Issue with running demo data

Hello!
I just installed pyapetnet on our server following the official instruction, and confirms that it is successful. However, when I tried the demo data (both DICOM and NIFTI), I got the following error. I wonder whether you have any suggestions on how to solve this issue? Thank you!
Traceback (most recent call last):
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/bin/pyapetnet_predict_from_dicom", line 8, in
sys.exit(main())
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/pyapetnet/predict_from_dicom.py", line 168, in main
pred = model.predict(x).squeeze()
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 70, in error_handler
raise e.with_traceback(filtered_tb) from None
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/tensorflow/python/eager/execute.py", line 52, in quick_execute
tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.InvalidArgumentError: Graph execution error:
Detected at node 'functional_3/functional_1/batchnorm_ind_0_1/FusedBatchNormV3_2' defined at (most recent call last):
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/bin/pyapetnet_predict_from_dicom", line 8, in
sys.exit(main())
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/pyapetnet/predict_from_dicom.py", line 168, in main
pred = model.predict(x).squeeze()
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/engine/training.py", line 2350, in predict
tmp_batch_outputs = self.predict_function(iterator)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/engine/training.py", line 2137, in predict_function
return step_function(self, iterator)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/engine/training.py", line 2123, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/engine/training.py", line 2111, in run_step
outputs = model.predict_step(data)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/engine/training.py", line 2079, in predict_step
return self(x, training=False)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/engine/training.py", line 561, in call
return super().call(*args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/engine/base_layer.py", line 1132, in call
outputs = call_fn(inputs, *args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 96, in error_handler
return fn(*args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/engine/functional.py", line 511, in call
return self._run_internal_graph(inputs, training=training, mask=mask)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/engine/functional.py", line 668, in _run_internal_graph
outputs = node.layer(*args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/engine/training.py", line 561, in call
return super().call(*args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/engine/base_layer.py", line 1132, in call
outputs = call_fn(inputs, *args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 96, in error_handler
return fn(*args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/engine/functional.py", line 511, in call
return self._run_internal_graph(inputs, training=training, mask=mask)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/engine/functional.py", line 668, in _run_internal_graph
outputs = node.layer(*args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/engine/base_layer.py", line 1132, in call
outputs = call_fn(inputs, *args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 96, in error_handler
return fn(*args, **kwargs)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/layers/normalization/batch_normalization.py", line 866, in call
outputs = self._fused_batch_norm(inputs, training=training)
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/layers/normalization/batch_normalization.py", line 659, in _fused_batch_norm
output, mean, variance = control_flow_util.smart_cond(
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/utils/control_flow_util.py", line 108, in smart_cond
return tf.internal.smart_cond.smart_cond(
File "/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/layers/normalization/batch_normalization.py", line 648, in _fused_batch_norm_inference
return tf.compat.v1.nn.fused_batch_norm(
Node: 'functional_3/functional_1/batchnorm_ind_0_1/FusedBatchNormV3_2'
scale must have the same number of elements as the channels of x, got 15 and 1
[[{{node functional_3/functional_1/batchnorm_ind_0_1/FusedBatchNormV3_2}}]] [Op:__inference_predict_function_14243]

Hi,
thanks for reporting this issue.
Can you report the following to debug the issue:

what operating system are you using?
can you execute conda list in your conda env, such that I can see the installed package versions?
(it could be an issue with a new keras/tensorflow version)
can you send the exact call that you used to predict from the test data?

Hi Georg,
Thank you for your prompt response! Please see the information below:

My operating system is Ubuntu 20.04.2.
conda list returns:

Name                    Version                   Build  Channel
_libgcc_mutex             0.1                        main
_openmp_mutex             5.1                       1_gnu
absl-py                   1.4.0                    pypi_0    pypi
astunparse                1.6.3                    pypi_0    pypi
bzip2                     1.0.8                h7b6447c_0
ca-certificates           2023.01.10           h06a4308_0
cachetools                5.3.0                    pypi_0    pypi
certifi                   2022.12.7       py310h06a4308_0
charset-normalizer        3.0.1                    pypi_0    pypi
contourpy                 1.0.7                    pypi_0    pypi
cycler                    0.11.0                   pypi_0    pypi
flatbuffers               23.1.21                  pypi_0    pypi
fonttools                 4.38.0                   pypi_0    pypi
gast                      0.4.0                    pypi_0    pypi
google-auth               2.16.0                   pypi_0    pypi
google-auth-oauthlib      0.4.6                    pypi_0    pypi
google-pasta              0.2.0                    pypi_0    pypi
grpcio                    1.51.1                   pypi_0    pypi
h5py                      3.8.0                    pypi_0    pypi
idna                      3.4                      pypi_0    pypi
imageio                   2.25.0                   pypi_0    pypi
keras                     2.11.0                   pypi_0    pypi
kiwisolver                1.4.4                    pypi_0    pypi
ld_impl_linux-64          2.38                 h1181459_1
libclang                  <IP_ADDRESS>                 pypi_0    pypi
libffi                    3.4.2                h6a678d5_6
libgcc-ng                 11.2.0               h1234567_1
libgomp                   11.2.0               h1234567_1
libstdcxx-ng              11.2.0               h1234567_1
libuuid                   1.41.5               h5eee18b_0
llvmlite                  0.39.1                   pypi_0    pypi
markdown                  3.4.1                    pypi_0    pypi
markupsafe                2.1.2                    pypi_0    pypi
matplotlib                3.6.3                    pypi_0    pypi
ncurses                   6.3                  h5eee18b_3
networkx                  3.0                      pypi_0    pypi
nibabel                   5.0.0                    pypi_0    pypi
numba                     0.56.4                   pypi_0    pypi
numpy                     1.23.5                   pypi_0    pypi
oauthlib                  3.2.2                    pypi_0    pypi
openssl                   1.1.1s               h7f8727e_0
opt-einsum                3.3.0                    pypi_0    pypi
packaging                 23.0                     pypi_0    pypi
pillow                    9.4.0                    pypi_0    pypi
pip                       22.3.1          py310h06a4308_0
protobuf                  3.19.6                   pypi_0    pypi
pyapetnet                 1.5.1                    pypi_0    pypi
pyasn1                    0.4.8                    pypi_0    pypi
pyasn1-modules            0.2.8                    pypi_0    pypi
pydicom                   2.3.1                    pypi_0    pypi
pymirc                    0.28                     pypi_0    pypi
pyparsing                 3.0.9                    pypi_0    pypi
python                    3.10.9               h7a1cb2a_0
python-dateutil           2.8.2                    pypi_0    pypi
pywavelets                1.4.1                    pypi_0    pypi
readline                  8.2                  h5eee18b_0
requests                  2.28.2                   pypi_0    pypi
requests-oauthlib         1.3.1                    pypi_0    pypi
rsa                       4.9                      pypi_0    pypi
scikit-image              0.19.3                   pypi_0    pypi
scipy                     1.10.0                   pypi_0    pypi
setuptools                65.6.3          py310h06a4308_0
simpleitk                 2.2.1                    pypi_0    pypi
six                       1.16.0                   pypi_0    pypi
sqlite                    3.40.1               h5082296_0
tensorboard               2.11.2                   pypi_0    pypi
tensorboard-data-server   0.6.1                    pypi_0    pypi
tensorboard-plugin-wit    1.8.1                    pypi_0    pypi
tensorflow                2.11.0                   pypi_0    pypi
tensorflow-estimator      2.11.0                   pypi_0    pypi
tensorflow-io-gcs-filesystem 0.30.0                   pypi_0    pypi
termcolor                 2.2.0                    pypi_0    pypi
tifffile                  2<IP_ADDRESS>              pypi_0    pypi
tk                        8.6.12               h1ccaba5_0
typing-extensions         4.4.0                    pypi_0    pypi
tzdata                    2022g                h04d1e81_0
urllib3                   1.26.14                  pypi_0    pypi
werkzeug                  2.2.2                    pypi_0    pypi
wheel                     0.37.1             pyhd3eb1b0_0
wrapt                     1.14.1                   pypi_0    pypi
xz                        5.2.10               h5eee18b_1
zlib                      1.2.13               h5eee18b_0

When running the prediction code, I also got the following warnings before the error message. Not sure whether this is relevant (maybe indeed keras/tf version issue as you suggested?), but just for your reference.

2023-01-25 13:33:22.396931: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F AVX512_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-01-25 13:33:22.523543: I tensorflow/core/util/port.cc:104] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable TF_ENABLE_ONEDNN_OPTS=0.
2023-01-25 13:33:26.200905: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
2023-01-25 13:33:26.201042: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
2023-01-25 13:33:26.201060: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
WARNING:tensorflow:SavedModel saved prior to TF 2.5 detected when loading Keras model. Please ensure that you are saving the model with model.save() or tf.keras.models.save_model(), NOT tf.saved_model.save(). To confirm, there should be a file named "keras_metadata.pb" in the SavedModel directory.
2023-01-25 13:33:33.319327: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudnn.so.8'; dlerror: libcudnn.so.8: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
2023-01-25 13:33:33.319363: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1934] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2023-01-25 13:33:33.319929: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F AVX512_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/keras/layers/core/lambda_layer.py:324: UserWarning: tensorflow.python.keras.utils.multi_gpu_utils is not loaded, but a Lambda layer uses it. It may cause errors.
function = cls._parse_function_from_config(
/bmr207/nmrgrp/nmr175/.conda/envs/pyapetnet/lib/python3.10/site-packages/pymirc/fileio/read_dicom.py:134: UserWarning: Cannot find SeriesType in first dicom header. Setting it to ('STATIC', 'IMAGE')
warnings.warn(f'Cannot find SeriesType in first dicom header. Setting it to {fallback_series_type}')

The line I called is pyapetnet_predict_from_dicom ./brainweb_06_osem_dcm/ ./brainweb_06_t1_dcm/ S2_osem_b10_fdg_pe2i --show as suggested. (already cd to the data folder).

On a separate note, is there any required/recommended CUDA version for this tool? My understanding is that the prediction part use CPU so it does not matter much, but we are planning to try to retrain this model with additional data.
Thank you!

I just tried myself on my local Ubuntu 20.04 system with CUDA. Installation and also the test predictions worked :/
(same tensorflow version 2.11 got installed.)
From the error messages that you posted, I think your tensorflow installtion is not happy with your CUDA installation
(It complains about many missing cuda libraries). Not sure though if this is the issue.

To test if it is indeed related to problems with tensorflow + CUDA, can you:

remove your pyapetnet conda env again: conda remove -n pyapetnet --all
create a new empty env: conda create pyapetpnet + conda activate pyapetnet
Install tensorflow following the official guide here: https://www.tensorflow.org/install/pip
Install pyapetnet: pip installpyapetnet

In the official guide, the matching cuda-toolkit version (11.2) and cudnn version (8.1) get installed in your conda env.

Thank you! I will test it and let you know. May I ask what CUDA driver version you are current using? (if checking with nvidia-smi).

In my test I used CUDA version 12 and driver version 525.78.01.
So probably not optimal (maybe I should also stick to the official tensorflow install instructions)

Thank you so much for the information!

Hi Georg,
I tried to install tf first following the official guide, but it still did not work. I then tried to install tf via conda despite not being recommended (conda install -c conda-forge tensorflow-gpu) first, then installed pyapetnet via pip, and it works! I am not sure why. Maybe conda just solves the compatibility issues better...
Anyway, I have one more question: how long does it take for you to run prediction on one demo case? It took me >1hr on a server with A100 GPU, which does not make sense to me.
Thanks again for your help!

(1) Glad that at least the installation works. Prediction of the demo case (even without using any GPU) should be less than one minute. If it takes >1h then there is sth severely wrong (but I have no clue what goes wrong).
If you "only" want to do predictions, you don't need any GPU. Can you maybe try to install tensorflow without GPU?
(2) Another option: Would it be an option for you to run the prediction from a docker container?
We have a docker file here:
https://github.com/gschramm/pyapetnet/blob/master/Dockerfile

Thank you so much for the information! We will try the options you recommended. Hopefully it will work as expected soon! I will close this issue for now.


Where is the 'zeus/version' file located?

I've noticed that this line throws an error when I run bundle exec rspec  in my local fork. I tried to find out where this is located, but failed. Can the line be removed?

The project Makefile has tasks to generate the version files. There are actually multiple tasks for this:
make go/zeusversion/zeusversion.go
make rubygem/lib/zeus/version.rb
make vagrant/lib/vagrant-zeus/version.rb

Generally when I'm testing a build, I populate the VERSION file with a testing build number (e.g. 0.15.5.rc1) and then generate the version files.


Branch or release for Swift 2.3

Hello!
My team uses Nimble-Snapshots in our Swift 2.2 product and FBSnapshotTestCase is one of it's dependencies. We want to be able to build our product with Xcode 8 and since upgrading our code base to Swift 3.0 will be a large task we have decided to first upgrade it to Swift 2.3.
Can you make a release or branch from commit b48e77e3397298baf1532a8e4f418197df2843c3 ? I strongly dislike pointing to a commit in Podfiles and having a separate branch for Swift 2.3 would make our Podfile less of a chore to deal with.

hmm, the code on master at the moment has code for both >3 and 2.3 doesn't this work for you guys?

It works but the moment you commit to master our application might break. I would sleep a lot better knowing that I'm pointing to a release in my Podfile.

I just cut a spec:

September 22nd, 10:24: Push for `FBSnapshotTestCase 2.1.3' initiated.
September 22nd, 10:24: Push for `FBSnapshotTestCase 2.1.3' has been pushed (0.38892521 s).

@parski why you weren't able to use the latest code of this library after Swift 3 branch was merged in? It uses #if swift(>=3) and it should have been working with both Swift 2.3 and Swift 3.0


feat: kong gateway add support for hcv approle auth method and approle dynamic auth path support

Description

This is a doc pr for the new feature in Kong Gateway 3.6 which adds support for Hashicorp Vault's Approle auth method as well as Approle dynamic auth path.
https://konghq.atlassian.net/browse/KAG-2891
Testing instructions
Preview link:
Checklist

[x] Review label added
[x] PR pointed to correct branch (main for immediate publishing, or a release branch: e.g. release/gateway-3.2, release/deck-1.17)

I committed some formatting changes in case anyone was still working on this, I haven't done the copy edit yet.


Blue and red objective states

As an alternative to putting the sticky objective markers on, WIBNI the objective markers had blue and red states to denote sticky control (or current control, as players see fit).

Added in 8b795be99ae108ae58f95792c57c4d3aa1340e54


Preselect Xinitrc and user

The only reason I want to use a login manager is to not type my username and after login to type startx. But I want my xinit get started (and I see you have a proper session to select for it).
So how to preselect a default user (me) and how to preselect xinitrc as the default launch session?

Ly will save the last user and desktop and load them back automatically by default. You can disable this by changing save to false in /etc/ly/config.ini: in this case the last saved login and desktop will be loaded but can't be changed by the user.


prodigal

[x] install program

[] run on real data

prodigal set up. full pipeline needs to be created.


Undefined behaviour in OP_DIV

Executing 1/0 invokes undefined behaviour (division by zero) in OP_DIV:
https://github.com/mruby/mruby/blob/52aafcd001095470ac1c397bdf83ce10e919c753/src/vm.c#L2356
This can be detected with clang's UndefinedBehaviorSanitizer: https://clang.llvm.org/docs/UndefinedBehaviorSanitizer.html
In MRI, this code raises a ZeroDivisionError.

It's defined behavior according to IEEE 754/IEC 60559. Also see: https://bugs.llvm.org/show_bug.cgi?id=19535

OK, feel free to close this issue if you don't think it's worth changing anything.
I see division by zero was discussed previously: https://github.com/mruby/mruby/issues/284, and it seems it was intentionally left as is.

Here the direct link as to what matz wrote 5 years ago at:
https://github.com/mruby/mruby/pull/285
"Thank you for the patch, but making Fixnum to behave like Float is a experiment I am doing on mruby for future Ruby spec. So I will fix #283 and #284 by other work around."
I think he mentioned mruby's different behaviour once in a presentation back then too, that the division behaviour will be different in other areas too, like 1/2 being 0.5 by default whereas main ruby will have 0..
With the merge of Fixnum and Bignum lateron in main ruby, and given that the comment was 5 years ago, perhaps matz could make a comment if anything has changed in the last 5 years in this regards, since it seems to be a recurring topic for some people like clayton here and back then Masaki Muranaka. :)

The policy explained in #285 has not been changed. So 1/0 should result +inf in mruby.
I am still not sure how to handle this "undefined behavior". Possible options are

leave it as it is
treat 0 especially and return +inf explicitly


switch-to-projects with multiple types of projects

What if in my solution I have 1 project that is .NET Standard and another project that is .NET Framework (that depends on .NET standard project)? switch-to-projects will not work then am I right?

I think it should work if all projects are sdk-style projects (i.e. use <PackageReference …> and not packages.config)

@RSuter I see, there isn't any straightforward way to convert old projects to new format though. Thanks for the answer.

Can you test with this pr? It adds support for legacy projects...
https://github.com/RSuter/DNT/pull/15


3.2.4 Release

Further improved support for Scala 3.
Bumped up to Scala 3.0.0-RC1.

@cheeseng any chance to include scala3 for scala.js?

@cheeseng any chance to include scala3 for scala.js?

The last time I tried there's an assertion error thrown from the scala-js compiler, so it does not seem like a straight forward thing.  We may try again with 3.0.0-RC1 though.

as far as I can see you're releasing support of 3.0.0-RC1 and Scala-Native 0.4.0 right now.
I guess it is worth to try to enable support Scala.js at Scala3.


The redefined macro ref and source not works

Hi team, I followed the advice, and still can't mock data and directly use database data,  did I missed sth?  my steps are:

redefine the ref, and source macros in the file: redifined_ref_source.sql.

{% macro ref(model_name) %}
   {{ return(dbt_unit_testing.ref(model_name)) }}
{% endmacro %}
{% macro source(source, model_name) %}
   {{ return(dbt_unit_testing.source(source, model_name)) }}
{% endmacro %}

in my intermediate layer  model:combine_category_and_project.sql. The way I use  remains :

with

    project as (select * from {{ ref("project") }}),

    catagory as (
        select project_id, category
        from {{ ref("catagory_source1") }}
        union
        select project_id, category
        from {{ ref("catagory_source2") }}
    ),

    result as (
        select project.*, catagory.category
        from project
        left join
            catagory
            on project.id = catagory.project_id
    )
select *
from result

then  I want to use mock data and test the logic of:combine_category_and_project.sql in test_combine_category_and_project, the way I use is :

-- depends_on: {{ ref('project') }}
-- depends_on: {{ ref('catagory_source1') }}
-- depends_on: {{ ref('catagory_source2') }}

{{ config(tags=['tag1']) }}

{% call dbt_unit_testing.test('combine_category_and_project', 'should map category') %}

    {% call dbt_unit_testing.mock_ref('project', {"input_format": "csv"}) %}
        id,name,display_name
        13,'aa','bb'
        18,'cc','dd'
    {% endcall %}

    {% call dbt_unit_testing.mock_ref('catagory_source1', {"input_format": "csv"}) %}
        project_id, category
        13,'category1'
    {% endcall %}

    {% call dbt_unit_testing.mock_ref('catagory_source2', {"input_format": "csv"}) %}
        project_id, category
        18,'category2'
    {% endcall %}

    {% call dbt_unit_testing.expect({"input_format": "csv"}) %}
        id,name,display_name,category
        13,'aa','bb','category1'
        18,'cc','dd','category2'
    {% endcall %}

{% endcall %}

If I remove the:
-- depends_on: {{ ref('project') }}
-- depends_on: {{ ref('catagory_source1') }}
-- depends_on: {{ ref('catagory_source2') }}

It will raise the compile error:To fix this, add the following hint to the top of the model
actually, I have mocked all of the depends in the file:test_combine_category_and_project .sql
what is the root cause of this?

Hi @GavinChowUp, it looks like you're missing the tag 'unit-test' in your test, as explained in the README.
Please let me know if this fixes your issue.
Thank you

Hi @psousa50 Thank you very much, I did not succeed in my mock because the unit-test was missed, thanks for providing such a useful framework. now the mock works.


ESP32 I2S breaks I2C, need I2S.start/stop

There's a long standing unresolved issue with I2C failing when running at the same time as I2S on the ESP32.
eg https://esp32.com/viewtopic.php?t=5563 and several others over the years
Admittedly this is an esp-idf issue, but I've found it can be worked around by turning off the I2S clocks while accessing I2C, which may not sound like a great general workaround, but works in my application.
These functions are available in esp-idf, but not exposed in the MP I2S driver.
Doing so is just a matter of adding a couple of stanzas, and modifying the machine_i2s_locals_dict_table eg
STATIC mp_obj_t machine_i2s_start(mp_obj_t self_in) {
    machine_i2s_obj_t *self = MP_OBJ_TO_PTR(self_in);
    i2s_start(self->port);
    return mp_const_none;
}
STATIC MP_DEFINE_CONST_FUN_OBJ_1(machine_i2s_start_obj, machine_i2s_start);

STATIC mp_obj_t machine_i2s_stop(mp_obj_t self_in) {
    machine_i2s_obj_t *self = MP_OBJ_TO_PTR(self_in);
    i2s_stop(self->port);
    return mp_const_none;
}
STATIC MP_DEFINE_CONST_FUN_OBJ_1(machine_i2s_stop_obj, machine_i2s_stop);

Would be great if this could be added to main library (would add this to MP issues, but Damien always seems so busy...)

Thanks for bringing this to my attention.  This is new to me.  I checked the ESP-IDF issues list on github -- this problem is not reported.
Before considering any changes to the MicroPython I2S API it is necessary to reproduce the problem.  Do you have time to find the minimum amount of MicroPython code that can reliably reproduce the problem?
thanks !

Hi Mike,
Yes, thats exactly the issue, it only really happens when driving the system hard with necessarily complex code.
I'm running an IMU at full tilt on I2C (1MHz bus , 2kHz * 48bits data) as well as using your code to get data from an ICS43434 MEMS mic @ 20kHz*32 bit, and I'm not sure I can distill this to a nugget.
All I can say is on a logic analyser , the difference between having the stop /start methods and not having them are dramatic.
Anyhow, I'm cool adding these changes in, so no worries

I think that gives me enough background to try and reproduce the failure.  I'm in the middle of adding I2S support to the MIMXRT port (e.g.  Teensy boards), so I won't be able to work on this for a while yet.
For a short-term workaround I wonder if using the deinit() method followed the init() method could substitute for start/stop?  Whatever samples that are remaining in the internal buffer would be wiped out with the deinit/init calls, but perhaps that is not important?

Hi Mike,
Yes init/deinit was the first thing I tried, but this didnt work in my app, which is actually  why I added the start/stop methods into your code.


Exposing enif_schedule_nif safely

enif_schedule_nif comes with a contract, much like enif_raise_exception. It's hard to support safely.
But we already support enif_raise_exception (see https://github.com/hansihe/rustler/blob/master/src/codegen_runtime.rs#L44 ). We could support enif_schedule_nif in the same way. Don't let the user call it directly, but let them return a special Rust value that means "call enif_schedule_nif safely for me".
There is one problem that we would need to solve, though. Currently, all NIFs have the return type NifResult<NifTerm<'a>>, allowing just two possibilities:

Ok(term): "return this term"
Err(exc): "raise this exception"

Now we want to add a third option, "schedule this nif". But we can't just change the return type, because that would break all existing code. I guess the way to do this is with a trait. Come to think of it, we should allow a wide variety of return types anyway, not just NifResult<NifTerm<'a>>; for example, anything that implements NifEncode should be just as good as a NifTerm, right?

Would it really be a bad thing to change the return type to add a Sched(...) option?  It obviously would break existing code trying to upgrade, but Rustler isn't at the magical "1.0" yet so there is a little more flexibility.

I think using a trait is better. The idea is that the user decides what the return type is, and Rustler figures out what to do with it.
So users may keep using NifResult<NifTerm> ... and write a new NIF that returns NifResult<NifSched> ... and write another new NIF that returns a Rust String, there's no reason Rustler couldn't handle all of them.

I don't know how readable this is, but here's the approach I took for a little Scheme implementation I've been messing around with: https://github.com/jorendorff/cell-gc/commit/149ce249bb4ac565783deeef9bcdbc502d061e5d
Before:
fn char_upcase<'h>(_hs: &mut GcHeapSession<'h>, args: Vec<Value<'h>>) -> Result<Trampoline<'h>> {
    if args.len() != 1 {
        return Err("char-upcase: 1 argument required".into());
    }
    let c = args[0].clone().as_char("char-upcase: character required")?;

    // I think the only character that doesn't upcase to a single character is
    // U+00DF LATIN SMALL LETTER SHARP S ('ß'). Guile returns it unchanged.
    // Fine with me.
    let mut up = c.to_uppercase();
    let result = match (up.next(), up.next()) {
        (Some(d), None) => d,
        _ => c,
    };

    Ok(Trampoline::Value(Value::Char(result)))
}

After:
builtins! {
    fn char_upcase "char-upcase" <'h>(_hs, c: char) -> char {
        // I think the only character that doesn't upcase to a single character is
        // U+00DF LATIN SMALL LETTER SHARP S ('ß'). Guile returns it unchanged.
        // Fine with me.
        let mut up = c.to_uppercase();
        match (up.next(), up.next()) {
            (Some(d), None) => d,
            _ => c,
        }
    }
}

This probably looks like it's solving a completely different problem. But if we can cope with return values like char, we can also cope with NifResult<NifTerm> vs. NifResult<NifSched> or whatever.

Of course I don't mean to propose any particular detail of that for Rustler. In particular, that builtins! macro syntax is silly. 🤡
I just wanted to show that something like this is possible. And the traits I used aren't much different from the NifEncode and NifDecode traits Rustler already has.

Requesting comments on an updated PR for this enhancement here: https://github.com/rusterlium/rustler/pull/232


Use of Swamp Expansion Biomes with Terraforged swamp Generation

Swamp Expansion adds more content to pre-existing swamps and adds new types, and the changes to swamps that normally occur with Swamp Expansion apply, but the new swamp types do not generate in Terraforged worlds.
Support for these new swamp types in Terraforged would be ideal, as it increases the variety.

SE doesn't mark its biomes with the 'overworld' BiomeType so TF won't use them.
You can read more about that here:
https://github.com/TerraForged/TerraForged/wiki/Mod:-Biomes
It's a relatively new marker so their developer(s) might not be aware of it. I'm sure they'd add it to their mod if you ask -  feel free to point them to the above link if it helps explain the problem/solution


convert for automatic1111

hello, thank you for your great work.
I wonder how (convert model) make it work in automatic1111 (img2img)
I try this code https://gist.github.com/jachiam/8a5c0b607e38fcc585168b90c686eb05 but its not work with FileNotFoundError: [Errno 2] No such file or directory: 'E:\pix2pix mod\v4d25\checkpoint-15000\unet\diffusion_pytorch_model.bin'
any way to make it like this file https://huggingface.co/timbrooks/instruct-pix2pix/blob/main/instruct-pix2pix-00-22000.safetensors
thanks again...

FileNotFoundError: [Errno 2] No such file or directory: 'E:\pix2pix mod\v4d25\checkpoint-15000\unet\diffusion_pytorch_model.bin'

Maybe provide the correct path?

FileNotFoundError: [Errno 2] No such file or directory: 'E:\pix2pix mod\v4d25\checkpoint-15000\unet\diffusion_pytorch_model.bin'

Maybe provide the correct path?

it show me it need diffusion_pytorch_model.bin  so I rename diffusion_pytorch_model.safetensors to .bin
then this what happened
Traceback (most recent call last):
File "C:\Users\GAMER\Desktop\New folder (6)\convert_diffusers_to_sd.py", line 216, in
unet_state_dict = torch.load(unet_path, map_location='cpu')
File "C:\Users\GAMER\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\serialization.py", line 986, in load
with _open_file_like(f, 'rb') as opened_file:
File "C:\Users\GAMER\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\serialization.py", line 435, in _open_file_like
return _open_file(name_or_buffer, mode)
File "C:\Users\GAMER\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\serialization.py", line 416, in init
super().init(open(name, mode))
FileNotFoundError: [Errno 2] No such file or directory: 'E:\pix2pix mod\v4d25\unet\diffusion_pytorch_model.bin'
C:\Users\GAMER\Desktop\New folder (6)>python convert_diffusers_to_sd.py --model_path "E:\pix2pix mod\v4d25" --checkpoint_path "C:\Users\GAMER\Desktop\New folder (6)\result\new.ckpt"
Traceback (most recent call last):
File "C:\Users\GAMER\Desktop\New folder (6)\convert_diffusers_to_sd.py", line 216, in
unet_state_dict = torch.load(unet_path, map_location='cpu')
File "C:\Users\GAMER\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\serialization.py", line 1028, in load
return _legacy_load(opened_file, map_location, pickle_module, **pickle_load_args)
File "C:\Users\GAMER\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\serialization.py", line 1246, in _legacy_load
magic_number = pickle_module.load(f, **pickle_load_args)
_pickle.UnpicklingError: invalid load key, '\xe0'.
I'm not sure if this the correct way to convert it

You cannot just be renaming a pickle file to have the safetensors extension. I would suggest making appropriate modifications to the conversion script for your needs.
Since this is not an issue directly to this repository, I am going to close this.


Reopening issue #1911

<select> elements open outside the application window. When opened a second time, they open in the correct position. The problem occurs again when moving the window to a new location.
Tauri info:
Operating System - Windows, version 10.0.19043 X64
Webview2 - 91.0.864.41

Node.js environment
  Node.js - 16.2.0
  @tauri-apps/cli - 1.0.0-beta.1 (outdated, latest: 1.0.0-beta.2)
  @tauri-apps/api - Not installed

Global packages
  npm - 7.13.0
  yarn - Not installed

Rust environment
  rustc - 1.52.1
  cargo - 1.52.0

Why did you create another issue? You can just reopen the other one.

Sorry, I didn't know issues could be reopened


changed typo from  to

Thanks for the PR but it was already resolved in #213. Anyways, thanks for bringing this to our attention 🙂


Merge PR of #620 and #644

#620 and #644 needed testing together before merging to main so I made a new PR that replaces them both.

From a merge POV, this looks good. I'm also happy with the monoscopic part. I didn't review the experimental side


Maix Dock Wi-Fi

The documentation is horrible to say the least.  I am trying to learn how to get the WIFI working and even though I tried the scripts they do not work.

The documentation is horrible to say the least. I am trying to learn how to get the WIFI working and even though I tried the scripts they do not work.

Same for me.
Please let me know if you get any progress.


add fondations for LLM

merging LLM (from #619) requires some reshaping of the code, here goes some changes splitted from the original PR.

add a Model abstracting away tensorflow specifics

still incomplete as it input/output tf.Tensors for now, and one can extract the tf.LayersModel
remove Task.training.modelCompileData as it's now contained inside the models.TFJS

add typesafe event emitter to safely register/call callbacks
rename Task.taskID to Task.id
while at it: drop unused training_functions, update axios, use async file read

For what it's worth very good stuff! I only left comment for what I didn't understand but it's a very nice refactoring

For what it's worth very good stuff! I only left comments for what I didn't understand but it's a very nice refactoring

héhé, thanks :smile:
followup of fixes form your remarks #645


New state of the arts for CIFAR <-> STL and VisDA

Great work, again :)
I've noticed that your work has been the state of the art, especially for the digits classification. But the performances for the CIFAR <-> STL seem to be improved. I'm wondering whether you've noticed any recent works for the non-digits tasks. If any, please share with us. Thank you very much:)

On the other hand, do you think domain adaptation will be efficient for the detection tasks? I've found two papers concerning this:
Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation
Domain Adaptive Faster R-CNN for Object Detection in the Wild
Have you found other works about applying domain adaptation to object detection? If any, please share with us. Thank you very much:)

I must admit I haven't followed the field that closely since early 2018. I did participate in the VisDa 2018 object detection domain adaptation challenge and got 2nd place with an algorithm that is related to the work here.
Still working on the publication.
Thanks for pointing out the paper; its interesting!


ENV/shared: set SOURCE_DATE_EPOCH

[x] Have you followed the guidelines in our Contributing document?
[x] Have you checked to ensure there aren't other open Pull Requests for the same change?
[x] Have you added an explanation of what your changes do and why you'd like us to include them?
[ ] Have you written new tests for your changes? Here's an example.

[x] Have you successfully run brew typecheck with your changes locally?
[ ] Have you successfully run brew tests with your changes locally?

https://reproducible-builds.org/docs/source-date-epoch/
This allows more reproducible builds by using a standardised environment variable to set the build date/time.
This env is set to the timestamp of the last git commit to the formula file, or the file's mtime if we don't have a tap.

Review period will end on 2021-04-15 at 15:40:03 UTC.

I'm not entirely sure what situations won't have one - it was mostly a sanity check. Given nil.to_i.to_s will return "0", it's probably safe to remove the check.

Review period ended.


Create Kadane_Algorithm.py

Simple Kaden's Algorithm in Python!.

@rajatsing contribute here https://github.com/Ishaan28malik/Get-Dev-Resources


Dont remember column type on create

Hello.
I'm use DBeaver 5.0.6 for MacOS. Work with PostgresSQL.
I create new column by clicking on Columns in table interface list:
Screenshot
Then window appears. I choose type (eg. bool). Click Ok.
Screenshot
Columns created with type varchar.
Screenshot
And I can really change it on tab double clicking on column name.

This is MacOS specific (and also an issue in SWT framework). I will try to make some general fix for all similar issues.
Workaround: press Enter or click somewhere outside of edit field. This will apply edited value and then you can click on "Ok".

After hit enter all works fine!
Thank you!


Modal is affected by other css styles

Hi,
By using the <modal> component where is wrapped by other dom elements (which has their own css styles), the rendered content of modal may be affected due to inheriting styling. This is because the template is rendered where the component it's used. Is there a way to render the template for example on <body> ?
Here is a better explanation:

change the font-size over the container affect all the inner content, except for some elements resized by bootstrap styles.
if you want your modal have not affected for the resizing, put the modal outside the element you are resizing, or change the font-size to the modal.

Hi @wffranco , thanks for you reply. I just put a simple example, there can be a lot of cases when the rendered modal is wrapped by other elements, like parent css classes affecting the modal, absolute elements, etc.
Yes, a simple solution is to always put the <modal> component on <body> or root element, but this means we can't use <modal> on sub-components or where is wrapped by other html elements, because the rendered html can be affected by wrapped elements styles.
So what I'm asking is to a solution to this conflict (not just fixing the font-size issue, which was just an example), so my guess is that the modal template should be "moved" or "transferred" to a non affecting html element like  or if there's a root/parent element.
Any idea of a good way to solve this ?

You test if without vue-strap you got the same behavior? Because almost the 90% of the styles are based on bootstrap, the modal component only have transition styles.


No new tables within storage account after restarting function app

I have an Azure Function App with a setting AzureWebJobsStorage.There are 2 tables within the storage account: History and Instances. I want to stop Azure Function App, delete History and Instances tables (followed this doc), restart Azure Function App so that new History and instances tables are created. I have the following code to restart function app:
Restart-AzFunctionApp -Name "Function-App" -ResourceGroupName "Resource-Group" - Force
I don't see any tables being created in the storage account after restarting the function app. After refreshing the function app manually via Azure Portal, I see the tables being created. What am I missing? How do I get it working via PowerShell command?

Document Details
⚠ Do not edit this section. It is required for learn.microsoft.com ➟ GitHub issue linking.

ID: 0abacaa4-8251-04dd-1199-0caef3780618
Version Independent ID: 5b789261-83a3-a6c0-a50d-8d74d3b1e41e
Content: Azure PowerShell Script Sample - Delete containers by prefix
Content Source: articles/storage/scripts/storage-blobs-container-delete-by-prefix-powershell.md
Service: azure-storage
GitHub Login: @stevenmatthew
Microsoft Alias: shaas

@lipalath-ms
Thanks for your feedback! We will investigate and update as appropriate.

@lipalath-ms
I'm going to assign this to the document author so they can take a look at it accordingly

Thanks for your contribution to our documentation
We are moving to a new user feedback system. As part of that effort, we are creating a content request in our backlog to address this gap and are closing this GitHub issue. The updated content will be published shortly.

Please continue to provide feedback about the documentation. We appreciate your contributions to our community.
#please-close

Thanks for your contribution to our documentation
We are moving to a new user feedback system. As part of that effort, we are creating a content request in our backlog to address this gap and are closing this GitHub issue. The updated content will be published shortly.

Please continue to provide feedback about the documentation. We appreciate your contributions to our community.
#please-close


fix: LSDV-4592: Remove ghost region on AudioV3

PR fulfills these requirements

[x] Commit message(s) and PR title follows the format [fix|feat|ci|chore|doc]: TICKET-ID: Short description of change made ex. fix: DEV-XXXX: Removed inconsistent code usage causing intermittent errors
[x] Tests for the changes have been added/updated (for bug fixes/features)
[ ] Docs have been added/updated (for bug fixes/features)
[x] Best efforts were made to ensure docs/code are concise and coherent (checked for spelling/grammatical errors, commented out code, debug logs etc.)
[x] Self-reviewed and ran all changes on a local instance (for bug fixes/features)

Change has impacts in these area(s)
(check all that apply)

[ ] Product design
[x] Frontend

Describe the reason for change
If a label is selected, and during the region creation we deselected the label using hotkeys, the region will be created as ghost region.
What does this fix?
If the user deselect a label using hotkey during the region creation, the region will be deleted.
What libraries were added/updated?
NA
Does this change affect performance?
No
Does this change affect security?
No
What alternative approaches were there?
NA
What feature flags were used to cover this change?
NA
Does this PR introduce a breaking change?
(check only one)

[ ] Yes, and covered entirely by feature flag(s)
[ ] Yes, and covered partially by feature flag(s)
[x] No
[ ] Not sure (briefly explain the situation below)

What level of testing was included in the change?
(check all that apply)

[x] e2e
[ ] integration
[ ] unit

Which logical domain(s) does this change affect?
(for bug fixes/features, be as precise as possible. ex. Authentication, Annotation History, Review Stream etc.)

Codecov Report
Base: 9.13% // Head: 9.15% // Increases project coverage by +0.01% :tada:

Coverage data is based on head (9258acd) compared to base (d108677).
Patch has no changes to coverable lines.

Additional details and impacted files
@@            Coverage Diff            @@
##           master   #1202      +/-   ##
=========================================
+ Coverage    9.13%   9.15%   +0.01%
=========================================
  Files         107     107
  Lines        8108    8109       +1
  Branches     2011    2011
=========================================
+ Hits          741     742       +1
  Misses       6185    6185
  Partials     1182    1182

Impacted Files
Coverage Δ

src/src/utils/feature-flags.ts
98.18% <0.00%> (+0.03%)
:arrow_up:

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.

:umbrella: View full report at Codecov.
:loudspeaker: Do you have feedback about the report comment? Let us know in this issue.


Does this initialization action offer the same as latest edition as Google Cloud Marketplace?

I have checked some news about starburst Enterprise edition on Google Cloud and I found that the following information is the most insightful as per [1]. It seems to me that the support at least for Latest Edition (version: 360) from Google Cloud to Starburst Presto has migrated from [2] to the Google Cloud marketplace as per [1]. The good sign of this is that the edition of presto available from the Google Cloud Market is 360 but the edition available from [2] is only 332 as per output given in [3 ].
Since the product has been available in Google Cloud Market therefore I do not think the support will be duplicated from Github.
Could Google Dataproc team advise me if the repository in [2] will provide the latest edition of Starburst Presto as it does from Google Cloud Marketplace.
I would like to hear from you after you have reviewed the availability per [4] suits your needs or not.

No, init action is currently hard coded 332 version:
https://github.com/GoogleCloudDataproc/initialization-actions/blob/25157b4a20e7283c0c7c77f391399c5fa17c46c3/starburst-presto/presto.sh#L25-L26
It's up to Starburst to update this init action to refer newer version, if they want to provide newer Presto version via this init action.
That said, Dataproc supports Presto without this init action: http://cloud/dataproc/docs/concepts/components/presto


5.25.0 has broken my builds

Bug report

I have a Laravel app which uses blade.php for browser-side content, with some small

Sorry, won't fix, without example we can't help you

Sorry, won't fix, without example we can't help you

Understood. Will try and make a minimal example.

Same issue here, I'm using Laravel Mix but no jQuery in the mix here, downgrading to 5.24.4 from 5.25.0 resolved the issue.
What is the current behaviour?
JS is not being executed client-side, I can't even get a console.log() output. No errors in the console either.
What is the expected behaviour?
JS should be executed client-side.
Other relevant information:
webpack version: 5.25.0
Node.js version: 14.15.4
Operating System: Windows 10
Additional tools: Laravel Mix

I thing bug on Laravel Mix side, as you can see not reports from other developers

Bug without example I can't help

Inevitably, my minimal example doesn't have the problem.  :( However it looks in the 'broken' version, all the js chunks are loaded but Webpack never "runs" them.

What is output of dist and generated index.html?

What is output of dist and generated index.html?

My HTML is unchanged (Webpack isn't generating that).
Relevant section snipped is
    <script src="/js/manifest.js?id=c7e3addb28db6d509f49"></script>
    <script src="/js/vendor.js?id=d425ac29b17e87266a7d"></script>
    <script src="/js/app.js?id=ce0df1181fd5328cf69f"></script>

    <script>console.log($)</script> -- crashes here

dist contains all the expected files.  Generated JS files seem identical apart from the last few lines. I can post an example of those if that helps?
In manifest.js there's this code, which I think is the actual module "runner".  It seems that __webpack_require__.o() is always returning false for these modules so they never get run...?
	if (__webpack_require__.o(installedChunks, chunkId) && installedChunks[chunkId]) {
		installedChunks[chunkId][0]();

Not all modules write yourself to window, so using $ is not a safe using here, do you have window.jQuery

Not all modules write yourself to window, so using $ is not safe here, do you have window.jQuery?

I'd get the same problem. My app.ts  starts with
import * as $ from "jquery"

window["$"] = $

... But that code is never executed because Webpack never 'runs' the modules it loads.  Breakpoints on that line are never hit in 5.25, but they are in previous 5.x builds.

This is very likely a bug in webpack. We did some refactoring to the startup logic.
You said only a few lines changed. Maybe you can post the diff?

This is very likely a bug in webpack. We did some refactoring to the startup logic.
You said only a few lines changed. Maybe you can post the diff?
I'm about to publish a small repo which demonstrates the issue. It's triggered by including a .scss file via mix. webpack thinks the load is not 'fulfilled' because it never 'sees' the scss file being loaded...

Ah that's possible if you have a chunk with only css and no JS, due to splitChunks.

Here's the repo.
https://github.com/roddypratt/webpack252bug

Hi! I'm one of the people who works on Mix. I'd be happy to help where I can with this!

Ah that's possible if you have a chunk with only css and no JS, due to splitChunks.

Yep this happens because we split CSS using splitChunks with a filename test + type: css/mini-extract + enforce: all

Yep, looks the regression, optimization options:
{
  optimization: {
   // Comment `runtimeChunk` solve the problem
   runtimeChunk: { name: '/manifest'}
   cacheGroups: {
    default: false,
    defaultVendors: false,
    'styles-mycss': {
      name: 'mycss',
      chunks: 'all',
      enforce: true,
      type: 'css/mini-extract',
      test: [Function]
    },
    vendor0: {
      name: '/vendor',
      chunks: 'all',
      enforce: true,
      priority: -10,
      test: /(?<!node_modules)[\\/]node_modules[\\/]()/i
    }
  }
}

Entry:
entry: {
    '/app': [
      '/path/to/project/src/app.ts',
      '/path/to/project/src/mycss.scss'
    ]
  },

i.e. using mini-css-extract-plugin + CSS entry + optimization.runtimeChunk broken

Thanks - Can confirm 5.25.1 fixes both my original project and the repo previously provided to reproduce the issue.!


create index with many values

Hello everyone,
is it possible to create index for multivalve dimension, like TO {recipient1, recipient2, recipient3} and more one metric column?
From the description, I understand it is not possible.
Regards,
Valentin.

Yes.  This requires some changes in the Druid APIs.

@vsankaranarayana thanks, will try figure it out.

@vsankaranarayana can you please guide which API should I look/change to make multivalued dimension. I implement analytics for email flow. From, To[could have multiple values], size, count.
Regards.


Dev krushna

Moved all the test-cases under Q/RUNTIME/test directory to q_testrunner framework.
Deleted unneeded files under Q/RUNTIME/test directory.

My simple concern remains that we are embedding logic in something that
should not be having such logic. It can be simply stated as a violation of
the e2e principal, but it’s your call.
Lastly we should not have two test case runners. Simply have one. The data
should state the expected result.
On Fri, Nov 17, 2017 at 6:50 PM ksrinath<EMAIL_ADDRESS>wrote:

@ksrinath commented on this pull request.
In OPERATORS/LOAD_CSV/test/good_data.lua
https://github.com/NerdWalletOSS/Q/pull/245#discussion_r151826221:

@@ -1,5 +1,5 @@
return {

{ meta = "gm1.lua", data = "gm1d1.csv" },
{ meta = "gm2.lua", data = "gm2d1.csv" },
{ meta = "gm3.lua", data = "gm3d1.csv" },

{ testcase_no = 1, meta = "gm1.lua", data = "gm1d1.csv" },

Objectively I think both alternatives are okay... Think this choice can be
left to the test case author.
(Personally I prefer the way it's done right now due to reasons of
readability, and the less likelihood of the test needed to be told to pick
up something else and run in future; it's just an implementation choice of
a test case, not a design choice.)
—
You are receiving this because your review was requested.
Reply to this email directly, view it on GitHub
https://github.com/NerdWalletOSS/Q/pull/245#discussion_r151826221, or mute
the thread
https://github.com/notifications/unsubscribe-auth/ABgX1wsWSkli0ng7l-_fvZT2l40m4a6Yks5s3kXggaJpZM4QgitB
.

--
Indrajeet Singh
<EMAIL_ADDRESS>http://www.nerdwallet.com/?trk=emaiL_sig
https://www.facebook.com/NerdWallet
https://www.linkedin.com/company/2029368
https://twitter.com/NerdWallet (415)
549-8913 <javascript:void(0);>
875 Stevenson St. - 5th Floor
San Francisco, CA 94103
Providing clarity for all of life's financial decisions


Update "Hello, Blockstack" tutorial for Blockstack Connect

https://docs.blockstack.org/browser/hello-blockstack.html
Update according to the changes made to the underlying app generator.

We're dropping this tutorial to simplify around the Todo list tutorial.


Dev mariuca

Codecov Report

Merging #75 (5470b47) into dev (6544a6c) will decrease coverage by 15.02%.
The diff coverage is 0.00%.

:exclamation: Current head 5470b47 differs from pull request most recent head 5ec653f. Consider uploading reports for the commit 5ec653f to get more accurate results

@@             Coverage Diff             @@
##              dev      #75       +/-   ##
===========================================
- Coverage   88.38%   73.36%   -15.03%
===========================================
  Files          75       78        +3
  Lines        3917     4719      +802
  Branches      188      188
===========================================
  Hits         3462     3462
- Misses        430     1232      +802
  Partials       25       25

Impacted Files
Coverage Δ

src/DucksNet.Domain/Model/User.cs
84.28% <0.00%> (-15.72%)
:arrow_down:

...igrations/20221205135853_InitialCreate.Designer.cs
0.00% <0.00%> (ø)

...ructure/Migrations/20221205135853_InitialCreate.cs
0.00% <0.00%> (ø)

...ructure/Migrations/DatabaseContextModelSnapshot.cs
0.00% <0.00%> (ø)

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.

Also. Please login into sonarqube and mark the issue as wontfix


"Cancel" text when uploading an avatar is confusing

The "cancel" button that appears when uploading an avatar makes it seem like the image is being actively uploaded (which is unfortunate, because since it isn't, the UI gives the appearance that the upload is hung.) I think a simple "(x)" icon would be much less confusing.

See also #756


nixos-anywhere: 1.1.2 -> 1.2.0

Diff: https://github.com/numtide/nixos-anywhere/compare/1.1.2...1.2.0
Description of changes

Things done

Built on platform(s)

[ ] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
24.05 Release Notes (or backporting 23.05 and 23.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[ ] Fits CONTRIBUTING.md.

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

Result of nixpkgs-review pr 307922 run on x86_64-linux 1

1 package built:

nixos-anywhere


Menu collapes on exception

features user
open a screen
try to open "Open Exception" screen -> Menu collapses
The menu shouldn't be changed?

fixed in 459dc180e9456e4c3ac6696ab9885bc4fb47ebc6


Solved issue 1007

Related Issue
Fixes:  #1007
Description
The content in the hero section are currently not aligned properly. This misalignment affects the overall visual appeal and user experience of the page.

Type of PR

[x] Bug fix
[ ] Feature enhancement
[ ] Documentation update
[ ] Other (specify): _______________

Screenshots / videos (if applicable)
##Before

##After

Checklist:

[x] I have made this change from my own.
[ ] I have taken help from some online resources.
[x] My code follows the style guidelines of this project.
[x] I have performed a self-review of my own code.
[x] I have commented my code, particularly in hard-to-understand areas.
[x] I have made corresponding changes to the documentation.
[x] My changes generate no new warnings.
[x] I have tested the changes thoroughly before submitting this pull request.
[x] I have provided relevant issue numbers and screenshots after making the changes.

Solve this conflicting issue & raise PR again


[feat] alternative vite.config.js

Describe the problem
Is there a way to specify alternative vite.config.js? I have in the same folder vite-browser.config.js and vite-native.config.js, which as their names suggests are configs for browser an native bundling of the same app (with slight difference). Tauri's help didn't help much in this regard.
tauri-app % npx tauri -h
Command line interface for building Tauri apps

Usage: npx-cli run npx [OPTIONS] <COMMAND>

Commands:
  build   Tauri build
  dev     Tauri dev
  icon    Generates various icons for all major platforms
  info    Shows information about Tauri dependencies and project configuration
  init    Initializes a Tauri project
  plugin  Manage Tauri plugins
  signer  Tauri updater signer
  help    Print this message or the help of the given subcommand(s)

Options:
  -v, --verbose...  Enables verbose logging
  -h, --help        Print help information
  -V, --version     Print version information

Describe the solution you'd like
something like tauri --vite-config vite-native.config.js should suffice.
well, I could potentially do in package.json:
  "scripts": {
    "dev": "vite --config vite-native.config.js",
    "build": "vite build",
    "preview": "vite preview",
    "tauri": "tauri"
  },

and do tauri dev, however, what if my package.json look like this?
  "scripts": {
    "dev:browser": "vite --config vite-browser.config.js",
    "dev:native": "vite --config vite-native.config.js",
    "build": "vite build",
    "preview": "vite preview",
    "tauri": "tauri"
  },

In this case what should I do?
Alternatives considered
No response
Additional context
No response

Found it... in tauri config.json


Make compilele-redis.sh executable

This fixed the build for ARM64 here.
make test fails with:

[14751] 16 Mar 08:48:36.572 # --- CLIENT LIST OUTPUT
[14751] 16 Mar 08:48:36.573 # id=3 addr=<IP_ADDRESS>:43205 fd=5 name= age=4 idle=0 flags=N db=9 sub=0 psub=0 multi=-1 qbuf=0 qbuf-free=32768 obl=0 oll=0 omem=0 events=r cmd=set

[14751] 16 Mar 08:48:36.573 # --- CURRENT CLIENT INFO
[14751] 16 Mar 08:48:36.573 # client: id=3 addr=<IP_ADDRESS>:43205 fd=5 name= age=4 idle=0 flags=N db=9 sub=0 psub=0 multi=-1 qbuf=0 qbuf-free=32768 obl=0 oll=0 omem=0 events=r cmd=set
[14751] 16 Mar 08:48:36.573 # argv[0]: 'set'
[14751] 16 Mar 08:48:36.573 # argv[1]: '923'
[14751] 16 Mar 08:48:36.573 # argv[2]: '923'

[exception]: Executing test client: I/O error reading reply.
I/O error reading reply
    while executing
"[srv $level "client"] {*}$args"
    (procedure "r" line 7)
    invoked from within
"r set $x $x"
    ("uplevel" body line 4)
    invoked from within
"uplevel 1 $code"
    (procedure "test" line 29)
    invoked from within
"test {SET 10000 numeric keys and access all them in reverse order} {
            set err {}
            for {set x 0} {$x < 10000} {incr x} {
        ..."
    ("uplevel" body line 23)
    invoked from within
"uplevel 1 $code"
    (procedure "tags" line 3)
    invoked from within
"tags {"slow"} {
        test {Very big payload random access} {
            set err {}
            array set payload {}
            for {set j 0} {$j ..."
    ("uplevel" body line 55)
    invoked from within
"uplevel 1 $code "
    (procedure "start_server" line 3)
    invoked from within
"start_server {tags {"basic"}} {
    test {DEL all keys to start with a clean DB} {
        foreach key [r keys *] {r del $key}
        r dbsize
    } ..."
    (file "tests/unit/basic.tcl" line 1)
    invoked from within
"source $path"
    (procedure "execute_tests" line 4)
    invoked from within
"execute_tests $data"
    (procedure "test_client_main" line 10)
    invoked from within
"test_client_main $::test_server_port "
Killing still running Redis server 14751
make[1]: *** [Makefile:211: test] Error 1
make[1]: Leaving directory '/redis/src'
make: *** [Makefile:6: test] Error 2
7

I will debug this error now!

The error in make test seems to be a QEMU related.
All is fine when executing make build-arm on real ARM64 hardware. I just needed to comment out @docker run -it --rm --privileged multiarch/qemu-user-static --credential yes --persistent yes there

The test failure is still there with Redis 6.0.10 too

The binary files (target/redis-2.8.19/src/redis-server) produced by Docker+QEMU and direct build on my ARM64 machine have the same file size: 5243928, but cmp gives some differences:
 cmp -l -b redis-server-built-on-arm64 redis-server-built-with-docker
    669 174 |    263 M-3
    670 366 M-v  304 M-D
    671 130 X     61 1
    672 203 M-^C 244 M-$
    673 323 M-S  122 R
    674 163 s    144 d
    675  15 ^M   351 M-i
    676 372 M-z   72 :
    677 212 M-^J 327 M-W
    678 176 ~     32 ^Z
    679 266 M-6  351 M-i
    680 105 E    226 M-^V
    681  30 ^X    64 4
    682 151 i    146 f
    683 310 M-H  303 M-C
    684 120 P    263 M-3
    685 270 M-8  336 M-^
    686 144 d    130 X
    687 273 M-;  171 y
    688 257 M-/  244 M-$
 798351 145 e    143 c
 798352  61 1     65 5
 798353  62 2     60 0
 798355 143 c     63 3
 798356 144 d    142 b
 798357  64 4     60 0
 798358 146 f     60 0
 798360 141 a     61 1
 798361 142 b     65 5
 798362  65 5     66 6
 798369  70 8     71 9
 798370  66 6     63 3
 798371  62 2     67 7
 798372  61 1     60 0
 798373  67 7     66 6

I don't have ARM hardware available so I can't generate a binary directly. It'll have to go through QEMU.
I think the best way to use the library for you is to generate your own binary and stick it in a resource and then configure a RedisServer to use it like so:
final ExecutableProvider executables = new ExecutableProviderBuilder()
    .add2_8_19()
    .put(OS.UNIX, Architecture.aarch64, "/path/to/resource/redis-server-arm")
    .build();

new RedisServer(Redis.DEFAULT_REDIS_PORT, executables);

Let me know if this works for you.

If just redis-server works (i.e. looked up in the $PATH) then I think this could work well even for the OSS projects I care about!
In TravisCI I can apt install redis-server and use the binary!
I will test it right away!
Thanks!


how can i custom the class's property name?

Is there an existing issue for this?

[X] I have searched the existing issues

Current Behavior
models.jsonc file:
[
{
"__className": "history",
"e_id": "9403"
}
]
history.dart file:
class History {
String? eId;
History({this.eId});
factory History.fromJson(Map<String, dynamic> json) => History(
eId: json['e_id'] as String?,
);
Map<String, dynamic> toJson() => {
'e_id': eId,
};
}
Expected Behavior
how can i annotation the e_id in JSON, auto change the dart class's eId to historyId?
like:
d@ - Marks as default value.
r@ - Marks as required value.
hope add the n@field@propery - Marks custom propery name.
Steps To Reproduce
No response
Version
No response
Relevant JSON syntax
No response
Anything else?
No response

@hiyangjx Hi 👋
To change the class property name you don't need to annotate anything. Just change JSON key name. In your case change 'e_id' to 'history_id'.

@hiyangjx Hi 👋 To change the class property name for primitive values you don't need to annotate anything. Just change JSON key name. In your case change 'e_id' to 'history_id'.

thanks. but the real json field is e_id, if i changed it in **.jsonc, i will change the following code manually after build every time.
from:
factory History.fromJson(Map<String, dynamic> json) => History(
historyId: json['history_id'] as String?,
);
to:
factory History.fromJson(Map<String, dynamic> json) => History(
historyId: json['e_id'] as String?,
);

Dart to Json Model support converting from the local file **.jsonc to make easily edit original json files. That if you want another property name you need change json key and generator will generate new updated JSON object. Annotation used for anothers options where you can't display in original JSON file. But for edit the name for primitive values is no idea to add annotation and change JSON guide lines. Can you explain with more details what wrong if you change the original json key in the jsonc file?
@hiyangjx

@iamarnas
Thanks for your reply. To put it simply, I just don't know how to use @jsonkey annotation. If I want to get history.swift:
`import 'package:json_annotation/json_annotation.dart';
class History {
@JsonKey(name: 'e_id')
String? id;
History({this.id});
factory History.fromJson(Map<String, dynamic> json) => History(
id: json['e_id'] as String?,
);
Map<String, dynamic> toJson() => {
'e_id': id,
};
}`
How can i write models.jsonc?

@hiyangjx Aaa, OK, I got it. This generator does not support changing name for primitive values. Only for class elements it possible to change type.

@iamarnas
Thanks, the https://github.com/flutterchina/json_model support this feature, if you need.

@hiyangjx Thank you for the tips 👍


Theme issue: can't read texts

Hi,
Thank you for your hard work.
I'm facing a problem with panel theme. I can't read texts. could you change text colors to white?
Thanks.

Oh, it's strange, I can reproduce the error.
Do you have same problem from computer or another mobile browser?

Yeah, I think if the device theme is set to "Dark mode" this problem happens.

Yes! It's dark mode. I don't know this!
I'm going to check how to fix it.
Thanks!

Fixed!


Temp is not an option in HA Deices

Just curious. Should the ds18b20 show here?

fixed in v.2.6.1


Reports with Days instead of interval

📑 I have found these related issues/pull requests
None
🏷 Feature Request Type
Status-page
🔖 Feature description
Please add Daily Reports like the screen shot and status icons with descriptions.

✔ Solution
Bars will show days instead of the current interval.
❓ Alternatives
No response
📝 Additional Context
No response

Duplicate of https://github.com/louislam/uptime-kuma/issues/1888
=> Closing as such


2 sheets per page view

This is a popular way to read manga on larger devices. A few bigger publications and apps support it.
Hoping KCC will eventually!

Duplicate of #392


Use compacted lists on fact index page.

Changes

Use compacted lists on fact index page. Fixes #3772.

For review: @DoSomething/front-end

:+1:


modified Japanese translation.

add some missing words(ex. cont'd.)
use proper word for "Desktop Firefox"
translated reduction, Developer, and Translator

Thank you for the translation improvement!

I have just pushed to gh-pages branch.


Prettier with pre-commit hook

This adds the following new packages:
prettier
lint-staged
husky
When you commit your files, it will prettify only the staged .js files and then run eslint --fix on them.  I haven't versioned this or prettified the whole project with this commit because I'm sure there will be opinions/feedback on this.  Maybe we don't want to auto fix lint issues, etc.
I also added a "prettify" npm script that will parse the whole project, mostly as reference, but also in case we decide to change any settings later it might be useful.

I pulled it down and gave it a try and it did exactly what I was hoping it'd do. This at least makes it so even if you don't have an editor configured, it auto formats the file for you when you go to commit.
We probably do want to use the --jsx-bracket-same-line false flag though since that looks like it already is our convention. I'm fine with ES Lint just fixing things as well, though @jrios might have some opinions on that.

The default for the --jsx-bracket-same-line is false, which is how I've been composing my code.  If same-line is the standard here though I'll set it to true.

Ah I didn't realize the default already was false, then we're good. :p


"aboutUpdateURL" should be a localizable string

in com.github.macadmins.Nudge.json so users might get sent right to the localized version of the help site.
Btw. thank you for open sourcing this :)

This is a great idea. I'll have to think about how to add this functionality is as it would make the osVersionRequirement key more complex than I intended it to be.

You can now do something like
{
    "osVersionRequirements": [
        {
            "aboutUpdateURLs": [
                {
                    "_language": "en",
                    "aboutUpdateURL": "https://support.apple.com/en-us/HT211896#macos1121"
                },
                {
                    "_language": "es",
                    "aboutUpdateURL": "https://support.apple.com/es-es/HT211896"
                },
                {
                    "_language": "fr",
                    "aboutUpdateURL": "https://support.apple.com/fr-fr/HT211896"
                }
            ],
            "majorUpgradeAppPath": "/Applications/Install macOS Big Sur.app",
            "requiredInstallationDate": "2021-02-28T00:00:00Z",
            "requiredMinimumOSVersion": "11.2.1",
            "targetedOSVersions": [
                "11.0",
                "11.0.1",
                "11.1",
                "11.2"
            ]
        }
    ]
}

Thanks again for the report. Nudge v<IP_ADDRESS>52021143543 and higher will support this functionality.

Wow, that was quick. Awesome, I'll give it a try later.


PDF entry layout

What do you need?
Andrew suggested the PDF entry may be better displayed as an image showing the pattern for placing one into a page/screen. See how GDS shows how to put a pdf on a page with: thumbnail image, title, description, pdf icon, file size.
Which entry/section is this related to?
http://content-style-guide.apps.staging.digital.gov.au/az-indexes/p.html#pdfs
Good example
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/361677/corporate-report-good-example.pdf
https://www.gov.uk/guidance/how-to-publish-on-gov-uk/accessible-pdfs

This sounds like something @maadonna might be interested in too, given that this could become a little pattern in the UI KIt and is available for template implementers to use for their authors when adding PDFs to things.
The tech specifics on the dynamic templating are nuanced… but the styling for this as a pattern is definitely something we could standardise in the UI-Kit.

@klepas - happy to workshop this with you and others when appropriate

I suspect this will be put on the backburner as a pattern. We have it tracked here, so it’s in our backlog. (:

https://github.com/govau/content-guide/issues/69


Raw files for CMU MOSEI dataset

Can the raw files for the CMU MOSEI dataset be shared? I saw that its on a Baidu server which I cannot access unfortunately.

If only the MOSEI dataset is needed, the following link may help. @sumit-agrwl  http://immortal.multicomp.cs.cmu.edu/raw_datasets/processed_data/

Hi, we've updated the Baiduyun link recently.
Closing this issue for now.


Edits to API Design doc

:warning: Validation status: warnings

File
Status
Preview URL
Details

docs/best-practices/api-design.md
:warning:Warning
View
Details

docs/best-practices/api-design.md

Line 104: [Warning] Invalid file link:(~/best-practices/antipatterns/chatty-io.md).
Line 104: [Warning] Invalid file link:(~/best-practices/antipatterns/extraneous-fetching.md).

For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.

:warning: Validation status: warnings

File
Status
Preview URL
Details

docs/best-practices/api-design.md
:warning:Warning
View
Details

docs/best-practices/api-design.md

Line 104: [Warning] Invalid file link:(~/antipatterns/chatty-io.md).
Line 104: [Warning] Invalid file link:(~/antipatterns/extraneous-fetching.md).

For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.

:warning: Validation status: warnings

File
Status
Preview URL
Details

docs/best-practices/api-design.md
:warning:Warning
View
Details

docs/antipatterns/no-caching/index.md
:warning:Warning
View
Details

docs/best-practices/api-implementation.md
:white_check_mark:Succeeded
View

docs/best-practices/api-design.md

Line 104: [Warning] Invalid file link:(~/antipatterns/chatty-io.md).
Line 104: [Warning] Invalid file link:(~/antipatterns/extraneous-fetching.md).

docs/antipatterns/no-caching/index.md

Line 106: [Warning] Illegal link: [API implementation][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.
Line 200: [Warning] Illegal link: [API implementation best practices][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.

For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.

:warning: Validation status: warnings

File
Status
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Details

docs/best-practices/api-design.md
:warning:Warning
View
Details

docs/antipatterns/no-caching/index.md
:warning:Warning
View
Details

docs/best-practices/api-implementation.md
:white_check_mark:Succeeded
View

docs/best-practices/api-design.md

Line 104: [Warning] Invalid file link:(~/antipatterns/chatty-io.md).
Line 104: [Warning] Invalid file link:(~/antipatterns/extraneous-fetching.md).

docs/antipatterns/no-caching/index.md

Line 106: [Warning] Illegal link: [API implementation][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.
Line 200: [Warning] Illegal link: [API implementation best practices][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.

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docs/best-practices/api-implementation.md
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docs/antipatterns/no-caching/index.md

Line 106: [Warning] Illegal link: [API implementation][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.
Line 200: [Warning] Illegal link: [API implementation best practices][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.

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docs/best-practices/api-implementation.md
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docs/antipatterns/no-caching/index.md

Line 106: [Warning] Illegal link: [API implementation][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.
Line 200: [Warning] Illegal link: [API implementation best practices][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.

For more details, please refer to the build report.
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docs/best-practices/api-implementation.md
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docs/antipatterns/no-caching/index.md

Line 106: [Warning] Illegal link: [API implementation][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.
Line 200: [Warning] Illegal link: [API implementation best practices][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.

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docs/best-practices/api-implementation.md
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docs/antipatterns/no-caching/index.md

Line 106: [Warning] Illegal link: [API implementation][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.
Line 200: [Warning] Illegal link: [API implementation best practices][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.

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docs/antipatterns/no-caching/index.md

Line 106: [Warning] Illegal link: [API implementation][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.
Line 200: [Warning] Illegal link: [API implementation best practices][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.

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docs/antipatterns/no-caching/index.md

Line 106: [Warning] Illegal link: [API implementation][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.
Line 200: [Warning] Illegal link: [API implementation best practices][api-implementation] -- missing bookmark. The file best-practices/api-implementation.md doesn't contain a bookmark named considerations-for-optimizing-client-side-data-access.

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VID PayloadProver trait API generalize to prove multiple payload subslices in a single proof

Per offline discussion on namespace/tx proofs, eventually we'll need this functionality. Something like this:
fn payload_multiproof(payload: &[u8], ranges: &[Range<usize>]) -> PROOF

Due to design changes we no longer need this.


missing README.install

I could use a little help with today’s packaging of Python module. I did what I could before the new Python distribution came out.
One can build by doing
$ python3 -mbuild

More details in Python PEP-0517.


Best way to destroy a model and related models/collections?

I can't figure out how to destroy a model and related models/collections.
What's the best way?

We just released the bookshelf-cascade-delete plugin which implements the solution proposed by @tkellen, hope it can help you guys!

The project leadership of Bookshelf recently changed. In an effort to advance the project we close all issues older than one year.
If you think this issue needs to be re-evaluated please post a comment on why this is still important and we will re-open it.
We also started an open discussion about the future of Bookshelf.js here https://github.com/bookshelf/bookshelf/issues/1600. Feel free to drop by and give us your opinion.
Let's make Bookshelf great again


Select and Deselect programmatically

A method for programmatically selecting and deselecting lines is missing.
If a line is selected and the data array changes, a line still remains selected even though it no longer exists.
It would be nice if you could implement 2 methods for this.

This is needed because of pagination only selecting visible lines.
Need to select all paginated content.

Found a solution,
let i = 1, self = this;
_.map(self.rows, function(row) {
    contact.vbt_id = i++;
    self.$refs.vueBootstrap4Table.addSelectedItem(row);
});


Add utility for generic sprite sheet format.

Follow up thought: The point of this is convenient use of tilesets so that people can focus on their game building. What other things would be helpful here that we can do for them?
val maxRows: Int = ???
val maxColumns: Int = ???
val maxIndex: Int = ???
val length: Int = maxIndex

def fromCoords/Point(pt: Point): Option[Graphic[Material.Bitmap]] = ???

Anything else you can think of?
On that last one, lots of excellent reasons to need to look up by index, but people are bad at indexes, and they might also like to just be able to look up by coordinates now and again.


HTML

HTML
User Story
As a bootcamp student
I want the prework notes to be structured on a webpage
so that I can easily find and read information
Acceptance Criteria
GIVEN a Prework study guide website
WHEN I visit the website in my browser
THEN I see four boxes titles HTML, CSS, Git, and Javascript with associated notes listed

added HTML to file


add: Jump Search

Describe the algorithm/code
Issue Description : Jump Search is an efficient searching algorithm for ordered lists. It divides the list into smaller blocks and jumps ahead by fixed steps to quickly reach a block that might contain the target value. It then performs a linear search within that block, providing a balance between the efficiency of binary search and the simplicity of linear search. Jump Search is especially useful for large datasets where binary search might be less efficient due to its logarithmic time complexity.
Hi there 👋
I'm excited to contribute to Hacktoberfest 2023, and I'd like to work on this issue. It looks like a great opportunity to learn and contribute to the project.
Please assign this issue to me, and I'll start working on it right away. If you have any specific instructions or guidelines, please let me know, and I'll make sure to follow them.
Thanks a lot for considering my request!
Best regards,
Prateek Sethi
Do you want to work on this feature?

[X] I am willing to implement this feature.

Hi @prateekpr17 !
It seems the issue and the definition you provided is AI generated!

Indeed I've used AI services to generate a more formal language for the description. Nothing more. I've already practiced the algorithm in python.

Okay you can start working on this issue! ✌


Move partitions elsewhere

Repository is huge with the ChoCo partitions included. I think it would be best to move them to another repository and maintain this one as a library for music entity linking.

The idea is to unbundle the repository in two:

MusicMetaLinker: extracts and aligns metadata
SmasHubLinker (within the SmasHub organization): uses MusicMetaLinker and adapts the workflow to the SmasHub JAMS-based workflow.

For now, I am creating a new branch for keeping a copy of the generated partitions, and removing them from main.

The idea is to unbundle the repository in two:

MusicMetaLinker: extracts and aligns metadata
SmasHubLinker (within the SmasHub organization): uses MusicMetaLinker and adapts the workflow to the SmasHub JAMS-based workflow.

For now, I am creating a new branch for keeping a copy of the generated partitions, and removing them from main.

Done


Update docs structure

Changes

Update README.md and add place holder docs

/kind

Fixes #

Release Note

Docs

Yes, it was mostly inspired by https://github.com/cncf/k8s-conformance