Working basic and advance toggle

Basic Toggle: A button to switch between 2 modes
Advance Toggle: Customisable number of modes for toggling, names can be included for each mode
It is possible to disable the toggles

Dropdown list component is complete
Styling consistency across basic toggle, advance toggle and dropdown list components

Done dropdown text box
Unique event emitter for all components


Feature request: Export to Azure Pricing

It would be great if we could use data that's exported to Excel and feed into Azure Pricing calculator or provide estimate of resources cost using Azure API, such as: https://learn.microsoft.com/en-us/rest/api/cost-management/retail-prices/azure-retail-prices

I've tried to add this feature (Azure Cost data) into the excel. But back then the idea was to give the real daily cost of each resource. But at least the way I was trying it was taking too much time to build the report and some resources did not have the cost information, like databricks VMs that are created and deleted multiple times during the day.
So we ended up giving up on that idea.
But consulting the API and giving a generic cost might work.


Gh 1294 remove unused addgraph

Codecov Report

:exclamation: No coverage uploaded for pull request base (develop@839cee4). Click here to learn what that means.
The diff coverage is 100%.

@@            Coverage Diff             @@
##             develop    #1302   +/-   ##
==========================================
  Coverage           ?   64.55%
  Complexity         ?     1531
==========================================
  Files              ?      688
  Lines              ?    22238
  Branches           ?     2738
==========================================
  Hits               ?    14356
  Misses             ?     6760
  Partials           ?     1122

Impacted Files
Coverage Δ
Complexity Δ

...gov/gchq/gaffer/federatedstore/FederatedStore.java
96.53% <ø> (ø)
0 <0> (?)

...gchq/gaffer/federatedstore/operation/AddGraph.java
88.23% <100%> (ø)
0 <0> (?)

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 839cee4...7030b5c. Read the comment docs.


[Translation] Contact Card German

There is no Translation in German for Prices on Contact Card

page 5050 "Contact Card"
group(Prices)
{
action(PriceLists)
{

Thanks for reporting this. We agree, and we’ll publish a fix asap, either in an update for the current version or in the next major release. Please do not reply to this, as we do not monitor closed issues. If you have follow-up questions or requests, please create a new issue where you reference this one.


Add version cmd

I also moved version number from setup.py to osdk.version (which is a common way to embeded version in python package: https://stackoverflow.com/questions/458550/standard-way-to-embed-version-into-python-package)

Lgtm


Added tanh activation and a way to switch between different functions

Also removed function so user does not have to choose both the correct activation function with the correct derivative of the activation function

When testing with the xor..... it is a little sensitive to the learning rate......

Made changes and fixed a confilict

this seems to be covered on PR #62...

Yes indeed, apologies @schrummy14 but I just couldn't resist the object-oriented solution.

That is fine. It will allow for a cleaner solution.


fix: fix faulty negation of expression

This fixes a regression in #3573. The intention was that even if jx gitops helmfile report would always change the files in doc there wouldn't an infinite loop. But the logic was faulty and here is new, better tested, attempt.

/cc tomhobson babadofar

/approve


more context for this parameter pelase

on file https://github.com/Microsoft/vscode/blob/master/src/vs/workbench/browser/parts/views/viewsViewlet.ts
folks helping out with the translations would like to know what is the parameter gong to be replaced with - or get a sample, please. this is the string:
"Visibility cannot be toggled for this view {0}"
thanks!

VSCode Version:
OS Version:

Steps to Reproduce:

Does this issue occur when all extensions are disabled?: Yes/No

Parameter that will be replaced here is the id of the view


Release snowchains_core v0.3.1

Codecov Report

Merging #72 into master will not change coverage.
The diff coverage is n/a.

@@          Coverage Diff           @@
##           master     #72   +/-   ##
======================================
  Coverage    2.95%   2.95%
======================================
  Files          24      24
  Lines        4440    4440
  Branches     1965    1965
======================================
  Hits          131     131
  Misses       4186    4186
  Partials      123     123

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 091e2ad...224e601. Read the comment docs.


Unable to use multiple dots in version

when using the version option, using 1.0.0 will not count as a valid version but 1.0 will pass.
svg2ttf: invalid option, version - "1.0.0"

Given that node packages all use multiple dot versions, I would like to ask to support this. I currently use my package.json version as a string for this option and it fails.

Fonts are NOT node packages. Also see #112 and continue there if you have "trusted" technical details to add.


Dose the data division for multi-gpu destruct the accuracy?

Data division for multi-gpu after tf1.11 seems to have the same shape of data across all gpus, which will result in a bigger variance of loss between different steps. For example, for the transformer model, when in one step, all the gpus are feeded with the data with length near 8, but in the next step, all the gpus are feeded with the data with length near 32, which will result in a bigger variance of loss.
In practice, I got a lower accuracy trained with tf2.0 than tf1.11.
@guptapriya @yuefengz @zongweiz @sgpyc

Hi,
Thank you for your question. Can you elaborate on your example? Why is the
data length 8 vs 32 in subsequent steps? Do you mean you have dynamic input
per step?
We have been able to train transformer to the state of art accuracy with
2.0 and 1.15, but we havent tested with 1.11. can you share your setup?
Which API are you you using, what are the batch sizes etc?
On Tue, Oct 15, 2019, 2:32 AM venuswu<EMAIL_ADDRESS>wrote:

Data division for multi-gpu after tf1.11 seems to have the same shape of
data across all gpus, which will result in a bigger variance of loss
between different steps. For example, for the transformer model, when in
one step, all the gpus are feeded with the data with length near 8, but in
the next step, all the gpus are feeded with the data with length near 32,
which will result in a bigger variance of loss.
In practice, I got a lower accuracy trained with tf2.0 than tf1.11.
@guptapriya https://github.com/guptapriya @yuefengz
https://github.com/yuefengz @zongweiz https://github.com/zongweiz
@sgpyc https://github.com/sgpyc
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/tensorflow/tensorflow/issues/33369?email_source=notifications&email_token=ADLTSF4IFVKOA3AHVZHYSV3QOVPW3A5CNFSM4JAX3ZAKYY3PNVWWK3TUL52HS4DFUVEXG43VMWVGG33NNVSW45C7NFSM4HRYXD4A,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/ADLTSF5JAK4TUE6MUJFV2ADQOVPW3ANCNFSM4JAX3ZAA
.

Yes, I used dynamic batchsize to train the official/transformer.
https://github.com/tensorflow/models/blob/master/official/transformer/v2/data_pipeline.py
Here is the data pipeline of 2.0 same as 1.11, for which batchsize means the number of tokens.  For example in tf1.11, I set the batchsize to 4096 which means 4096 tokens for every replica, for a replica       the length of the tokens seem to be as near as possible(padding fills up the gap), for example a replica can get a batch with the shape of [1024,4], and another get a shape of [ 128,32], in the same step, the shape of the batch may vary between different replica. But there is similar situation between steps.
For the later version like tf1.14 and tf2.0, the parameter batchsize means total tokens of all the replicas, so for example the batchsize 4096*8 may have a shape of [8192,4] and autoshard across all the replicas, every replica get the same shape of [1024,4], but for the next step, it may read a shape of [1024, 32], and every replica get the same shape of [128,32], which may result in a variance between different steps.
I have read a paper https://arxiv.org/pdf/1806.00187.pdf

in which it is said that it my destruct the accuracy with all replica feeded with the same shape of data.
I don't kown whether I have described the question clearly.
@guptapriya @ravikyram

python transformer_main.py --data_dir=$DATA_DIR --model_dir=$MODEL_DIR \     --vocab_file=$VOCAB_FILE --param_set=$PARAM_SET \     --train_steps=$TRAIN_STEP --steps_between_evals=$TRAIN_STEP \     --batch_size=4096 --max_length=256 \     --num_gpus=8 \     --epochs=275 \     --enable_time_history=True \     --enable_xla=False \     --enable_grappler_layout_optimizer=True
Here is the command line.
@guptapriya @ravikyram

Is there a option for Backward compatibility? @guptapriya @ravikyram

@venuswu Is there a way that you can provide us a minimal reproducible example ? Also can you please explain it clearly as I am unable to understand what you are trying to convey? Whats the root cause of the issue?

Clsoing this issue as it has been inactive for more than 14 days. Please add additional details and we can open this issue again


[TF2.0] Can't use tf.data.Dataset::cache with distribution strategy

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): Yes
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 18.04
TensorFlow installed from (source or binary): pip tf-nightly-gpu-2.0-preview
TensorFlow version (use command below): 2.0.0.dev20190514
Python version: 3.7.3
CUDA/cuDNN version: 10 / <IP_ADDRESS>
GPU model and memory: V100

Describe the current behavior
Using tf.data.Dataset::cache and tf.distribute.MirroredStrategy() will fail with Cache should only be read after it has been completed. [Op:MultiDeviceIteratorInit] in TF 2.0 nightly.
Describe the expected behavior
Using tf-nightly-gpu==1.14.1.dev20190514 graph mode tf.data caching works using distribution strategy and doesn't throw an error.
Code to reproduce the issue
import tensorflow as tf
import tensorflow_datasets as tfds

mnist_train, mnist_test = tfds.load(name='mnist', split=[tfds.Split.TRAIN, tfds.Split.TEST], as_supervised=True, data_dir="gs://plumerai/data")

strategy = tf.distribute.MirroredStrategy()

def scale(image, label):
  image = tf.cast(image, tf.float32)
  image /= 255

  return image, label

train_dataset = mnist_train.cache().repeat().map(scale).shuffle(1000).batch(256)
test_dataset = mnist_test.cache().repeat().map(scale).batch(256)

with strategy.scope():
  model = tf.keras.Sequential([
      tf.keras.layers.Conv2D(32, 3, activation='relu', input_shape=(28, 28, 1)),
      tf.keras.layers.MaxPooling2D(),
      tf.keras.layers.Flatten(),
      tf.keras.layers.Dense(64, activation='relu'),
      tf.keras.layers.Dense(10, activation='softmax')
  ])

  model.compile(loss='sparse_categorical_crossentropy',
                optimizer=tf.keras.optimizers.Adam(),
                metrics=['accuracy'])

model.fit(train_dataset, validation_data=test_dataset, steps_per_epoch=100, validation_steps=10, epochs=10)

Other info / logs
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py", line 646, in fit validation_freq=validation_freq)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training_distributed.py", line 143, in fit_distributed steps_name='steps_per_epoch')
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training_arrays.py", line 194, in model_iteration val_iterator = _get_iterator(val_inputs, model._distribution_strategy)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training_arrays.py", line 512, in _get_iterator inputs, distribution_strategy)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/distribute/distributed_training_utils.py", line 529, in get_iterator initialize_iterator(iterator, distribution_strategy)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/distribute/distributed_training_utils.py", line 535, in initialize_iterator init_op = control_flow_ops.group(iterator.initialize())
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/input_lib.py", line 274, in initialize return super(DistributedIteratorV1, self)._initializer
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/input_lib.py", line 259, in _initializer init_ops.extend(it.initialize())
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/input_lib.py", line 660, in initialize self._iterator._eager_reset() # pylint: disable=protected-access
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/data/ops/multi_device_iterator_ops.py", line 333, in _eager_reset max_buffer_size=self._max_buffer_size)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/ops/gen_dataset_ops.py", line 3118, in multi_device_iterator_init _six.raise_from(_core._status_to_exception(e.code, message), None)
File "<string>", line 3, in raise_from tensorflow.python.framework.errors_impl.InternalError: Cache should only be read after it has been completed. [Op:MultiDeviceIteratorInit]

Will it be possible to provide full minimal code snippet that can reproduce the issue on version 2.0.0.dev20190514. That would really help us to debug faster. Thanks!

@achandraa Sorry for the incomplete code sample. This was the result of some late night debugging ;)
I added a complete code sample above.

Hi! Any update in this?

I meet the same problem today with newest released tf2.0.

Same problem with me. If I cache on the validation data I get the same error. What do we do wrong?

Same problem with me. If I cache on the validation data and use the validation_step in the fit() call, I always get the same error.
However, if I do not include the validation_step, and remove the repeat() from the validation dataset, it works nicely, as the validation runs until the validation_data dataset is exhausted (see the documentation of fit(). As it is not necessary to shuffle the validation data, the repeat is not really necessary here. So this way the problem is solved.
So I guess I did not use the correct validation_steps value after all, but it is not really needed.

I just found my problem come from that I accidently used same tf dataset for both train and valid stage. In the same time, the number of steps I set do not exhausted all data in the cache.
After I use different tf.data.dataset and set a larger number of steps, the problem solved.

Thanks for @darcula1993 . Using cache() after take() or skip() solved my problem.

I'm experiencing the same issue.
both suggestions by darcula1993 and sbl1996 dont help
A minimal reproduction code:

%tensorflow_version 2.x
#must use tf 1.x to use TPU properly
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
import tensorflow_datasets as tfds
import os

resolver = tf.distribute.cluster_resolver.TPUClusterResolver(tpu='grpc://' + os.environ['COLAB_TPU_ADDR'])
tf.config.experimental_connect_to_cluster(resolver)
tf.tpu.experimental.initialize_tpu_system(resolver)
strategy = tf.distribute.experimental.TPUStrategy(resolver)

#constants
IMG_HEIGHT=IMG_WIDTH=200
BATCH_SIZE=128

def create_model():
  model = tf.keras.models.Sequential()
  model.add(tf.keras.layers.BatchNormalization(input_shape=(IMG_HEIGHT,IMG_WIDTH,1)))
  model.add(tf.keras.layers.Conv2D(64, (3, 3), activation='elu'))
  model.add(tf.keras.layers.MaxPooling2D(2))
  model.add(tf.keras.layers.Dropout(0.25))

  model.add(tf.keras.layers.BatchNormalization())
  model.add(tf.keras.layers.Conv2D(64, (3, 3), activation='elu'))
  model.add(tf.keras.layers.MaxPooling2D(2))
  model.add(tf.keras.layers.Dropout(0.25))

  model.add(tf.keras.layers.BatchNormalization())
  model.add(tf.keras.layers.Conv2D(64, (5, 5), activation='elu'))
  model.add(tf.keras.layers.MaxPooling2D(2))
  model.add(tf.keras.layers.Dropout(0.25))

  model.add(tf.keras.layers.BatchNormalization())
  model.add(tf.keras.layers.Conv2D(128, (3, 3),  activation='elu'))
  model.add(tf.keras.layers.MaxPooling2D(2))
  model.add(tf.keras.layers.Dropout(0.25))

  model.add(tf.keras.layers.BatchNormalization())
  model.add(tf.keras.layers.Conv2D(256, (3, 3),  activation='elu'))
  #model.add(tf.keras.layers.MaxPooling2D(2))
  model.add(tf.keras.layers.Dropout(0.25))

  model.add(tf.keras.layers.BatchNormalization())
  model.add(tf.keras.layers.Conv2D(512, (3, 3),  activation='elu'))
  model.add(tf.keras.layers.MaxPooling2D(2))
  model.add(tf.keras.layers.Dropout(0.25))

  model.add(tf.keras.layers.Flatten())
  model.add(tf.keras.layers.Dense(256))
  model.add(tf.keras.layers.Activation('elu'))
  model.add(tf.keras.layers.Dropout(0.5))
  model.add(tf.keras.layers.Dense(10))
  model.add(tf.keras.layers.Activation('softmax'))
  return model

@tf.function
def convert(image,label):
  return (tf.image.convert_image_dtype(image, tf.float32),tf.expand_dims(tf.cast(label,tf.float32),0))
@tf.function
def resize(image,label):
  return (tf.image.resize(image,(IMG_HEIGHT,IMG_WIDTH)),label)

test_split, valid_split, train_split = tfds.Split.TRAIN.subsplit([10, 10, 80])
train_ds = (tfds.load("mnist", split=train_split, as_supervised=True, try_gcs=True)
  .map(convert)
  .map(resize)
  .batch(BATCH_SIZE).take(144).cache().repeat().prefetch(50))
#this requires a google cloud bucket for the data dir path, but the same problem happens in MNIST as well

with strategy.scope():
  model=create_model()
  model.compile(
        optimizer=tf.keras.optimizers.Adam(),
        loss="sparse_categorical_crossentropy",
        metrics=["sparse_categorical_accuracy"])

model.fit(train_ds,epochs=15,steps_per_epoch=200)

Produces this error
InternalError: Cache should only be read after it has been completed.
Additional GRPC error information:
{"created":"@1572919336.377239490","description":"Error received from peer","file":"external/grpc/src/core/lib/surface/call.cc","file_line":1039,"grpc_message":"Cache should only be read after it has been completed.","grpc_status":13} [Op:MultiDeviceIteratorInit]

The environment is a Colab notebook with python 3.6 and TPU accelerator.
The problem disappears if the code is switched to TF 1.x and training runs well.

I'm experiencing the same issue.
both suggestions by darcula1993 and sbl1996 dont help
A minimal reproduction code:

%tensorflow_version 2.x
#must use tf 1.x to use TPU properly
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
import tensorflow_datasets as tfds
import os

resolver = tf.distribute.cluster_resolver.TPUClusterResolver(tpu='grpc://' + os.environ['COLAB_TPU_ADDR'])
tf.config.experimental_connect_to_cluster(resolver)
tf.tpu.experimental.initialize_tpu_system(resolver)
strategy = tf.distribute.experimental.TPUStrategy(resolver)

#constants
IMG_HEIGHT=IMG_WIDTH=200
BATCH_SIZE=128

def create_model():
  model = tf.keras.models.Sequential()
  model.add(tf.keras.layers.BatchNormalization(input_shape=(IMG_HEIGHT,IMG_WIDTH,1)))
  model.add(tf.keras.layers.Conv2D(64, (3, 3), activation='elu'))
  model.add(tf.keras.layers.MaxPooling2D(2))
  model.add(tf.keras.layers.Dropout(0.25))

  model.add(tf.keras.layers.BatchNormalization())
  model.add(tf.keras.layers.Conv2D(64, (3, 3), activation='elu'))
  model.add(tf.keras.layers.MaxPooling2D(2))
  model.add(tf.keras.layers.Dropout(0.25))

  model.add(tf.keras.layers.BatchNormalization())
  model.add(tf.keras.layers.Conv2D(64, (5, 5), activation='elu'))
  model.add(tf.keras.layers.MaxPooling2D(2))
  model.add(tf.keras.layers.Dropout(0.25))

  model.add(tf.keras.layers.BatchNormalization())
  model.add(tf.keras.layers.Conv2D(128, (3, 3),  activation='elu'))
  model.add(tf.keras.layers.MaxPooling2D(2))
  model.add(tf.keras.layers.Dropout(0.25))

  model.add(tf.keras.layers.BatchNormalization())
  model.add(tf.keras.layers.Conv2D(256, (3, 3),  activation='elu'))
  #model.add(tf.keras.layers.MaxPooling2D(2))
  model.add(tf.keras.layers.Dropout(0.25))

  model.add(tf.keras.layers.BatchNormalization())
  model.add(tf.keras.layers.Conv2D(512, (3, 3),  activation='elu'))
  model.add(tf.keras.layers.MaxPooling2D(2))
  model.add(tf.keras.layers.Dropout(0.25))

  model.add(tf.keras.layers.Flatten())
  model.add(tf.keras.layers.Dense(256))
  model.add(tf.keras.layers.Activation('elu'))
  model.add(tf.keras.layers.Dropout(0.5))
  model.add(tf.keras.layers.Dense(10))
  model.add(tf.keras.layers.Activation('softmax'))
  return model

@tf.function
def convert(image,label):
  return (tf.image.convert_image_dtype(image, tf.float32),tf.expand_dims(tf.cast(label,tf.float32),0))
@tf.function
def resize(image,label):
  return (tf.image.resize(image,(IMG_HEIGHT,IMG_WIDTH)),label)

test_split, valid_split, train_split = tfds.Split.TRAIN.subsplit([10, 10, 80])
train_ds = (tfds.load("mnist", split=train_split, as_supervised=True, try_gcs=True)
  .map(convert)
  .map(resize)
  .batch(BATCH_SIZE).take(144).cache().repeat().prefetch(50))
#if the .cache() is removed the issue disappears

with strategy.scope():
  model=create_model()
  model.compile(
        optimizer=tf.keras.optimizers.Adam(),
        loss="sparse_categorical_crossentropy",
        metrics=["sparse_categorical_accuracy"])

model.fit(train_ds,epochs=15,steps_per_epoch=200)

Produces this error
InternalError: Cache should only be read after it has been completed.
Additional GRPC error information:
{"created":"@1572919336.377239490","description":"Error received from peer","file":"external/grpc/src/core/lib/surface/call.cc","file_line":1039,"grpc_message":"Cache should only be read after it has been completed.","grpc_status":13} [Op:MultiDeviceIteratorInit]

The environment is a Colab notebook with python 3.6 and TPU accelerator.
TF version:v2.0.0-rc2-26-g64c3d38 2.0.0
The problem disappears if the code is switched to TF 1.x and training runs well.

try catche first then map?

Can you try with TF 2.1? I believe this issue should have been fixed by https://github.com/tensorflow/tensorflow/commit/08f41c6216d177933ba8eb48cd171a1e004e6ca2

Closing this issue since it's resolved. Feel free to reopen if still have problems. Thanks!


Set Up SAP Business Application Studio for Development

Tutorial URL: https://developers.sap.com/tutorials/appstudio-onboarding.html
Hi,
I'm a UX designer for SCP Cockpit and currently testing various tutorials.
The tutorial Set Up SAP Business Application Studio for Development includes sections were the user has to work in the subscriptions page.
Soon the marketplace will change and services and subscriptions will be moved to one page. You can read more about this topic here: https://jtrack.wdf.sap.corp/browse/SAPCPCFS-18270?src=confmacro
I just wanted to inform you as a heads up, in case you were not aware of this upcoming change :)
Thanks and best regards,
Olga

@raz-korn Please note the changes from @OlgaWerner . I will close the issue -- if you need it open, let me know.
@OlgaWerner  Please note this is a public forum, in case it was not clear.


test: Remove spammy "Cilium DaemonSet not ready yet" logs

For each Cilium installation, Cilium DaemonSet not ready yet messages are logged once per second until Cilium is ready. Given we will already have an explicit message in case of timeout while waiting for Cilium to be ready, those messages are unnecessary.
Fixes: #14384

test-me-please

test-me-please

All team reviews are covered and CI is green. Merging.

All team reviews are covered and CI is green. Merging.


Error target gi-crystal failed to compile

Describe the bug
gi-crystal failed to compile because of missing dependencies that I have no idea how to install:
Error target gi-crystal failed to compile:
/nix/store/frriydwnf7v3dpayy5a6ki00qsp95iiy-binutils-2.38/bin/ld: cannot find -lgirepository-1.0 (this usually means you need to install the development package for libgirepository-1.0): No such file or directory
/nix/store/frriydwnf7v3dpayy5a6ki00qsp95iiy-binutils-2.38/bin/ld: cannot find -lglib-2.0 (this usually means you need to install the development package for libglib-2.0): No such file or directory
/nix/store/frriydwnf7v3dpayy5a6ki00qsp95iiy-binutils-2.38/bin/ld: cannot find -lgobject-2.0 (this usually means you need to install the development package for libgobject-2.0): No such file or directory
clang-10: error: linker command failed with exit code 1 (use -v to see invocation)
Error: execution of command failed with code: 1: `cc "${@}" -o /home/annaaurora/projects/Collision/lib/gi-crystal/bin/gi-crystal  -rdynamic -L/nix/store/firv3vzakvzg0qf1frxyxdjxpgsxslll-boehm-gc-8.0.6/lib -L/nix/store/cf720cm79g30in8klyd19mzbfh81xvlq-libatomic_ops-7.6.12/lib -L/nix/store/mmbj9as03r27jwa7qg0qvkdvp9xabngm-pcre-8.45/lib -L/nix/store/alvnhmybxvc251sz90zaid0l1xz907fk-libevent-2.1.12/lib -L/nix/store/585y3cdw8sv9xrl1krb2i4md21bnw1fi-libyaml-0.2.5/lib -L/nix/store/nbd9kijlxi8ppm70g1m85j7z31kbpqjx-zlib-1.2.12/lib -L/nix/store/c6wcf1ikq9l776yhcmfjrrbivc8n8paa-libxml2-2.9.14/lib -L/nix/store/mmrv9z6b5mf0b93izhizc4j0wnnb17hn-openssl-1.1.1q/lib -lxml2 -lgirepository-1.0 -lglib-2.0 -lgobject-2.0 -lyaml -lpcre -lm -lgc -lpthread -levent -lrt -ldl`

To Reproduce
Steps to reproduce the behavior:

shards install

Expected behavior
Alls shards build and install.
Environment:

OS: NixOS
Install method: shards

Additional context
I have a suspiscion that this is a NixOS problem. I wanted to shards install to get the libadwaita bindings for packaging Collision for nixpkgs.

Thanks for raising this issue!
I'm not familiar with nix however from the error, it seems that girepository, glib and gobject are not available. Since those depend on the environment (gi-crystal is the binding generator), I suppose this guide on packaging GNOME apps might come in handy. Also taking a look at other libadwaita nix packages might be helpful!
See: nixpkgs/pika-backup & Onto wrapGAppsHook
Oh openssl is also needed for calculating the hashes (it should be buildInputs = [ openssl ]; (?))
Some other notes on packaging:

Please take a look at the Makefile for the build commands and configuration options.
You can set some locations using env vars just like it's done in the Makefile.
Collision uses GSettings for keeping track of the window size and maximized state between restarts. Package maintainers can disable GSettings by passing -Ddisable_gschema. The "packaging GNOME apps" nix guide has a section for GSettings.
Collision is currently fully tested on x86_64-linux.

Let me know if there's anything I can do from my side! I can also add a nix target on the Makefile if it makes maintaining it easier!

See: nixpkgs/pika-backup & Onto wrapGAppsHook

yeah I forgot wrapGAppsHook

I took a look at some of the .nix files for other programs with wrapGAppsHook and libadwaita but it doesn't help.

I still have no idea how to install lgirepository, libglib and libgobject. I can't find the three of them in any package manager.

I also don't know how to use the bindings when I have them.

I solved shards install failing by installing gobject-introspection which provides the libraries. it was even mentioned on https://github.com/GeopJr/libadwaita.cr, sorry…

But there still are some error messages:
shards install
Resolving dependencies
Fetching https://github.com/geopjr/libadwaita.cr.git
Fetching https://github.com/geopjr/gettext.cr.git
Fetching https://github.com/geopjr/non-blocking-spawn.git
Fetching https://github.com/hugopl/gtk4.cr.git
Fetching https://github.com/hugopl/gi-crystal.git
Fetching https://github.com/hugopl/version_from_shard.git
Using version_from_shard (1.2.5)
Installing gi-crystal (0.14.0)
Postinstall of gi-crystal: shards build
Installing gtk4 (0.12.0)
Installing libadwaita (1.0.0 at 72f2e42)
Installing non-blocking-spawn (1.0.5)
Installing gettext (1.0.0)
Shard "gi-crystal" may be incompatible with Crystal 1.2.2
Shard "gtk4" may be incompatible with Crystal 1.2.2
Shard "non-blocking-spawn" may be incompatible with Crystal 1.2.2
Shard "gettext" may be incompatible with Crystal 1.2.2

and
./bin/gi-crystal
info - Starting at 2022-10-10 20:57:59 +02:00, project dir: /home/annaaurora/projects/Collision
info - Generating bindings at /home/annaaurora/projects/Collision/lib/gi-crystal/src/auto
info - Using binding config at /home/annaaurora/projects/Collision/lib/gi-crystal/src/bindings/g_lib/binding.yml
info - Using binding config at /home/annaaurora/projects/Collision/lib/gi-crystal/src/bindings/g_object/binding.yml
info - Using binding config at /home/annaaurora/projects/Collision/lib/gtk4/src/bindings/gdk/binding.yml
info - Using binding config at /home/annaaurora/projects/Collision/lib/gtk4/src/bindings/gio/binding.yml
info - Using binding config at /home/annaaurora/projects/Collision/lib/gtk4/src/bindings/gsk/binding.yml
info - Using binding config at /home/annaaurora/projects/Collision/lib/gtk4/src/bindings/gtk/binding.yml
info - Using binding config at /home/annaaurora/projects/Collision/lib/gtk4/src/bindings/harfbuzz/binding.yml
info - Using binding config at /home/annaaurora/projects/Collision/lib/gtk4/src/bindings/pango/binding.yml
info - Using binding config at /home/annaaurora/projects/Collision/lib/libadwaita/src/bindings/binding.yml
fatal - Typelib file for namespace 'Gdk', version '4.0' not found

All these dependencies (gobject-introspection, glib, gdk) should have been provided by wrapGAppsHook, right?
It also mentions There is also [wrapGAppsHook4]{#ssec-gnome-hooks-wrapgappshook4}, which replaces GTK 3 with GTK 4.

maybe you need to up the crystal version?

Collision already "requires" (more like suggest) Crystal 1.6.0 but anything above what the shards require should work. Crystal version has to be bumped in nix (seems to be blocked https://github.com/NixOS/nixpkgs/pull/173928).
You can try with 1.2.2, it should still work as expected!

You can try with 1.2.2, it should still work as expected!

Also the binding generation?

Probably. (The above error is on the environment missing Gdk - not the binding generator).
I'm currently trying to fix the nix crystal package so 1.6.0 gets in, you can wait for that I guess. (But still 1.2.2 should still probably work)

It doesn't work. non-blocking-spawn requires >= 1.3.2, < 2.0.0

thanks for trying to update the crystal package

It doesn't work. non-blocking-spawn requires >= 1.3.2, < 2.0.0

Try passing --ignore-crystal-version on shards install, if that doesn't work, I can go change the shard requirements as that mine.

gettext also requires 1.3.2

Also mine, it should work on 1.2.2.

Not sure if it's a good idea for you to set down the requirements. Do your programs have no issues with lower versions?

I think we should wait for the crystal nixpkgs update instead of trying to make this fit.

I agree on waiting, however they should still work. There haven't been that many breaking changes >= 1.0.0. The only reason these shards (including the ones I maintain) have that requirement is that the crystal tool that initializes a new project automatically sets it to the current one.


Loading the same url into different views simultaneously

I have to update several image views with the same url, when I get an update event. The code does  something like:
imageLoader.loadImage(url, targetSize, opt, new SimpleImageLoadingListener() {
    public void onLoadingComplete(String url, View view, Bitmap loadedImage) {
        ... some accounting goes here ...
        view.setImageBitmap(bitmap);
    }
    public void onLoadingCancelled(String url, View view) {
        Log.w("Loader", "onLoadingCancelled");
    }
})

This is called with the same url on different views. As a result, none of the views gets updated - onLoadingCancelled is called on all instances.
If I add to the url a random argument (url + "&xxx=" + rnd()), everything goes as planned. I suspect a caching problem, but can't be sure.

I traced the problem down to the way isViewReused() is implemented. It calls engine.getLoadingUriForView(imageAware) to get the cache key. This depends on the imageAware's id, which is derived from the uri (for NonViewAware) or the view's hashCode (for ViewAware).
The problem with loadImage (contrary to displayImage) is that it uses the same id for different load tasks on different views, causing a caching clash.
One solution is to use displayImage instead, but that's not exactly what I want. Another solution would be to add a unique [optional] "taskId" to the loadImage method, and to add it to the NonViewAware


replace new_like with wrap_like

Throughout this comment I'm using Image as proxy for all of our features for simplicity

This is my take on reducing the overhead transforms v2 has. Currently, we are using the idiom
https://github.com/pytorch/vision/blob/7eb5d7fcab73afec976907a855d9e63fa31f5579/torchvision/prototype/features/_image.py#L136
everywhere to wrap a plain tensor into the image feature. Doing so results in multiple __torch_function__ calls as detailed in #6681. Similar to the constructor, the Image.new_like method accepts arbitrary data: Any as input and thus has to go through the constructor every time.
However, we never call it without a tensor input. Plus, whenever we pass dtype to Image.new_like, it is not to change the dtype of the tensor to be wrapped, but rather to retain it:
https://github.com/pytorch/vision/blob/7eb5d7fcab73afec976907a855d9e63fa31f5579/torchvision/prototype/features/_bounding_box.py#L158
Taking this one step further, this also means that the new_like name is somewhat misleading. Yes, one gets a new features.Image object, but unlike the torch.*_like methods, we don't get a new storage unless the dtype or device is changed.
This PR proposed to fix the above by refactoring Image.new_like to Image.wrap_like. Opposed to new_like, wrap_like only takes a tensor to be wrapped as well the metadata for the specific type, i.e. color_space for features.Image. This prevents the need to go through the constructor and results in no __torch_function__ calls at all:
import unittest.mock

import torch
from torchvision.prototype import features

image = features.Image(torch.rand(3, 16, 16))

with unittest.mock.patch(
    "torchvision.prototype.features._feature._Feature.__torch_function__", side_effect=AssertionError
):
    # This has to be `.new_like` on `main` and `.wrap_like` on the PR
    features.Image.wrap_like(image, torch.rand(3, 16, 16))

We can estimate the impact of this change on one classification training:
from time import perf_counter_ns

import torch
from torchvision.prototype import features

# @datumbox, @vfdev-5: please let me know if these assumptions don't reflect reality
# This comes from @vfdev-5's benchmarks
num_calls_per_sample = 20
# Number of samples in imagenet training set
num_samples_per_epoch = 1_200_000
num_epochs = 600
# The wrapping happens in the transforms pipeline, i.e. on each worker individually.
# Thus, each worker only has a fraction of samples to process
num_processes = 8

input = features.Image(torch.rand(3, 512, 512))
output = torch.rand(3, 512, 512)

time_diffs = []
for _ in range(1000):
    time_diff_per_sample = 0
    for _ in range(num_calls_per_sample):
        start = perf_counter_ns()
        # This has to be `.new_like` on `main` and `.wrap_like` on the PR
        features.Image.wrap_like(input, output)
        stop = perf_counter_ns()
        time_diff_per_sample += stop - start
    time_diffs.append(time_diff_per_sample)

overhead_per_sample = float(torch.tensor(time_diffs).to(torch.float64).median()) * 1e-9
print(f"Overhead per sample: {overhead_per_sample*1e6:5.1f} µs")

estimated_overhead_per_training = overhead_per_sample * num_samples_per_epoch * num_epochs / num_processes
print(f"Estimated overhead per training: {estimated_overhead_per_training / 60 / 60:.1f} h")

Overhead per sample:  21.2 µs
Estimated overhead per training: 0.5 h

Although the overhead is quite low with roughly 20 µs per sample or 1 µs per call, the enormous amount of calls during a full training blows this up to a significant increase. However, running the same benchmark on main yields
Overhead per sample: 208.3 µs
Estimated overhead per training: 5.2 h

To put it in words, this PR achieves roughly a 10x reduction of the overhead. And the only thing we lose is the ability to pass arbitrary data to the wrapping function or change the dtype and device in the process. Both of which we don't do and I currently don't see a use case for it either.
Note that this doesn't affect the ability to pass arbitrary data to the constructor. This is still supported. Plus, in contrast to the proposed wrap_like function, the constructor may also process the metadata, like guessing the color_space if none is passed to features.Image, while wrap_like only takes the correct type or takes the value from the reference.

As discussed offline, there are multiple ways we can approach the interface design. Nothing is set in stone here. We'll move with what I have proposed with the strong possibility of refactoring later. The performance gain is too high to hold this up with bike shedding.


frida.core.RPCException: Error: access violation accessing 0x89 while running on an iPhone 7 iOS 13.5.1

I'm trying to run toothpicker on my iPhone 7 running iOS 13.5.1, I used "symbols_ios_13_5". I'm assuming the symbols are the issue as maybe 13.5 symbols aren't compatible with 13.5.1. How would I go about extracting the symbols from 13.5.1?

Dear @xyn,
indeed, the symbols change in every iOS version, no matter if minor or major, since all daemons get recompiled. Moreover, there are different versions depending on the architecture, i.e., the the bluetoothd on pe-A12 has different symbols than on A12+.
@nezza is currently working on ToothPicker :) He diffed the symbols for iOS 14.3 on an iPhone 7/8/X. Note that the symbols as pasted here are unconfirmed, so not sure if they work or not.
// iOS 14.3, A11
    symbols_ios_14_3_iphonex: {
        allocateACLConnection: 0xed3a0,
        allocateLEConnection: 0xed74c,
        OI_SignalMan_Recv: 0x136828,
        OI_L2CAP_Recv: 0x12da74,
        bt_forceDisconnect: 0xd23d8,
        ACL_reception_handler: 0xf2b8c,
        OI_HCI_ReleaseConnection: 0xed9e0,
        create_connection: 0x147630,
        _GATT_LE_DisconnectedCB: 0x140568,
        ReadRemoteVersionInformationCB: 0x14d6cc,
        hci_handle_exists: 0xecffc,
        LE_ReadRemoteVersionInformationComplete: 0x148744,
        OI_LP_ConnectionAdded: 0x119c8c,
        btstack_free: 0x79f28,
        startSecurityPolicyEnforcement: 0x181334,
        enforceLinkPolicy: 0x181a34,
        registerTimeout: 0x17f51c,
        ble_adv_stuff: 0x441888,
        coreDumpPacketCounter: 0x31a800,
        OI_L2CAP_WriteMBUF: 0x115988,
        is_internal_build: 0x78b7c,
    },

He used the Ghida versioning tool. I prefer BinDiff for IDA Pro. Either way, the workflow is to import an older bluetoothd version extracted from an IPSW file and then diff it against your current version.
Instead of getting ToothPicker running on iOS 13.5.1, I would recommend upgrading your iPhone 7 (if it is a 7 and not a newer model) to iOS 14.3.

Dear @xyn,
indeed, the symbols change in every iOS version, no matter if minor or major, since all daemons get recompiled. Moreover, there are different versions depending on the architecture, i.e., the the bluetoothd on pe-A12 has different symbols than on A12+.
@nezza is currently working on ToothPicker :) He diffed the symbols for iOS 14.3 on an iPhone 7/8/X. Note that the symbols as pasted here are unconfirmed, so not sure if they work or not.
// iOS 14.3, A11
    symbols_ios_14_3_iphonex: {
        allocateACLConnection: 0xed3a0,
        allocateLEConnection: 0xed74c,
        OI_SignalMan_Recv: 0x136828,
        OI_L2CAP_Recv: 0x12da74,
        bt_forceDisconnect: 0xd23d8,
        ACL_reception_handler: 0xf2b8c,
        OI_HCI_ReleaseConnection: 0xed9e0,
        create_connection: 0x147630,
        _GATT_LE_DisconnectedCB: 0x140568,
        ReadRemoteVersionInformationCB: 0x14d6cc,
        hci_handle_exists: 0xecffc,
        LE_ReadRemoteVersionInformationComplete: 0x148744,
        OI_LP_ConnectionAdded: 0x119c8c,
        btstack_free: 0x79f28,
        startSecurityPolicyEnforcement: 0x181334,
        enforceLinkPolicy: 0x181a34,
        registerTimeout: 0x17f51c,
        ble_adv_stuff: 0x441888,
        coreDumpPacketCounter: 0x31a800,
        OI_L2CAP_WriteMBUF: 0x115988,
        is_internal_build: 0x78b7c,
    },

He used the Ghida versioning tool. I prefer BinDiff for IDA Pro. Either way, the workflow is to import an older bluetoothd version extracted from an IPSW file and then diff it against your current version.
Instead of getting ToothPicker running on iOS 13.5.1, I would recommend upgrading your iPhone 7 (if it is a 7 and not a newer model) to iOS 14.3.

Using these addresses I'm getting the following error "frida.core.RPCException: Error: abort was called"
This is the whole crash log: https://paste.ubuntu.com/p/MzqWXFmycy/

Using these addresses I'm getting the following error "frida.core.RPCException: Error: abort was called"
This is the whole crash log: https://paste.ubuntu.com/p/MzqWXFmycy/

Looks like some issue with the script or symbols again. Which iOS and Frida version are you running?

Looks like some issue with the script or symbols again. Which iOS and Frida version are you running?

I am running iOS 14.3, iPhone 7 and the latest version of Frida installed from http://build.frida.re(I installed Frida for Pre A12 devices)

I am running iOS 14.3, iPhone 7 and the latest version of Frida installed from http://build.frida.re(I installed Frida for Pre A12 devices)

(I had restored from 13.5.1 to 14.3)

(I had restored from 13.5.1 to 14.3)

@jiska2342 any fix to xyn's issue ?

@jiska2342 any fix to xyn's issue ?

I will look into the issue this weekend, haven't had the chance to upgrade to 14.3 yet.

I will look into the issue this weekend, haven't had the chance to upgrade to 14.3 yet.

It seems to work for me. I'm using an iPhone 7 on iOS 14.3 using the symbols @jiska2342 provided above.
Did you add these symbols to the symbols.js, adapted bluetoothd.js to use these symbols, and compiled the harness script again? It seems to crash immediately at the connection allocation. Maybe the wrong address is called.

It seems to work for me. I'm using an iPhone 7 on iOS 14.3 using the symbols @jiska2342 provided above.
Did you add these symbols to the symbols.js, adapted bluetoothd.js to use these symbols, and compiled the harness script again? It seems to crash immediately at the connection allocation. Maybe the wrong address is called.

thx again @ttdennis spoke with xyn he and i work together and seems all working fine :) sorry for late answer tho.

thx again @ttdennis spoke with xyn he and i work together and seems all working fine :) sorry for late answer tho.


UI bug with AdColony framework

Hi,
I noticed that when the app is linked against the  AdColony framework, there is a ui bug in the TSMessage.

To reproduce, just add the AdColony pod and run the sample app
pod 'AdColony', '~> 2.5'

cheers

I'm seeing this too!


Add issue template to tell people about #89

A lot of issues get created that are duplicates of #89. We should consider creating an issue template telling people about the rate limiting issues that links to #89.

I agree 👍

Fixed in 58aaa9289b0e59f35d36a7841483a49e48a7b367


[3.2 and 4.0] Using DBHTMLText::HTMLATT() gives unexpected results.

Ideally these functions should be wrapped on DBHTMLText so that it strips the HTML tags. If I convert HTML to an attribute, I expect it to just work, and not have to do something like this in a template:
$Content.NoHTML.HTMLATT

Why should HTMLATT strip tags? What if you want to encode your html into a data-* attribute, and have this rendered by javascript? I think we have different ideas of the purpose of this code. :)
Your example is precisely what I would expect to do if I wanted to first strip html characters, and then encode for ATT properties (although $Content.NoHTML.ATT would be fine too).

You're absolutely right. I didn't consider storing HTML in a data-* attribute. (Despite the fact that I do this!)


Update Makefile to use clang++

easyinstall.sh has been updated in PR #971 to install clang++. The Makefile should be updated to use clang by default instead of gcc.
Note: I don't think there is any need to go back to gcc, so I think it can be a one-way change.
Ideally, the makefile will still allow for cross-compilation on a x86 system for the ARM platform.

Please see my comment regarding code metrics in https://github.com/akuker/RASCSI/issues/968. Before updating the Makeifile pleease ensure that everything else is still functional. It would be bad to have no code coverage metrics and/or code analysis anymore.

Is this ticket still needed?


Add missing postinst script

Bug Report
The following lines ...
https://github.com/irods/irods_capability_indexing/blob/82eee54b7433fdb51df43da8776d962b82185147/CMakeLists.txt#L114-L115
lead to the following output because the postinst script does not exist.
CPack Warning: Adding file to tar:
#top level directory: /home/kory/dev/github/irods_capability_indexing_build/_CPack_Packages/Linux/DEB/irods_capability-indexing-<IP_ADDRESS>-Linux/document-type
#missing file: /home/kory/dev/github/irods_capability_indexing/packaging/postinst
CPack Warning: Adding file to tar:
#top level directory: /home/kory/dev/github/irods_capability_indexing_build/_CPack_Packages/Linux/DEB/irods_capability-indexing-<IP_ADDRESS>-Linux/elasticsearch
#missing file: /home/kory/dev/github/irods_capability_indexing/packaging/postinst

Considering other iRODS repos contain that script, we should add it.

The references to the postinst script are not needed and should be removed.
See https://github.com/irods/irods_capability_indexing/pull/131#issuecomment-1957827183.

Related to #108.


Pass through devServer options through to dev middleware.

I want to be able to set headers on the webpack dev server, and use other options from the devServer config header to adjust how the dev middleware behaves.  https://github.com/nuxt/nuxt.js/issues/762 is solved by this mechanism (I think, anyway).

w00t, thanks pi0!


IsarError: Could not initialize IsarCore library

On Some devices (Google Pixel 3a(Snapdragon 670)), it is working perfectly fine. But on some devices (Example: Samsung Galaxy A10(Exynos 7884)) it shows this error:
Unhandled Exception: IsarError: Could not initialize IsarCore library. If you create a Flutter app, make sure to add isar_flutter_libs to your dependencies: Invalid argument(s): Failed to load dynamic library 'libisar.so': dlopen failed: cannot locate symbol "__emutls_get_address" referenced by "/data/app/.......==/lib/arm/libisar.so"...
Version

Platform: Android
Flutter version: 3.0.1
Isar version: 2.5.0
Isar Generator version: 2.5.0

I think it's the same issue with 32 bit devices(#281), a galaxy A10 should 64 bit, but it seems that it runs on 32 bit mode (refer to this discussion : https://android.stackexchange.com/questions/225314/is-the-cpu-of-samsung-galaxy-a10s-64-bit-or-32-bit), you can try upgrading to isar 3.0.0 and see if it fixes the issue

I think it's the same issue with 32 bit devices(#281), a galaxy A10 should 64 bit, but it seems that it runs on 32 bit mode (refer to this discussion : https://android.stackexchange.com/questions/225314/is-the-cpu-of-samsung-galaxy-a10s-64-bit-or-32-bit), you can try upgrading to isar 3.0.0 and see if it fixes the issue

Isar 3.0.0 is not stable yet.

I think you have no other choice. I am using Isar 3.0.0 dev in production right now, if you look at the generated files you will notice that there aren't many changes, and there are no breaking changes to the core API's.

I think it's the same issue with 32 bit devices(#281), a galaxy A10 should 64 bit, but it seems that it runs on 32 bit mode (refer to this discussion : https://android.stackexchange.com/questions/225314/is-the-cpu-of-samsung-galaxy-a10s-64-bit-or-32-bit), you can try upgrading to isar 3.0.0 and see if it fixes the issue

I have same issue with Isar 2.5.0 in 32bit devices(Motorola XT1626, Android 7.0), after upgrade to Isar 3.0.0 i solved my issue.

Awesome, thanks for confirming @rodevapp


Trying to download from Xfinity/Comcast for AETV

[x] I've verified and I assure that I'm running youtube-dl 2017.11.15
[x] At least skimmed through the README, most notably the FAQ and BUGS sections
[x] Searched the bugtracker for similar issues including closed ones

What is the purpose of your issue?

[x] Bug report (encountered problems with youtube-dl)

I know some people have had this issue in the past? I'm not sure how to fix it. I am on Windows running the latest version. I downloaded the first 3 episodes fine.. because they didn't require a login/pass.
[debug] System config: []
[debug] User config: []
[debug] Custom config: []
[debug] Command-line args: ['-F', '--ap-mso=Comcast_SSO', '--ap-username=PRIVATE', '--ap-password=PRIVATE', '-v', 'http://www.aetv.com/shows/shipping-wars/season-1/episode-4']
[debug] Encodings: locale cp1252, fs mbcs, out cp437, pref cp1252
[debug] youtube-dl version 2017.11.15
[debug] Python version 3.4.4 - Windows-10-10.0.15063
[debug] exe versions: rtmpdump 2.3
[debug] Proxy map: {}
[aenetworks] shipping-wars/season-1/episode-4: Downloading webpage
[aenetworks] 17165811: Downloading JSON metadata
[aenetworks] 17165811: Downloading Provider Redirect Page
ERROR: Unable to extract post url; please report this issue on https://yt-dl.org/bug . Make sure you are using the latest version; type  youtube-dl -U  to update. Be sure to call youtube-dl with the --verbose flag and include its complete output.
Traceback (most recent call last):
File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\rg3\tmp10f7prtw\build\youtube_dl\YoutubeDL.py", line 784, in extract_info
File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\rg3\tmp10f7prtw\build\youtube_dl\extractor\common.py", line 437, in extract
File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\rg3\tmp10f7prtw\build\youtube_dl\extractor\aenetworks.py", line 143, in _real_extract
File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\rg3\tmp10f7prtw\build\youtube_dl\extractor\adobepass.py", line 1448, in _extract_mvpd_auth
File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\rg3\tmp10f7prtw\build\youtube_dl\extractor\adobepass.py", line 1360, in post_form
File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\rg3\tmp10f7prtw\build\youtube_dl\extractor\common.py", line 809, in _html_search_regex
File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\rg3\tmp10f7prtw\build\youtube_dl\extractor\common.py", line 800, in _search_regex
youtube_dl.utils.RegexNotFoundError: Unable to extract post url; please report this issue on https://yt-dl.org/bug . Make sure you are using the latest version; type  youtube-dl -U  to update. Be sure to call youtube-dl with the --verbose flag and include its complete output.

I have sent you an email with a user/pass.


Not working with Alfresco 5.0 d

Hi,
is this extension supported on Alfresco Community 5.0.0 d, version Number: 5.0.0 (d r99759-b2). I've downloaded and tested downloadable installation bundle from the Alfresco website.
In Alfresco WAR is see:
alfresco-5.0.d$ java -jar ./bin/alfresco-mmt.jar list ./tomcat/webapps/alfresco.war
Module 'com.github.dynamicextensionsalfresco' installed in './tomcat/webapps/alfresco.war'

Title:        Dynamic Extensions for Alfresco
Version:      1.4.0
Install Date: Wed Sep 30 23:09:05 CEST 2015
Description:   Dynamic Extensions for Alfresco module package

But URL http://localhost:8080/alfresco/service/dynamic-extensions/ gives HTTP 404, also this extension can not be found on webscripts list.
Do you have any idea why this would not work? I use vanilla Alfresco Community download bundle, from https://www.alfresco.com/alfresco-community-download. I am using Ubuntu Linux 14.04 LTS.

Hi,
5.0.d is certainly supported. I did a quick check with a vanilla install and DE 1.4 and everything is working as expected.
Are you sure you added the trailing slash to the url?
http://localhost:8080/alfresco/service/dynamic-extensions/
and not
http://localhost:8080/alfresco/service/dynamic-extensions
You can set the DE log level via the tomcat/webapps/alfresco/WEB-INF/classes/alfresco/module/com.github.dynamicextensionsalfresco/log4j.properties file to DEBUG and then check your alfresco.log file or post it here.


Android app not found

Hi!
I've noticed android app disappeared in google play store. I need it. Your app is the best among other MQTT dashboards. Can you please upload it anywhere?

If you search for "ru.esp8266.iotmanager" you'll find an APK from 2017, v1.55. I won't link it here because it's not clear why the app disappeared. I installed and seems pretty cool.

v2.0 https://play.google.com/store/apps/details?id=ru.esp8266.iotmanager


Fix several minor typos

Description
Several minor typos in the getting started docs.
Checklist:

[X] I've made sure that tests/test_cookiecutter_generation.py is updated accordingly (especially if adding or updating a template option)
[X] I've updated the documentation or confirm that my change doesn't require any updates

Rationale
Just cleans up docs.

@keithcallenberg good catch. thank you 🚢 :shipit:


Rename TerminationCriteria

StopAfter would read well, and convenience constructors would help it read even smoother. Eg:
islandManager.run(StopAfter.duration(1.second))

or
islandManager.run(StopAfter.pointIsDominated(Map(
      "ObjectiveA" -> 100,
      "ObjectiveB" -> 777,
      …)

Please check #64, where I introduced the required renaming.


[darknet, openmama, gherkin-c, libevent] Conflicts when installing headers

The following header conflics occur when trying to install these libraries in the presence of each other.

Header file
Conflicting Ports

include/list.h
darknet & openmama

include/parser.h
darknet & gherkin-c

include/event.h
gherkin-c & libevent

Due to user expectation, we wan't to preserve upstream include paths as much as possible.
However, when these file conflicts happen, a decision must be made by the vcpkg team on which library will be "blessed" by our CI tests.
For example, in the case of libevent, due to it's long history, it takes precedence in claiming ownership of include/event.h.
The logical solution would be to move the installation path to these packages to their own subfolders, e.g.: include/darknet/list.h, include/openmama/list.h. And the easiest way to do this, would be doing this within the portfile. However, the right way would be to submit a request for these changes to be made upstream.

@cenit would it be OK to move darknet's headers to their own subfolder, or would this break too many consuming projects?

I think it’s feasible. Let me try it upstream. It should be quick.
Darknet doesn’t have a long history used as a library, especially in c++ (most users exploit the Python bindings). For a long time the source code of the executable itself was hacked and adapted to requirements, so I don’t see a huge uproar from this request

Is it correct that vcpkg integrate only adds the vcpkg header base directory?
In this case. Does the CI test also include an check over all headers that verifies that #incudes are reachable either from this base directory or from the local header directory? Because sometimes I need to fix paths. The problem is that this shows up only during usage. E.g in magnum port a couple of days ago (some bullet integration and Khronos headers)

https://github.com/microsoft/vcpkg/issues/6532

#6532

with #6000 it should be relatively easy to move LibLZMA, just changing the
set(INSTALL_INCLUDE_DIR  "include"            CACHE PATH   "Path where headers will be installed")

with
set(INSTALL_INCLUDE_DIR  "include/lzma"     CACHE PATH   "Path where headers will be installed")

gherkin-c is currently disabled in the CI tests, and darknet have moved into its headers into its own sub-directory.  I am closing the issue as resolved (although there are other ports not listed in this issue that still conflict)


Moving from OkHttpClient to Apache HttpClient

Move from the current OkHttpClient to Apache HttpClient, and use a single instance of it across, rather than creating a new instance every time.
One proposal is, wherever the OkHttpClient is used, say in HttpNodeDataSource, dataSink and so on, use a container class called, HttpExecutor and create this HttpExecutor right in the RangerHttpClient and AbstractRangerHttpHubClient respectively, from their start methods.
Keeps the interfaces clean and changes minimal and testable.

The new HttpComponents interface is similar to what you are saying .. ithink it will significantly clean up the code. Looking fwd to this...

@pranithk is picking it up.


Davy edits

@zzuziak

I uploaded complete solutions to the two quizzes
Fixed some typos

@krokrob  we removed the solutions from this repo so that students can't access them, right? :thinking:

@krokrob @zzuziak  then we could create a repo data-quizzes-solution :) ?

@davydw can you remove solutions from this PR so I can merge the fixes in the empty notebooks?

@zzuziak  I removed the solutions from this PR :)

:tada:


Build and publish a Dockerfile based on a binderhub fork (using chartpress)

The binderhub software needs to run in a container, and we need to define that. We also need to use a fork to trial an "no launch" out-out feature to be upstreamed to the BinderHub python package's REST API.
I've created most of this already, but its not published to quay.io etc yet and not using the fork.

Note that this is part of a https://github.com/2i2c-org/binderhub-service/milestone/1 with a time estimate.

Success, see https://quay.io/repository/2i2c/binderhub-service


Node Material Editor: Fix automatic creation of inputs for "sourceY" …

…and "sourceZ"
Fix #13761

Please make sure to label your PR with "bug", "new feature" or "breaking change" label(s).
To prevent this PR from going to the changelog marked it with the "skip changelog" label.

Snapshot stored with reference name:
refs/pull/13773/merge
Test environment:
https://babylonsnapshots.z22.web.core.windows.net/refs/pull/13773/merge/index.html
To test a playground add it to the URL, for example:
https://babylonsnapshots.z22.web.core.windows.net/refs/pull/13773/merge/index.html#WGZLGJ#4600
Links to test babylon tools with this snapshot:
https://playground.babylonjs.com/?snapshot=refs/pull/13773/merge
https://sandbox.babylonjs.com/?snapshot=refs/pull/13773/merge
https://gui.babylonjs.com/?snapshot=refs/pull/13773/merge
https://nme.babylonjs.com/?snapshot=refs/pull/13773/merge
To test the snapshot in the playground with a playground ID add it after the snapshot query string:
https://playground.babylonjs.com/?snapshot=refs/pull/13773/merge#BCU1XR#0


RBAC using JWT

Hi everyone,
I'm following KrakenD documentation in order to implement a working example of forcing requests to provide a token issued by a third party.
https://www.krakend.io/docs/authorization/jwt-validation/
My main issue is that I have to set every role that a given protected resource allows by using "roles_key" and "roles" keys:

roles_key: When passing roles, the key name inside the JWT payload specifying the role of the user.
roles: list. When set, the JWT token not having at least one of the listed roles are rejected.

Is there any way to set this roles dynamically by using a properties file or an external configuration file? I'm asking this because it would give the opportunity to change access policies using an UI or any given service.
Thanks in advance.

hi @limadelrey, welcome to the KrakenD community!
the KrakenD does not reload its configuration after starting (#166).
if you want to avoid repetitions or managing complex configurations in a single file, you can use the flexibleconfig module. https://www.krakend.io/docs/configuration/flexible-config/
Cheers!

Thank you @kpacha.


failed inheritance in python after adding subclass attribute to pyclass

Bug Description
I have an example of a pyo3 subclass failing to be inherited from in Python.  I tried using subclass in a pyclass in https://github.com/NREL/fastsim (can grant access to this private repo if needed), and when I tried:
import fastsimrust as fsr
import fastsim as fsim
class ChildVehicle(fsr.RustVehicle):
    def get_veh_kg(self) -> float:
        return self.veh_kg

veh = ChildVehicle.from_file(str(fsim.package_root() / 'resources/vehdb/2012_Ford_Fusion.yaml'))

veh.get_veh_kg()

this happened:
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In [12], line 7
      3         return self.veh_kg
      5 veh = ChildVehicle.from_file(str(fsim.package_root() / 'resources/vehdb/2012_Ford_Fusion.yaml'))
----> 7 veh.get_veh_kg()

AttributeError: 'fastsimrust.RustVehicle' object has no attribute 'get_veh_kg'

Note that on the Rust side, we use a proc macro to add the pyo3 attributes so it'll look a little wonky to anyone who looks into the Rust code.
@birkenfeld

Steps to Reproduce

Give me your github user name so I can give you access to https://github.com/NREL/fastsim.
Clone and install by following the instructions in fastsim/fastsim/docs/README.md
run this code

import fastsimrust as fsr
import fastsim as fsim
class ChildVehicle(fsr.RustVehicle):
    def get_veh_kg(self) -> float:
        return self.veh_kg

veh = ChildVehicle.from_file(str(fsim.package_root() / 'resources/vehdb/2012_Ford_Fusion.yaml'))

veh.get_veh_kg()

Backtrace
python
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In [12], line 7
      3         return self.veh_kg
      5 veh = ChildVehicle.from_file(str(fsim.package_root() / 'resources/vehdb/2012_Ford_Fusion.yaml'))
----> 7 veh.get_veh_kg()

AttributeError: 'fastsimrust.RustVehicle' object has no attribute 'get_veh_kg'

### Your operating system and version

Windows 10

### Your Python version (`python --version`)

3.10.6

### Your Rust version (`rustc --version`)

1.64.0

### Your PyO3 version

0.17.2

### How did you install python? Did you use a virtualenv?

python.org installer

yes, using the command `python -m venv fastsim-venv` in the project folder, and `fastsim-venv` is in `.gitignore`.

### Additional Info

_No response_

Thanks for making a new issue.
Can you share the code of RustVehicle::from_file? It is probably a static/class method that returns an instance of RustVehicle, so it has no idea about ChildVehicle.
It would instead have to be a class method that creates an instance of the class passed to it (which might be a bit involved due to the Rust/Python interface).

@birkenfeld ,
pub fn from_file(filename: &str) -> Result<Self, anyhow::Error> {
    let extension = Path::new(filename)
        .extension()
        .and_then(OsStr::to_str)
        .unwrap_or("");

    let file = File::open(filename)?;
    let mut veh_res: Result<RustVehicle, anyhow::Error> = match extension {
        "yaml" => Ok(serde_yaml::from_reader(file)?),
        "json" => Ok(serde_json::from_reader(file)?),
        _ => Err(anyhow!("Unsupported file extension {}", extension)),
    };
    veh_res.as_mut().unwrap().set_derived();
    veh_res
}

I can understand how this didn't magically do what I expected.  It's not clear to me that what I had planned to do is worth doing.  I feel like there should be something in the documentation, which I'm happy to write up, making it clear that this inheritance won't work like it would in pure python.

What I could probably do to get the behavior I want is have a subclass from_file method that calls the parent class from_file method, iterates through the attributes (python equivalent of fields) of the instantiated parent class and assigns the values to identical fields in the instantiated child class, and then returns the child class instance which can have (still have not tested this out) attributes/fields and/or methods that are only in the child class.
@birkenfeld , does this sound like it'd work?  If yes, I'll test it out, and if it works, I'll close this issue.  I'll also write up a simple example that demonstrates the concepts mentioned above that can go in the docs.

You're looking for a #[classmethod] - something along the lines of
#[classmethod]
pub fn from_file(cls: &PyType, filename: &str) -> PyResult<Py<Self>> {
    let instance = cls.call(( /* your args tuple */, /* your kwargs dict */)?
    instance.extract() // cast the &PyAny to Py<Self> to ensure this is a subclass as expected - can make a better error message
}

@davidhewitt , interesting!  Let me try to wrap my mind around that, test it out, and then I'll report back.  It may be a few days.

I feel like there should be something in the documentation, which I'm happy to write up, making it clear that this inheritance won't work like it would in pure python.

@davidhewitt has already given the proper solution using @classmethod. I just want to stress that what you were showing would not work in pure Python either. It is equivalent to:
class RustVehicle:
    def __init__(self, some_param):
        ...

    def from_file(filename):
        return RustVehicle(...)

class PythonVehicle(RustVehicle):
    def get_veh_kg(self):
        return ...

veh = PythonVehicle.from_file("file")
print(veh.get_veh_kg())

gives the same exception:
Traceback (most recent call last):
  File "test.py", line 13, in <module>
    print(veh.get_veh_kg())
AttributeError: 'RustVehicle' object has no attribute 'get_veh_kg'

@birkenfeld , I'm pretty sure it would work with:
from typing_extensions import Self

class RustVehicle:
    def __init__(self, some_param):
        ...

    def from_file(filename):
        return Self(...)

class PythonVehicle(RustVehicle):
    def get_veh_kg(self):
        return ...

veh = PythonVehicle.from_file("file")
print(veh.get_veh_kg())

Is there anything left to keep this open?

I think this can be closed, thanks for handling 👍


[WIP] Windows compatibility

This will address https://github.com/googlefonts/noto-emoji/issues/43

[x] Add glyf table (+ empty glyphs, and loca table)
[x] Add cmap format 4 table
[x] Add new binary to codebase
[x] Produce both versions when running make (was: Create flag to add cmap/glyf or not)

Deleting this WIP in favor of the finished version: https://github.com/googlefonts/noto-emoji/pull/323


[question]update typescript to 4.2.x, An import path cannot end with '.ts' ?

when i upgrade typescript from 4.1.5 to 4.3.2, my progrom cannot build.

the error info：  An import path cannot end with a '.ts' extension. Consider importing<EMAIL_ADDRESS>instead.

version 4.1.5 is ok。Is it not allowed to use .ts extention after 4.2.x?
my tsconfig.json:
{
  "compilerOptions": {
    "target": "es2019",
    "module": "esnext",
    "moduleResolution": "node",
    "forceConsistentCasingInFileNames": true,
    "jsx": "preserve",
    "incremental": true,
    "isolatedModules": true,
    "strict": true,
    "resolveJsonModule": true,
    "importHelpers": true,
    "esModuleInterop": true,
    "allowSyntheticDefaultImports": true,
    "sourceMap": true,
    "skipLibCheck": true,
    "noUnusedLocals": false,
    "types": [
      "webpack-env",
      "jest"
    ],
    "lib": [
      "esnext",
      "dom",
      "dom.iterable",
      "scripthost"
    ]
  },
  "includes": ["../shared/**/**"],
  "exclude": [
    "node_modules"
  ]
}

See #38149, and note that this repository is not suited for questions. You should ask on StackOverflow instead.


Syntax for unit

The new "unit" type from the canonical ABI is implemented as the keyword unit, but we may also wish to consider using the () syntax for the unit type. This also relates to https://github.com/bytecodealliance/wit-bindgen/issues/216 and https://github.com/WebAssembly/component-model/issues/21, however.

The unit type is now removed, so I'm going to close this.


fix installation issue that readiness-timeout flag is not honored.

resolve: https://github.com/istio/istio/issues/30221
[ ] Configuration Infrastructure
[ ] Docs
[ X ] Installation
[ ] Networking
[ ] Performance and Scalability
[ ] Policies and Telemetry
[ ] Security
[ ] Test and Release
[ ] User Experience
[ ] Developer Infrastructure
Pull Request Attributes
Please check any characteristics that apply to this pull request.
[ ] Does not have any changes that may affect Istio users.

In response to a cherrypick label: new pull request created: #30323

In response to a cherrypick label: new pull request created: #30323


Add firebase manager

https://github.com/complexorganizations/firestore-manager

@Prajwal-Koirala if you add the proper .opensource/project.json file to your repo I'd be happy to add your project!

added

Added your project! It should show up on the site within 24 hours.

Thank you my good sir.
@samtstern


Proper handling of next

We should handle next according to dialect.
Saying (in )1 week and next week produces the same result in parse_datetime, but most tools and humans would understand it differently:
next week in task managers for example is typically interpreted as the beginning of next week, which should be equivalent to Monday then.
Also, if today on a Thursday I write next Thursday, it selects the Thursday in a fortnight (Uk Dialect if that matters), which is odd in my opinion.

And I just realized that unlike its predecessor, interim can handle this monday - but I would interpret that as the monday in this week, which today would be the 12.8., but it produces the coming Monday 19.8.

According to chatgpt:
The phrase "this Monday" can have slightly different interpretations based on the context of the current day of the week when you say it. Here is a detailed explanation:

1. **Early in the Week (Sunday or Saturday):**
   - If today is **Saturday** or **Sunday**, "this Monday" usually refers to the upcoming Monday.

   For example, if today is Sunday, October 8, 2023, and you say "this Monday," it typically means Monday, October 9, 2023.

2. **On Monday Itself:**
   - If today is **Monday**, "this Monday" usually refers to the current day.

   For example, if today is Monday, October 9, 2023, and you say "this Monday," it means the current day, October 9, 2023.

3. **Later in the Week (Tuesday to Friday):**
   - If today is **Tuesday**, **Wednesday**, **Thursday**, or **Friday**, "this Monday" usually refers to the Monday that has just passed, earlier in the same week.

   For example, if today is Wednesday, October 11, 2023, and you say "this Monday," it typically means Monday, October 9, 2023.

To summarize:

- **Sunday or Saturday**: "This Monday" refers to the upcoming Monday.
- **Monday**: "This Monday" refers to the current day.
- **Tuesday to Friday**: "This Monday" refers to the Monday earlier in the same week.

The context in which the phrase is used can often clarify its meaning, but these are the general conventions.

What is definitely wrong is that this thursday today on a thursday is interpreted as the coming thursday.


When send message to new number first time it shows single tick

When send message to new number first time it shows single tick on our side and Show "Waiting for this message. This may take a while" on receiver side.
Please provide solution at the earliest.

Okay, i'll apply a hotfix asap

After checking, this seems to only happen when the app is outdated. Try updating the whatsapp app then try again.

i have checked app is updated still has this issue. i have downgraded it to baileys version 4.1.0. the problem is resolved.
But issue is still there when you use latest version of baileys.

Any update?

Any update?

Sorry, i got really busy recently. I'll definitely do it when i have the time.

any update?

@aarvee022 Chill, please don't bump all the issues since it spammed my notifications. I'm currently working on a custom baileys store and will be focused on this first.
On other hand, i do realize that my codes on this repo is kinda hard to maintain, so i'll probably rewrite things while also solving all the issues.
So please be more patient, i'm definitely giving my best on this.

I still have error with this, is there any fix ?


If line highlighting is on then get exception if caret is outside of viewport

I'm getting the following exception:
java.util.NoSuchElementException: No value present
        at java.base/java.util.Optional.get(Optional.java:148)
        at org.fxmisc.flowless.CellListManager.getPresentCell(CellListManager.java:65)
        at org.fxmisc.flowless.CellPositioner.getVisibleCell(CellPositioner.java:33)
        at org.fxmisc.flowless.Navigator.distanceFromGround(Navigator.java:373)
        at org.fxmisc.flowless.Navigator.fillViewportFrom(Navigator.java:333)
        at org.fxmisc.flowless.Navigator.visit(Navigator.java:131)
        at org.fxmisc.flowless.StartOffStart.accept(TargetPosition.java:85)
        at org.fxmisc.flowless.Navigator.layoutChildren(Navigator.java:80)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1206)
        at org.fxmisc.flowless.VirtualFlow.layoutChildren(VirtualFlow.java:257)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1206)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1213)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1213)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1213)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1213)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1213)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1213)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1213)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1213)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1213)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1213)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1213)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1213)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1213)
        at javafx.graphics/javafx.scene.Parent.layout(Parent.java:1213)
        at javafx.graphics/javafx.scene.Scene.doLayoutPass(Scene.java:576)
        at javafx.graphics/javafx.scene.Scene$ScenePulseListener.pulse(Scene.java:2482)

This occurs when I first create the area, wrapped in a VirtualizedScrollPane, and setLineHighlightingOn is set to true before any text is added to the area.  If I then add text that is rendered larger than the viewport height (i.e. by having a high font size) then I get the exception above.   I'm not calling area.requestFollowCaret so I don't think that's the cause.  If I don't have the line highlighting switched on then I don't get the exception for the same text/font size.

Hi Gary, I can't seem to replicate this issue. Can you please supply a simple demo program that reliably produces the exception.

I'll see if I can.  My code has ballooned in size now that it's nearing completion.

So doing some more detailed tests I think the issue actually lies with the layout of the viewport.  If the caret is on the last line of the viewport and I press "Enter" then a new line is added (new paragraph) but the caret is not positioned at the bottom of the viewport, you can still scroll down a few pixels.  This is at a font size of 12pt.  If you increase the font size, say to 40pt and then repeat the process, only about a third of the caret is visible and most of the new line is actually outside of the viewport.
I tried to get a picture of this but I haven't found a way to set the blink rate of the caret, doing area.getCaretSelectionBind().setBlinkRate doesn't seem to be working.
However I've added a picture with the writing line highlighted.

In the image above, I had the caret on the last line of the viewport, I pressed "Enter" and the caret moved down but the viewport didn't scroll fully to make the line fully visible.  You can see the small gap at the bottom of the vertical scrollbar on the right.
The image below shows the last line fully scrolled into view (I moved it manually)

If the text area is empty and I press enter repeatedly then the first line that moves below the bottom of the viewport is fine but the second new line at the bottom of the viewport shows the problem.
A further issue that I'll mention here rather than creating a new issue is that if the caret is at the start of the line and I press "Del" on my keyboard rather than "Backspace" then the writing line highlight will often disappear until I press another key.

Okay, so I was able to replicate the incomplete line problem you described above and have submitted a PR to fix it.
Also experienced the "Del" line highlighting issue, and will have a look at that tomorrow.
Still haven't encountered the NoSuchElementException though ?  Can you please verify the fix I've submitted so far and if you still encounter the Exception.

The PR fixes the incomplete line problem, thanks.  I'm still getting the NoSuchElementException, I'm currently trying to create a reproducible example.
I have a few other issues with the line highlighter though.  I have a reproducible example for those, essentially just do:
StyleClassedTextArea area = new StyleClassedTextArea ();
area.setLineHighlighterOn (true);
area.setWrapText (true);
try {
  area.insert (0, new String (Files.readAllBytes (Paths.get ("ipsum.txt")), StandardCharsets.UTF_8), "text");
} catch (Exception e) { e.printStackTrace (); }
VirtualizedScrollPane<StyleClassedTextArea> vsPane = new VirtualizedScrollPane<>(area);
VBox vbox = new VBox();
VBox.setVgrow(vsPane, Priority.ALWAYS);
vbox.getChildren().addAll(vsPane);
Scene scene = new Scene(vbox, 600, 400);
s.setScene (scene);
s.show ();

I've attached the ipsum.txt file, it just contains a large amount of lorem ipsum text.
ipsum.txt
If setWrapText is true then the line highlight (scroll to the bottom of the area) is a line above the caret.
If setWrapText is false then the line highlight behaves strangely and will often be on the line above the caret.  Also if you scroll the area horizontally the highlight won't stretch the entire length of the area, it seems to be a fixed width equal to the width of the viewport.

The "lorem ipsum" problem has been fixed (in above PR) as well as an NPE problem I encountered along the way (in another PR). Could you please try the current "snapshot" out and see if you still get the NoSuchElementException ..... thanks.

Yes those fixes seem to solve the NPE issue and the NoSuchElementException, at least I now don't see it when I try to reproduce the circumstances.  Thanks.


CFG view doesn't work with binary output

It seems like the output is missing edges between basic blocks.
To repro:

reset ui
load "maxArray" example
open CFG view
toggle binary mode

Closed by Chedy's PR


Fixed issue #6349

Issue Reference
#6349

@akathuria289
Not working, please run the given command:
npm run prod


feat(stdlib): implement ArrayGrid component

Change Summary
This implements the <ArrayGrid> component.
I wasn't sure how much of the logic we wanted to add initially, vs. just having a skeleton ArrayGrid that could be instantiated in BrightScript. It seems like most of the special logic would come from the contentNode field; however, nodes as fields are not yet supported in brs, so we can't do too much with it yet.
Let me know what you think!

I wasn't sure how much of the logic we wanted to add initially

I think getting the skeleton up to unblock general loading across an app as you've done makes more sense.  We can implement the details if users ever need this functionality in tests (which may be never).


Increase ngrok version to 3.2.3

Increase ngrok version to 3.2.3 in order to prevent timeout. See here: https://github.com/stripe/stripe-payments-demo/issues/82

Thanks a mill for flagging this! I've updated the version in a separate PR[0] to also commit the package lock file. Therefore closing this one.
[0] https://github.com/stripe/stripe-payments-demo/pull/88


Error when entering an incorrect 2FA code

If you enter an incorrect 2FA code you get this error. Entering the correct code and everything works.
NodeBB v1.16.2.
Internal Error.
Oops! Looks like something went wrong!
/login/2fa
Cannot read property 'startsWith' of undefined

Should be fixed in the latest version of 2factor.

v2.9.5


Build(deps-dev): Bump eslint-plugin-react-hooks from 4.5.0 to 4.6.0 (#3643)

Pull request opened by the merge tool on behalf of #3643

Merged in 07db6aae1967c447f9f409090f32613b38a859de