can be found here (for commit https://github.com/redhat-developer/odo/commit/fa8d7a02a3 by @metacosm)

:white_check_mark: odo build 854 completed and artifacts can be found here (for commit https://github.com/redhat-developer/odo/commit/9900386834 by @metacosm)

@metacosm , can you please also create the issue regarding the same and provide more context or any specific use case for this ?

:white_check_mark: odo build 934 completed and artifacts can be found here (for commit https://github.com/redhat-developer/odo/commit/3519ce3bdd by @metacosm)

:white_check_mark: odo build 935 completed and artifacts can be found here (for commit https://github.com/redhat-developer/odo/commit/8dbd8fe8d2 by @metacosm)

This PR as of now needs alot of work due to the major changes in odo. It would be better if a new PR using the current master is created at a later point when plugins become priority.
Hence closing the PR


Suggestion

Maybe this can be integrated on this project? https://github.com/RisingStack/graffiti

graffiti is a great approach to building a GraphQL server, but I think one of the main benefits of this stack is the fact that the schema is decoupled from the database implementation. Migrating this server from Mongo to any of the other supported databases is trivial.

Ok! you are right I think.


Mininet hosts fails to ping internet while using l3_learning script for pox controller

Im trying to ping the internet through the mininet hosts creating the topology using --nat command.
The hosts can connect to the internet while using the l2_learning script while it fails to connect while using l3_learning script,it goes to an infinite loop of flooding ARP requests and there is no reply.
What might be the issue?

I don't use Mininet anymore and haven't really looked at this setup, so I'm just guessing, but...
What is the routing table like on the hosts?  If they're set up to just use a specific interface, that won't be enough... you'll need to have a gateway set for reaching the internet.

The routing table on the host shows this.

I haven't messed with l3_learning for a long time, but thinking about it a bit more... l3_learning is sort of a funny animal, and I think your use case is just not something it's meant to do.  It could be made to do it with some work, but whether that'd be worth it, I think depends on what exactly you're trying to do...

I'm working on a SDN project and want to fetch a file from mininet hosts.Some of the hosts act as a cache server which uses ARP to send the file to other hosts which would require use of L3_learning for ARP .
I cannot find a reason on why l2_learning works fine with the same topology whereas l3_learning cannot get the traffic to flow through it.

If the hosts are sending ARPs, the ARPs will certainly be forwarding by l2_learning...

Why not by l3_learning?

For starters, the comment at the top of l3_learning says:
"Keep a table that maps IP addresses to MAC addresses and switch ports.
Stock this table using information from ARP and IP packets."
You'll never get an IP packet from <IP_ADDRESS> without sending one to it first (due to the NAT/routing outside of the OpenFlow part of the network).  So the only way you could populate this table entry would be via an ARP.  But you'll also never get an ARP from <IP_ADDRESS> (or any other Internet address).
Thus, you'll never get a table entry for <IP_ADDRESS>.  So you can never send to it.
l3_learning isn't how L3 works on a "normal" network.  It's specifically an example of doing something sort of unusual.  It wouldn't be that hard to make it work, but it won't work out of the box.

Ohkay , thanks a lot for the information.


Add back in max game size support

Need a way to limit the size of a game based on the files that are critical and everything inside of the sandbox folder.
This should be tied into the export .pv8 process which should only generate a zip with the core files when doing a build.

This is fixed.


Library not load

Hi !
I am learning development and your project seems easy to learn.
I installed your .deb but the libcolorpicker.dylib library and the BattiBarPrefs image not found makes the project untestable

Hello, and good luck learning tweak development. I'm confused by your comment, as you're stating you installed the deb(eg. the finished executable you need to test it), but you are also claiming that it is untestable? If you installed from a precompiled deb, then you need to make sure you have installed the correct dependencies(found in the control file. As far as an image you are claiming is missing, I see all three icon images found in the resources folder of the preferences directory.
This project was last built when it was stated for release, and I have been out of the tweak development community for some time now. If you'd like to see the finished product, I suggest you install it from the repository(either Packix of Havoc, I haven't kept up to date on the switch) to ensure you have all dependencies. I would suggest reaching out to an active developer for more up to date information.
Best of luck
Issue closed, as with given information there is not enough to fix a possibly non-issue.


[Problem]: cannot pull most of the tags for ghcr.io/buanet/iobroker

Description / Beschreibung
Seems like most of the manifests on ghcr.io/buanet/iobroker are not pullable
Image version
9.0.1
Docker logs / Docker Protokoll
docker pull ghcr.io/buanet/iobroker:v9.0.1
v9.0.0: Pulling from buanet/iobroker
manifest unknown

docker pull ghcr.io/buanet/iobroker:v8.0.1
v8.0.1: Pulling from buanet/iobroker
manifest unknown

docker pull ghcr.io/buanet/iobroker:v8.0.0
v8.0.0: Pulling from buanet/iobroker
manifest unknown

docker pull ghcr.io/buanet/iobroker:v7.2.0
v7.2.0: Pulling from buanet/iobroker
manifest unknown

docker pull ghcr.io/buanet/iobroker:v7.1.2
-> pulls

am i missing something?

am i missing something?

Sure. Duplicate of #330


Query about basal TFs

I am revising some TF annotations, and I was wondering why  there is a term
TFIIIB-type transcription factor activity

for TFIIB, but no equivalent terms for the TFIID,F,H etc?

Hi Val,
Note that the term you list is not for TF-II-B, but for TF-III-B (hyphens for clarity in number if 'I's).
TFIIIB is kind of a special case, largely because it is a RNAP III txn factor, instead of one for RNAP II. It does a very specific job that can be defined in terms of what it is binding to. From what I read when David H and I were working on this, there isn't as much variability in how RNAP III promoters work, i.e. which factors bind to the promoter recruit the RNAP.
There is so much variability in how promoters for RNAP II work that I can't define how any of the basal factors for RNAP II work, so there are no terms like this for any of the RNAP II basal txn factors.
-Karen

OK just curious, closing


[MINOR][CORE|SQL|STREAMING|YARN]Fix incorrect comment of SessionCatalog and all the typos 'temp'.

What changes were proposed in this pull request?
First
I accidentally found the comment of SessionCatalog is incorrect.
The original comment of SessionCatalog contains the description An internal catalog that is used by a Spark Session. But SessionCatalog also used by Rule, LogicalPlan and so on.
Second
Spark comment contains a lot of typo 'temp', All the typos should replaced by word 'temporary'.
How was this patch tested?
Not need UT.

That's not a typo. 'temp' is widely understood shorthand for 'temporary'


AnimatableTextField breaks insets/leftView

Setting a leftView of an AnimatableTextField or trying to specify insets otherwise is broken and does not produce the desired leading/trailing padding.

Sorry we missed that issue, closing this now since it's been a while, let us know if you still have any issues.


🐛 Notification Do not Disturb not working

branch
stable
Architecture
x86_64
Description
I don't know what just happened, but the appearance of notifications changed and do not disturb does not make a difference anymore:

Reproduction steps
unsure

related to https://github.com/manjaro-sway/manjaro-sway/discussions/814

and for some reason, notifications are also sticky now

Your notifications don't look like the themed mako that is installed by default.
recording_20241110-192339.webm

No reaction, no support.

I guess it was a transient issue, thanks anyway :)


Fix i18n button not updating (#1181)

Added a value prop to the Toggle component, being passed down to the Select component to explicitly state which option is selected. The problem seemed to be that when selecting a new language, the component would re-render the options in the order they are passed down via the values prop, thus causing the error.

Coverage remained the same at 98.605% when pulling beb7839ff12a7a410d7607b8bbef37ec1e3a5cd2 on adjnor:fix-i18n-button into 3aafc0c593d2f51bda03538d7131dec7168b8475 on mxstbr:dev.

This LGTM! @gihrig @sedubois I'm away for the weekend, can one of you merge to dev and cherry pick the commit to master?

I'm still seeing the problem :-/
I did:
git clone https://github.com/adjnor/react-boilerplate.git react-bp2 && cd react-bp2
git checkout -b adjnor-fix-i18n-button
yarn
npm start
localhost:3000
Change language to de: Language changes, but button still shows en
I have cleared Application > Clear storage > Clear site data, then opened new tab.
When changing language, I get the following console error:

etc...

@gihrig, when you checkout my branch it should be 'git checkout fix-i18n-button' otherwise I think you're creating a new branch.
As for the errors in the console, it's unrelated to this PR, it comes from react-intl complaining when a message has not been passed for the chosen locale

Yes, I copied the URL from Github, git complained, so I edited without really looking, My bad!
So yes, works as expected now. Thanks for contributing :tada:


Cannot reference both profileDOS and profileBotDefense. Duplicate profiles error message.

Environment

Application Services Version: 3.19.1
BIG-IP Version: <IP_ADDRESS>

Summary
Using AS3, I cannot create both a DoS profile and reference a Bot profile on Big-IP 15.1. When creating a DoS profile, AS3 seems to be creating a shadow f5_appsvcs_<DOS PROFILE NAME>_botDefense Bot profile which then creates a conflict when trying to add the desired Bot profile.
Steps To Reproduce
Steps to reproduce the behavior:

Submit the following declaration:

{
    "class": "ADC",
    "schemaVersion": "3.19.0",
    "Common": {
        "class": "Tenant",
        "Shared": {
            "class": "Application",
            "template": "shared",
            "vs_http": {
                "layer4": "tcp",
                "pool": "http-pool",
                "translateServerAddress": true,
                "translateServerPort": true,
                "class": "Service_HTTP",
                "profileHTTP": {
                    "use": "/Common/Shared/custom-http"
                },
                "profileTCP": {
                    "use": "/Common/Shared/custom-tcp"
                },
                "profileDOS": {
                    "use": "/Common/Shared/custom-dos"
                 },
                 "profileBotDefense": {
                    "bigip": "/Common/bot-defense"
                },
                "virtualAddresses": [
                    "<IP_ADDRESS>/0"
                ],
                "virtualPort": 80,
                "snat": "auto"
            },
            "custom-http": {
                "trustXFF": true,
                "maxHeaderCount": 256,
                "maxHeaderSize": 65536,
                "hstsIncludeSubdomains": false,
                "proxyType": "reverse",
                "serverHeaderValue": "none",
                "class": "HTTP_Profile"
            },
            "custom-tcp": {
                "class": "TCP_Profile"
            },
            "http-pool": {
                "members": [
                    {
                        "addressDiscovery": "static",
                        "servicePort": 80,
                        "serverAddresses": [
                            "<IP_ADDRESS>"
                        ],
                        "shareNodes": true
                    }
                ],
                "monitors": [
                    {
                        "use": "/Common/Shared/http-monitor"
                    }
                ],
                "class": "Pool"
            },
            "custom-dos": {
                "application": {
                    "triggerIRule": true,
                    "captchaResponse": {
                        "failure": "You have entered an invalid answer for the question. Please, try again.\n
\n%DOSL7.captcha.image% %DOSL7.captcha.audio% %DOSL7.captcha.change%\n
\nWhat code is in the image\\?\n%DOSL7.captcha.solution%\n
\n%DOSL7.captcha.submit%\n
\n
\nYour support ID is: %DOSL7.captcha.support_id%.",
                        "first": "This question is for testing whether you are a human visitor and to prevent automated spam submission.\n
\n%DOSL7.captcha.image% %DOSL7.captcha.audio% %DOSL7.captcha.change%\n
\nWhat code is in the image\\?\n%DOSL7.captcha.solution%\n
\n%DOSL7.captcha.submit%\n
\n
\nYour support ID is: %DOSL7.captcha.support_id%."
                    },
                    "heavyURLProtection": {
                        "automaticDetectionEnabled": false
                    },
                    "rateBasedDetection": {
                        "thresholdsMode": "manual",
                        "escalationPeriod": 45,
                        "deEscalationPeriod": 600,
                        "sourceIP": {
                            "maximumTps": 40,
                            "minimumTps": 35
                        },
                        "url": {
                            "heavyURLProtectionEnabled": false,
                            "rateLimitingEnabled": false
                        }
                    },
                    "stressBasedDetection": {
                        "thresholdsMode": "manual",
                        "badActor": {
                            "mitigationMode": "none"
                        }
                    }
                },
                "class": "DOS_Profile"
            },
            "http-monitor": {
                "adaptive": false,
                "interval": 6,
                "dscp": 0,
                "receive": "OK$",
                "send": "GET /health HTTP/1.1\\r\\nConnection: Close\\r\\nHost: localhost\\r\\n\\r\\n",
                "timeUntilUp": 0,
                "timeout": 21,
                "class": "Monitor",
                "monitorType": "http",
                "targetAddress": "",
                "targetPort": 0
            }
        }
    }
}

Observe the following error response:

{"results":[{"code":422,"message":"declaration failed","response":"01070097:3: Virtual server /Common/Shared/vs_http lists duplicate profiles.","host":"localhost","tenant":"Common","runTime":1948},{"code":422,"message":"declaration failed","response":"01070097:3: Virtual server /Common/Shared/vs_http lists duplicate profiles.","host":"localhost","tenant":"Common","runTime":2504}],"declaration":"HTML Tag-like Content in the Request URL/Body","code":422}

Expected Behavior
A DoS profile named custom-dos to be attached to the virtual server.
A Bot profile named bot-defense (default) attached to the virtual server.
Actual Behavior
The DoS profile named custom-dos is attached to the virtual server, along with a system-generated f5_appsvcs_custom-dos_botDefense bot profile. When AS3 tries to associate the specified bot profile bot-defense the error duplicate profiles error is observed.
If I remove the profileDOS element from the declaration, I can apply the bot profile as expected.
If I remove the profileBotDefense element from the declaration, I can apply the DoS profile as expected.
I cannot reference both the profileDOS and profileBotDefense profiles due to the system generated bot profile from the DoS profile.
For this example, I am using the Big-IP 15.1 bot-profile which TMSH config is:
    app-service none
    whitelist {
        apple_touch_1 {
            match-order 2
            url /apple-touch-icon*.png
        }
        favicon_1 {
            match-order 1
            url /favicon.ico
        }
    }
}

Thank for for your bug report. This is being tracked internally at https://jira.pdsea.f5net.com/browse/AUTOTOOL-1588

This issue should be resolved in the 3.22.0 release.


Fixing file location on package.json

Codecov Report

Merging #413 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master     #413   +/-   ##
=======================================
  Coverage   82.56%   82.56%
=======================================
  Files          14       14
  Lines         562      562
=======================================
  Hits          464      464
  Misses         98       98

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I think re-building the dist/ folder as part of the commit is a bad idea because the contents of your dist may not necessarily reflect all the commits that have gone into master since your generated dist was created. It also pollutes the diff when trying to do code reviews or check commits in the git history.


Test with DMD 2.069.0

<EMAIL_ADDRESS>

Oh I hadn't see you tagged 0.7.26
I'm inclined not to remove support for 2.066.1 (even if I'd really like to) until GCC is ready.

Yeah, we definitely still need to support 2.066.1. One can only hope that some day LDC/GDC will be part of the autotester...