can't copy and paste text from Swing console in linux

Hi,
Is there a method to call to enable the ability to copy and paste text from a Swing terminal in linux ?
Thx!

Ctrl-C / Ctrl-V should work out of the box. I have no issues with copy and paste on my Linux system.

I think I know part of the problem. I doubt you have played the game. In the game CTRL+C is defined  to show list of countries as can be seen in the screenshot I'm sharing below.

You can register handlers for the copy and paste actions. Try something like this:
terminal.registerHandler("control INSERT", t -> {
    t.getTextPane().copy();
    return new ReadHandlerData(ReadInterruptionStrategy.Action.CONTINUE);
});
terminal.registerHandler("shift INSERT", t -> {
    t.getTextPane().paste();
    return new ReadHandlerData(ReadInterruptionStrategy.Action.CONTINUE);
});

Replace "control INSERT" and "shift INSERT" with the key combinations you prefer.

Could there be something for arbitary text selections via mouse or should I/we put up a new bug instead to address that ?

This will append the text selected by mouse to the input:
terminal.registerHandler("shift INSERT", t -> {
    String selectedText = t.getTextPane().getSelectedText();
    if(selectedText != null) {
        t.getTextPane().setCaretPosition(t.getDocument().getLength());
        t.appendToInput(selectedText, true);
        t.getTextPane().setCaretPosition(t.getDocument().getLength());
    }
    return new ReadHandlerData(ReadInterruptionStrategy.Action.CONTINUE);
});

@siordache ,
The Ctrl-C and Ctrl-V works and I can change it to whatever.
Other than keyboard, can we have a right-click popup menu for doing copy and paste with a mouse ?

@siordache ,
The Ctrl-C and Ctrl-V works by default in Windows at least.
Appreciate with your snippet of codes above. Now I can change it to whatever I need.
Other than keyboard, can we have a right-click popup menu for doing copy and paste with a mouse ?

It will surely help us if we can have mouse support as well. Would that be too much work ?

The SwingTextTerminal exposes its frame and textPane, so you can add context menus or main menus to them using plain Swing programming.
I recommend putting these changes in a subclass of SwingTextTerminal, as shown here.

@siordache , thanks much for the implementation ! I'm closing this thread now.


Picture not taken - sample should check whether the camera device supports auto-focus

Some cameras do not support auto-focus (for instance, the front-facing camera of the device I'm using). In the sample app, this results in the app failing to take a photo.
I found this same question being asked by several different people on here and on StackOverflow, and people have been asking this question over the past couple of years. An update to the sample app is long overdue.
I found a promising answer here. in takePicture(), the app should call captureStillImage rather than lockFocus if auto-focus is not supported by the selected camera.
Technical info: The Capture callback "process()" method does not have a condition branch for the case where the autofocus algorithm is inactive (i.e. where afState = 0). Consequently if the selected camera device does not support autofocus, stillImageCapture() never gets called.

你说的是正确的，我的设备执行lockFocus()这个方法，就没有任何反应，日志信息也没有输出相关的内容，你的方法解决了我的问题。thank you

This sample has been migrated to a new location where we can accept Pull Requests (check README for more information).
As recommended by GitHub, we are closing all issues and pull requests now that this older repo will be archived.
If you still see this issue in the updated repo, please reopen the issue/PR there. Thank you!


the character AI isn't responding to me back

when i input , the code just run without giving error but it is also not responding to my input , like i waited 30 min after inputting and  it doesn't do anything ;-;. hope you can help!

I will fix all bugs with user.send_message() in the next few days, it will be in version 0.4.0

thanks for the help , update me when it works it would be great help!

chat.send_message() has been rewritten In v0.4.0

chat.send_message() has been rewritten In v0.4.0

still not working here using pip package v0.4.1


Update URLs to use https://downloads.mesosphere.com. Fixes #171

I've tested a handful of these to make sure the assets are still downloadable.
For the most part I had to move no files - but there are a bunch of Spark files in the downloads.mesosphere.com bucket under "assets". I had to move the "log4j.properties" file over into the downloads.mesosphere.io bucket under "spark/assets" since it turns out https://downloads.mesosphere.com actually points to the downloads.mesosphere.io bucket. The other files still need to be moved and the Spark tutorial updated.
@cmaloney, @jsancio - please sanity check! An alternative approach here is to submit new versions of the packages with the URLs updated and then hope package maintainers use the new URLs going forwards. This might be preferable to updating old packages too. Let me know.

@ssk2 Why are we doing this? Does this break already deployed/installed packages? Meaning this doesn't change the URL in Marathon AppDefinition that have already been deployed.
Also, package revision are immutable and should not been changed after they have been deployed. Please explain why we are doing this. Is there a Jira issue for this?

Please see the linked issue #171 for a description. We have generally
inconsistent ways of accessing assets for packages and this can cause
breakages / confusion.
I'm unsure how it could possibly break already deployed packages - am I
missing something?
I'll create new packages with the new URLs, as per your other comment.
On 6 Nov 2015 17:05, "José Armando García Sancio"<EMAIL_ADDRESS>wrote:

@ssk2 https://github.com/ssk2 Why are we doing this? Does this break
already deployed/installed packages? Meaning this doesn't change the URL in
Marathon AppDefinition that have already been deployed.
Also, package revision are immutable and should not been changed after
they have been deployed. Please explain why we are doing this. Is there a
Jira issue for this?
—
Reply to this email directly or view it on GitHub
https://github.com/mesosphere/universe/pull/256#issuecomment-154474102.

@jsancio - updated! I created new revisions for each of the packages that contained old/bad URLs and updated index.json.

Links fixed in documentation in https://github.com/mesosphere/mesosphere-docs/pull/223.

The spark package files are now generated from: https://github.com/mesosphere/spark-build/tree/master/package
This is so we can create a package artifact from our automated spark test.  If you are going to make changes to spark, please do so there, as these won't persist.

@mgummelt: I've moved the Spark package changes over to spark-build and raised a PR there. If no-one has any objections to the other changes in this PR, I will merge this tomorrow.


add support for multiple projects

The idea is, if I have multiple remote projects represented in the same directory as multiple remotes of my git repository, there should be support for interacting with more than one of them. Right now something like the command "environment:ssh" only works against the "main" project, and there's no way to use that specific command to ssh into other projects.
Edit: yes you can use ssh command against other projects, but (a) detecting the project and branch using git is easier, requires less looking up info and then copy pasting (detect current branch and which remote does current branch track) and (b) other commands you cannot specify project AFAIK such as environment:checkout.

You can do
platform ssh -p projectid

but maybe I'm missing something

you're right I updated the issue to clarify. Also FYI this is an issue I discussed with @Kazanir so he has some context.


feat: Custom nodepools

What type of PR is this? (check all applicable)

feat: A new feature

Description
Adds custom node pools capability to google cluster deploy.

This PR is included in version 1.3.0 :tada:


Selectively enable different frontends

Description
Allows users to configure which frontends/features they want to include in the torch-tensorrt builds.
Features can be enabled as so:
NO_TORCHSCRIPT=1 pip install -e . ... # Includes the C++ runtime but no Torchscript frontend
PYTHON_ONLY=1 pip install -e . ... # No C++ dependencies at all, a pure python package

A builds feature set can be accessed via the following struct
import torch_tensorrt

torch_tensorrt.ENABLED_FEATURES

where ENABLED_FEATURES is a namedtuple FeatureSet:
namedtuple('FeatureSet', [
    "torchscript_frontend",
    "torch_tensorrt_runtime",
    "dynamo_frontend",
    "fx_frontend"
])

In order to support optional features, a number of core types have been abstracted:

torch_tensorrt.Device has no direct dependencies on the torchscript core and can be translated to torch_tensorrt.ts.Device to access those features
Similarly torch_tensorrt.Input behaves the same way
enums for dtype,DeviceType, memory_format have been defined and can translate from numpy, tensorrt, torch and torch_tensorrt._C (assuming torch_tensorrt.ENABLED_FEATURES.torchscript_frontend is True)

Translating between different library enums now can take the form
import torch
import tensorrt as trt
import torch_tensorrt

# Convert, throw error if no conversion exists
trt_dtype = torch_tensorrt.dtype._from(torch.float16).to(trt.DataType) # returns trt.DataType.HALF

#Try to convert, do not throw an error if there is no conversion, just return None
trt_dtype = torch_tensorrt.dtype.try_from(torch.float16).to(trt.DataType) # returns trt.DataType.HALF

# Alternatively, use a fallback type
trt_dtype = torch_tensorrt.dtype.unknown.to(trt.DataType, use_default=True) #returns trt.DataType.FLOAT

Fixes #1943
Fixes #2379
Type of change
Please delete options that are not relevant and/or add your own.

New feature (non-breaking change which adds functionality)

Checklist:

[x] My code follows the style guidelines of this project (You can use the linters)
[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas and hacks
[x] I have made corresponding changes to the documentation
[x] I have added tests to verify my fix or my feature
[x] New and existing unit tests pass locally with my changes
[x] I have added the relevant labels to my PR in so that relevant reviewers are notified

Additionally, tested on Windows E2E models and appears to cleanly dispatch to the correct runtime without needing to modify the use_python_runtime flag

A few examples, such as the one below, use precision still and would fail with some of the changes.
https://github.com/pytorch/TensorRT/blob/c5b8909f47485df934041e8fd40e1f75f9d77671/examples/dynamo/torch_compile_stable_diffusion.py#L42

Will docs be updated with the instructions as a different PR ?


How to remove Hash for breakpoint debugging?

I want breakpoint debugging, but this Hash always change when I edit my code. please help me :)

Update your webpack config, change
devtool: '#eval-source-map',

to
devtool: '#source-map',

this may help.

I will close this assuming @CodinCat's suggestion resovles this. Please open another issue if you still have probelms.

tks!


can this be configured for flask ?

[ ] I am using the latest SDK version
[ ] This API is compatible with my vCenter version (You can get the info from 'vcenter_version' in each sample)
[ ] I have searched existing issues and Troubleshooting wiki

Environment

sdk package version:

python version:

vSphere version:

Operating System/Shell (used to run SDK-based apps):

Steps or code snippet to reproduce
Actual behavior
Expected behavior

@dfoley84 Can you be more specific about your question?

@tianhao64 at the moment i am working on a "Node.js" front end that will link back to Terraform, to give users a GUI interface for requesting vsphere / amazon web service resources. While Terraform is limited with vmware provider, i would like to opt for the same idea for vSphere SDK for python using "Flask" to give users a rich GUI interface for requesting vsphere resources. Since you don't offer a java script version.
Also what is the difference between this SDK vs PowerCLI for automation ?

@dfoley84 This sdk has python bindings to vSphere, VMC and NSXT REST APIs. PowerCLI provides cmd link utils to interact with multiple VMware products. Note that at this point majority of the vSphere features are covered by pyVmomi. Automation SDK covers a few new features as well as vCenter VM lifecycle APIs.
PyVmomi uses vSphere web service APIs which are SOAP based APIs. For more info refer to: https://code.vmware.com/doc/preview?id=4206
vSphere Automation SDKs (python, java, .net, perl, ruby and REST) uses new version REST based APIs. Some new features like Tagging, Content Library,
Appliance Management, NSX and VMware Cloud on AWS console APIs are only available through the Automation SDKs. Some existing SOAP based APIs, such as VM lifecycle and VC inventory APIs are also re-designed to support REST. For more info please see: https://vmware.github.io/vsphere-automation-sdk/. Here is talk from @kmruddy about the new REST API: https://www.youtube.com/watch?v=nr3pJovtbzM


Old datasource ids are not referenced in chart import

SUMMARY

BEFORE/AFTER SCREENSHOTS OR ANIMATED GIF

TESTING INSTRUCTIONS

ADDITIONAL INFORMATION

[ ] Has associated issue:
[ ] Required feature flags:
[ ] Changes UI
[ ] Includes DB Migration (follow approval process in SIP-59)

[ ] Migration is atomic, supports rollback & is backwards-compatible
[ ] Confirm DB migration upgrade and downgrade tested
[ ] Runtime estimates and downtime expectations provided

[ ] Introduces new feature or API
[ ] Removes existing feature or API

Thanks @philipher29 for the PR. It seems like there's a conflict with your branch, would you mind rebasing against master? Also would you mind filling out the PR description including the testing instructions.

Closing this since it's in need of a rebase, but please feel free to re-open when it's ready to rock! Thanks in advance!


FUNCTION OBJECT_SCHEMA_NAME not supported in Azure Synapse Serverless

Maybe I'm missing something but I'm thinking this doc should have a caveat that it is not supported in Azure Synapse Serverless, since the "Applies to:" references "Azure Synapse Analytics".  Error: "FUNCTION 'OBJECT_SCHEMA_NAME' is not supported" is returned using it in Azure Synapse Serverless.
Thanks,
Luke

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

ID: 5c0cee1d-1e90-2cd1-39c2-67404d0f2cc8
Version Independent ID: 483fc29c-d706-dbf2-db99-513bc683298c
Content: OBJECT_SCHEMA_NAME (Transact-SQL) - SQL Server
Content Source: docs/t-sql/functions/object-schema-name-transact-sql.md
Product: sql
Technology: t-sql
GitHub Login: @MikeRayMSFT
Microsoft Alias: mikeray

@lpargiter -- thank you for your feedback.
@MikeRayMSFT -- please look into this issue.

Has there been any progress on this? I just wasted an afternoon working on something only to find out that it will work in our dedicated but not our serverless

@jenpritchard -- Jen, thank you for your followup.
@rwestMSFT -- Randolph, please look into this issue.

#reassign:WilliamDAssafMSFT

@lpargiter Thanks for taking the time to provide this feedback, your suggestions help improve our documentation. This article will be updated to clarify its applicability for Azure Synapse. You are correct, this syntax is not supported for serverless SQL pools.


"Lib: XMLRPC Timeout - can you `ping' the sensor?" with make test even though I can ping the sensor

Hello Everyone,
I am trying to connect to the O3X100 Sensor using ubuntu 18.04 and ROS Melodic.
I installed Ifm3d and ifm3d-ros. However, every time I try to connect to the Sensore I get the error message above. This happens when running  $ make check in the ifm3d installation as well as when running $ catkin_make run_tests in the ifm3d-ros installation and when running $ roslaunch ifm3d camera.launch.
However, I am able to ping the sensor when running $ ping <IP_ADDRESS> .
The output when running $ make check is:
[ 22%] Built target ifm3d_camera_shared
[ 37%] Built target ifm3d_framegrabber_shared
[ 44%] Built target ifm3d_image_shared
[ 51%] Built target gtest
[ 59%] Built target gtest_main
[ 70%] Built target ifm3d-image-tests
[==========] Running 10 tests from 1 test case.
[----------] Global test environment set-up.
[----------] 10 tests from Image
[ RUN      ] Image.MoveCtor
unknown file: Failure
C++ exception with description "Lib: XMLRPC Timeout - can you `ping' the sensor?" thrown in the test body.
[  FAILED  ] Image.MoveCtor (1 ms)
[ RUN      ] Image.MoveAssignmentOperator
unknown file: Failure
C++ exception with description "Lib: XMLRPC Timeout - can you `ping' the sensor?" thrown in the test body.
[  FAILED  ] Image.MoveAssignmentOperator (0 ms)
[ RUN      ] Image.CopyCtor
unknown file: Failure
C++ exception with description "Lib: XMLRPC Timeout - can you `ping' the sensor?" thrown in the test body.
[  FAILED  ] Image.CopyCtor (0 ms)
[ RUN      ] Image.CopyAssignmentOperator
unknown file: Failure
C++ exception with description "Lib: XMLRPC Timeout - can you `ping' the sensor?" thrown in the test body.
[  FAILED  ] Image.CopyAssignmentOperator (1 ms)
[ RUN      ] Image.References
unknown file: Failure
C++ exception with description "Lib: XMLRPC Timeout - can you `ping' the sensor?" thrown in the test body.
[  FAILED  ] Image.References (0 ms)
[ RUN      ] Image.CloudMechanics
unknown file: Failure
C++ exception with description "Lib: XMLRPC Timeout - can you `ping' the sensor?" thrown in the test body.
[  FAILED  ] Image.CloudMechanics (0 ms)
[ RUN      ] Image.XYZImage
unknown file: Failure
C++ exception with description "Lib: XMLRPC Timeout - can you `ping' the sensor?" thrown in the test body.
[  FAILED  ] Image.XYZImage (1 ms)
[ RUN      ] Image.ComputeCartesian
unknown file: Failure
C++ exception with description "Lib: XMLRPC Timeout - can you `ping' the sensor?" thrown in the test body.
[  FAILED  ] Image.ComputeCartesian (0 ms)
[ RUN      ] Image.TimeStamp
unknown file: Failure
C++ exception with description "Lib: XMLRPC Timeout - can you `ping' the sensor?" thrown in the test body.
[  FAILED  ] Image.TimeStamp (1 ms)
[ RUN      ] Image.IlluTemp
unknown file: Failure
C++ exception with description "Lib: XMLRPC Timeout - can you `ping' the sensor?" thrown in the test body.
[  FAILED  ] Image.IlluTemp (0 ms)
[----------] 10 tests from Image (4 ms total)

[----------] Global test environment tear-down
[==========] 10 tests from 1 test case ran. (4 ms total)
[  PASSED  ] 0 tests.
[  FAILED  ] 10 tests, listed below:
[  FAILED  ] Image.MoveCtor
[  FAILED  ] Image.MoveAssignmentOperator
[  FAILED  ] Image.CopyCtor
[  FAILED  ] Image.CopyAssignmentOperator
[  FAILED  ] Image.References
[  FAILED  ] Image.CloudMechanics
[  FAILED  ] Image.XYZImage
[  FAILED  ] Image.ComputeCartesian
[  FAILED  ] Image.TimeStamp
[  FAILED  ] Image.IlluTemp

10 FAILED TESTS
modules/image/test/CMakeFiles/check_image.dir/build.make:57: recipe for target 'modules/image/test/CMakeFiles/check_image' failed
make[3]: *** [modules/image/test/CMakeFiles/check_image] Error 1
CMakeFiles/Makefile2:700: recipe for target 'modules/image/test/CMakeFiles/check_image.dir/all' failed
make[2]: *** [modules/image/test/CMakeFiles/check_image.dir/all] Error 2
CMakeFiles/Makefile2:108: recipe for target 'CMakeFiles/check.dir/rule' failed
make[1]: *** [CMakeFiles/check.dir/rule] Error 2
Makefile:199: recipe for target 'check' failed
make: *** [check] Error 2

@Vinzz98 Can you run the following command (after you have built the software) from your build directory:
$ IFM3D_VLOG=20 GTEST_FILTER=CameraTest.FactoryDefaults make check

Then, please paste in the output of /tmp/ifm3d.INFO into a comment on this issue. It will help us understand the issue better.

Hello @tpanzarella ,
Thank you for your quick answer. The output when running your command from the ifm3d/build directory is:
CameraTest.FactoryDefaults make check
[ 22%] Built target ifm3d_camera_shared
[ 37%] Built target ifm3d_framegrabber_shared
[ 44%] Built target ifm3d_image_shared
[ 51%] Built target gtest
[ 59%] Built target gtest_main
[ 70%] Built target ifm3d-image-tests
Note: Google Test filter = CameraTest.FactoryDefaults
[==========] Running 0 tests from 0 test cases.
[==========] 0 tests from 0 test cases ran. (0 ms total)
[  PASSED  ] 0 tests.
[ 70%] Built target check_image
[ 88%] Built target ifm3d-camera-tests
Scanning dependencies of target check_camera
Note: Google Test filter = CameraTest.FactoryDefaults
[==========] Running 1 test from 1 test case.
[----------] Global test environment set-up.
[----------] 1 test from CameraTest
[ RUN      ] CameraTest.FactoryDefaults
/home/vinz/catkin_ws/src/ifm3d/modules/camera/test/ifm3d-camera-camera-tests.cpp:28: Failure
Expected: this->cam_->FactoryReset() doesn't throw an exception.
Actual: it throws.
/home/vinz/catkin_ws/src/ifm3d/modules/camera/test/ifm3d-camera-camera-tests.cpp:30: Failure
Expected: this->cam_->DeviceType() doesn't throw an exception.
Actual: it throws.
[  FAILED  ] CameraTest.FactoryDefaults (6003 ms)
[----------] 1 test from CameraTest (6003 ms total)
[----------] Global test environment tear-down
[==========] 1 test from 1 test case ran. (6003 ms total)
[  PASSED  ] 0 tests.
[  FAILED  ] 1 test, listed below:
[  FAILED  ] CameraTest.FactoryDefaults
1 FAILED TEST
modules/camera/test/CMakeFiles/check_camera.dir/build.make:57: recipe for target 'modules/camera/test/CMakeFiles/check_camera' failed
make[3]: *** [modules/camera/test/CMakeFiles/check_camera] Error 1
CMakeFiles/Makefile2:330: recipe for target 'modules/camera/test/CMakeFiles/check_camera.dir/all' failed
make[2]: *** [modules/camera/test/CMakeFiles/check_camera.dir/all] Error 2
CMakeFiles/Makefile2:108: recipe for target 'CMakeFiles/check.dir/rule' failed
make[1]: *** [CMakeFiles/check.dir/rule] Error 2
Makefile:199: recipe for target 'check' failed
make: *** [check] Error 2

Right. Can you paste in the output of the log file found at: /tmp/ifm3d.INFO. Thanks.

Log file created at: 2018/11/26 15:54:03
Running on machine: Vincent-MacBookPro
Log line format: [IWEF]mmdd hh:mm:ss.uuuuuu threadid file:line] msg
I1126 15:54:03.564774 11304 camera_impl.hpp:406] Increasing XML-RPC response size limit...
I1126 15:54:03.564962 11304 camera_impl.hpp:410] Initializing Camera: ip=<IP_ADDRESS>, xmlrpc_port=80, password=
I1126 15:54:03.564973 11304 camera_impl.hpp:414] XMLRPC URL Prefix=http://<IP_ADDRESS>:80
E1126 15:54:03.565232 11304 camera_impl.hpp:259] http://<IP_ADDRESS>:80/api/rpc/v1/com.ifm.efector/->getParameter:Unable to transport XML to server and get XML response back.  libcurl failed to execute the HTTP POST transaction, explaining:  Failed to connect to <IP_ADDRESS> port 80: Connection refused
W1126 15:54:03.565464 11304 camera.cpp:214] Could not probe device type: Lib: XMLRPC Timeout - can you ping' the sensor? W1126 15:54:03.565512 11304 camera.cpp:234] Returning instance of base camera class! E1126 15:54:03.565896 11304 camera_impl.hpp:259] http://<IP_ADDRESS>:80/api/rpc/v1/com.ifm.efector/->requestSession:Unable to transport XML to server and get XML response back.  libcurl failed to execute the HTTP POST transaction, explaining:  Failed to connect to <IP_ADDRESS> port 80: Connection refused E1126 15:54:03.565959 11304 camera_impl.hpp:193] Lib: XMLRPC Timeout - can you ping' the sensor?
E1126 15:54:09.566915 11304 camera_impl.hpp:259] http://<IP_ADDRESS>:80/api/rpc/v1/com.ifm.efector/->getParameter:Unable to transport XML to server and get XML response back.  libcurl failed to execute the HTTP POST transaction, explaining:  Failed to connect to <IP_ADDRESS> port 80: Connection refused
I1126 15:54:09.567260 11304 camera_impl.hpp:419] Dtor...

http://<IP_ADDRESS>:80/api/rpc/v1/com.ifm.efector/->requestSession:Unable to transport XML to server and get XML response back. libcurl failed to execute the HTTP POST transaction, explaining: Failed to connect to <IP_ADDRESS> port 80: Connection refused E1126

@Vinzz98 Do you have a password set on the camera?
@graugans Any insights on what on an O3X100 would cause a "connection refused" to the XML-RPC (HTTP) server?

http://<IP_ADDRESS>:80/api/rpc/v1/com.ifm.efector/->requestSession:Unable to transport XML to server and get XML response back. libcurl failed to execute the HTTP POST transaction, explaining: Failed to connect to <IP_ADDRESS> port 80: Connection refused E1126

@Vinzz98 Do you have a password set on the camera?
@graugans Any insights on what on an O3X100 would cause a "connection refused" to the XML-RPC (HTTP) server?

@tpanzarella I didn't set one but how could I check?

To disable the password, you will need the current password. Can you paste in the output of:
$ ifm3d ls

IIRC, this does not require a session with the camera.

@Vinzz98 With your camera plugged in, can you paste this URL into your web browser: http://<IP_ADDRESS>/api/rpc/v1/com.ifm.efector/. What do you get? Maybe you can attache a screen shot from your browser so we can see too?
Also, can you paste in the output of:
$ ifconfig

and the output of:
$ netstat -r

Thanks.

The output of $ ifconfig is:
ens9: flags=4163<UP,BROADCAST,RUNNING,MULTICAST>  mtu 1500
inet <IP_ADDRESS>  netmask <IP_ADDRESS>  broadcast <IP_ADDRESS>
inet6 fe80::6db:f994:c2a3:5879  prefixlen 64  scopeid 0x20
ether 38:c9:86:40:a7:ba  txqueuelen 1000  (Ethernet)
RX packets 78  bytes 12294 (12.2 KB)
RX errors 0  dropped 0  overruns 0  frame 1
TX packets 339  bytes 35979 (35.9 KB)
TX errors 0  dropped 0 overruns 0  carrier 0  collisions 0
device interrupt 19
lo: flags=73<UP,LOOPBACK,RUNNING>  mtu 65536
inet <IP_ADDRESS>  netmask <IP_ADDRESS>
inet6 ::1  prefixlen 128  scopeid 0x10
loop  txqueuelen 1000  (Local Loopback)
RX packets 37828  bytes 4287679 (4.2 MB)
RX errors 0  dropped 0  overruns 0  frame 0
TX packets 37828  bytes 4287679 (4.2 MB)
TX errors 0  dropped 0 overruns 0  carrier 0  collisions 0
wlp3s0: flags=4163<UP,BROADCAST,RUNNING,MULTICAST>  mtu 1500
inet <IP_ADDRESS>  netmask <IP_ADDRESS>  broadcast <IP_ADDRESS>
inet6 fe80::d212:37:5204:4bcb  prefixlen 64  scopeid 0x20
inet6 2001:67c:10ec:574b:8000::155  prefixlen 128  scopeid 0x0
ether a4:5e:60:d4:09:15  txqueuelen 1000  (Ethernet)
RX packets 290893  bytes 94232161 (94.2 MB)
RX errors 0  dropped 1  overruns 0  frame 0
TX packets 71332  bytes 10938974 (10.9 MB)
TX errors 0  dropped 0 overruns 0  carrier 0  collisions 0
The output of $ netstat -r is:

It looks like you have bound the IP address of the camera to your ethernet interface (ens9). <IP_ADDRESS> is the default IP of the camera. You need to set your address to something different.

I changed my IP and now everything works fine! Thank you very much for your quick help !


[FORK] Replace sponsor info

remove the sponsor this project info

@MatthewMiddlehurst I think you have fixed this? Can we close?

Old info is removed but theres nothing to replace it currently.

ok, I'll close this as the immediate task has been done


Getting error when I have a dependency and a required array inside of a oneOf.

Description
I have nested objects with a few dependencies in those objects. Whenever an inner object has dependencies making a field rquired based on another one having a value and if the object is required by the parent it throws an error
Error: [Formly Error] [Expression "templateOptions.required"] Cannot read property 'middleName' of undefined
It's going to be easier to see it than to explain it with words.
Minimal Reproduction
https://stackblitz.com/edit/issue-with-v21?file=src%2Fapp%2Fapp.component.ts
In the example if you remove the required array on line 67 the error goes away or if you remove the dependencies in line 62 it works. It's something about that combination that is making it break.
When it's broken you can see that the radio button doesn't actually change the fields that correspond to the value in the oneOf, when it works you can see the fields change when you change the option.
Your Environment

Angular version: 10.2.5
Formly version: 5.10.21

Additional context
We don't have these problems when running version 5.10.18, when we tried to upgrade to 5.10.21 our application became unusable because of this.
I did some testing and this issue starts showing on version 5.10.19

I think the issue might have been introduced by this commit
https://github.com/ngx-formly/ngx-formly/pull/2817/commits/28e7def1e708768453ddf9f3da46a5eb8e434102

Thanks for looking into this @aitboudad. Do you have an idea of when the next minor version of the npm package will be release?
Thank you!

This issue has been fixed and released as part of v5.10.22 release.
Please let us know, in case you are still encountering a similar issue/problem.
Thank you!


Allows the ability to configure bulkheads using config properties

Also addresses issue where semaphore bulkhead was used when threadpool config was supplied.
Fixes #224

@OathMeadow this PR addresses the issues in #224.  Let me know what you think.


Disable in-app update when in guided access mode

Hi AppCenter team,
When guided access is enabled on iPad, e.g., for a kiosk application, it would be great if the in-app update mechanism is disabled since it won't work. The system will kill the app to install the update but as soon as the app is killed, guided access relaunches it, and it will present the “Update available” alert again.
I know I could disable the update check for that specific use case but the developer has to think about that, and that particular situation might not arise during development. Would be great if that is handled on the SDK level. There is official API to check if guided access is enabled.
Thanks 🙏

PR is opened up @florianbuerger. Should get merged fairly soon, but will be a little while until we ship a new SDK with all the work going on right now.

HI @florianbuerger, going to move this to next month. Before merging the PR change to disable in-app updates in guided access mode we'd like to investigate a possible fix for it.

@florianbuerger - this has been merged into our master branch and should be shipped in the next SDK release early May. Thanks for submitting the issue!


add support for providing a list of IRIs in a file to track

Currently, preston track takes either stdin for tracking a content stream
e.g.,
cat foo.txt | preston track
, or a list of IRIs on the commandline.
preston track https://example.org
Suggest to add option to provide a list of IRIs in a file.
e.g.,
preston track -f really-long-list-of-IRIs.txt
where really-long-list-of-IRIs.txt contains IRIs to be tracked, one per line
e.g.,
https://example.org
https://example.org/ex1

feature available in v0.8.1


NCS 2.9.0 history cleanup

There are some checks failing for using fromlist instead of fromtree, but I think I will leave these as is.


Sometimes the Project Context is not loaded Unity 2020.1.0.bxx

Describe the bug
Sometimes when starting play mode the project context is not loaded.
To Fix it, you have to rename the prefab, start playmode, stop playmode, name it back to "ProjectContext", or just update the prefab somehow. The it is loaded for a while
To Reproduce
Steps to reproduce the behavior:
It is random but more frequent after updating Unity or a package
Expected behavior
The Project Context should be loaded everytime you go into playmode :)
Screenshots
If applicable, add screenshots to help explain your problem.
Extenject and Unity info (please complete the following information):

Zenject version: 9.1.0
Unity version: Unity 2020.1.0.b13 (but also happened in b11 and b12)
Project's scripting backend [e.g. Mono/IL2CPP]: Mono

Additional context

I tried this with 2020.1.0f1 but was unable to reproduce it.  Can you provide a minimal example?

Yea the problem is gone, since unity 2020.1 is out of beta

Ok thanks for letting us know

The problem reoccured with 2020.1.9f1.

And now it occurs not at random, but every time I startup Unity Zenject doesn't load the ProjectContext until I update it.
Happens in 2020.1.9 and later versions


Merge, rather than overwrite target fields.

3.0.0 did away with field and sub-field merging.  This is a regression.  This PR fixes that.
fixes #98

Hmm, this test fails:
https://github.com/untergeek/logstash-filter-geoip/blob/8ed594ad0f7432618a9ad7a3c0285d2958d27cfa/spec/filters/geoip_spec.rb#L240-L246
But ... the test is confusing. I don't understand the relationship between "look up an ipv6 address" and "the result should be empty" ? Maybe we remove this test?

(I don't think your PR changed this test, but since it is failing and I like green travis, I am in favor of removing the test unless we can figure out why it exists)
Otherwise, code review looks good!

Yeah.  The test does not make sense with the change to merge.  I'll remove it.

Actually, I just changed it to accurately test it, and updated the test titles.

LGTM

❤


Add email validation for signup form

Description
Added email validation format in sign up page, so that faulty email registration is avoided.

Placeholder: "Fixes #418

Screenshots (if applicable)
Add any screenshots that help explain or visualize the changes.

Checklist
Make sure to check off all the items before submitting. Mark with [x] if done.

[X ] I have performed a self-review of my code
[ X] I have commented my code, particularly in hard-to-understand areas
[ X] My changes generate no new warnings
[ X] I am working on this issue under GSSOC

hey please assign level 2 @Trisha-tech


ADD read-only automatically generated to dateCreated and dateModified attributes/metadata

This is a transversal change to all data models were dateCreated and dateModified are used. The changes in this PR are supported by this statement in the data model guidelines (https://github.com/Fiware/dataModels/tree/master/guidelines.md#date-attributes)

dateCreated and dateModified are special entity attributes provided off-the-shelf by NGSIv2 implementations. Be careful because they can be different than the actual creation or update date of the real world entity represented by its corresponding digital entity.

Note that this PR affects only to the way in which these attribute/metadata has to be consumed but the syntax keep the same. In other words, no JSON Schema was changed in this PR.
Additional specific line-comments are provided. Please have a look to them.
CC: @jmcanterafonseca @manucarrace @mrutid

cc: @chicco785

i am bit in a big mess ... it will take few days but I will look into it
On 24 May 2018 at 16:49, Jose M. Cantera<EMAIL_ADDRESS>wrote:

cc: @chicco785 https://github.com/chicco785
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/Fiware/dataModels/pull/246#issuecomment-391742807,
or mute the thread
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.

If the tweaking work consists in just adding extra atrributes for entities with have identified so (for which suggestions has been included in the PR) and taking into account that such additions are few I think is more effective (from a git-cracy point of view ;) to deal with it in this PR.


Introduce way of synchronizing MailChimp lists with users

What problem does this pull request solve?
Trello card: https://trello.com/c/iQOMKY1h/364-add-rake-task-to-automatically-add-new-users-to-mailchimp-mailing-lists
We have a database table full of user information, and we have some MailChimp lists that we'd like to contain all the same email addresses.
We're happy for the synchronization to happen out-of-band with regular user management activities, so we've built it as a Rake task that will be run on a schedule. The scheduling will be handled at the infrastructure level, in the forms-deploy repository.
Things to consider when reviewing

Ensure that you consider the wider context.
Does it work when run on your machine?
Is it clear what the code is doing?
Do the commit messages explain why the changes were made?
Are there all the unit tests needed?
Has all relevant documentation been updated?

In Mailchimp we currently for each contact as well as email address we have first name, last name and organisation. Can this script also handle that?

In Mailchimp we currently for each contact as well as email address we have first name, last name and organisation. Can this script also handle that?

The users database table and resulting model in Ruby records the user's name as a single field, but MailChimp has it as a first and last name fields. We could try to be clever with splitting on spaces, but I think we'd be asking to get it wrong a lot.
So I think we can do it, but I'm not convinced we should.

In Mailchimp we currently for each contact as well as email address we have first name, last name and organisation. Can this script also handle that?

The users database table and resulting model in Ruby records the user's name as a single field, but MailChimp has it as first and last name fields. We could try to be clever with splitting on spaces, but I think we'd be asking to get it wrong a lot.
So I think we can do it, but I'm not convinced we should.

That's a good point, I definitely agree we should not be doing the splitting. We might be able to configure Mailchimp to only have one name field.
But actually looking into our current Mailchimp audience in more detail it seems that for platform update emails I think we don't care too much about that extra information, so what you've got now should work.


Speedup[Question❓]

Thank you very much for your work.
I want to know whether can use GPU to accelerate matrix operation！

You can use CuPy to solve the linear system in the expert example (using the lemur test images).
from pymatting import *
import numpy as np
import scipy.sparse
import cupy
import cupyx.scipy.sparse.linalg
import time

scale = 1.0

image = load_image("lemur.png", "RGB", scale, "box")
trimap = load_image("lemur_trimap.png", "GRAY", scale, "nearest")

# height and width of trimap
h, w = trimap.shape[:2]

# calculate laplacian matrix
L = cf_laplacian(image)

# decompose trimap
is_fg, is_bg, is_known, is_unknown = trimap_split(trimap)

# constraint weight
lambda_value = 100.0

# build constraint pixel selection matrix
c = lambda_value * is_known
C = scipy.sparse.diags(c)

# build constraint value vector
b = lambda_value * is_fg

# build linear system
A = L + C

start_time = time.perf_counter()

# Build incomplete cholesky preconditioner
A = A.tocsr()
A.sum_duplicates()
M = ichol(A)

# solve linear system with conjugate gradient descent
x_cpu = cg(A, b, M=M)

elapsed_time = time.perf_counter() - start_time

print("Solving the linear system on CPU took", elapsed_time, "seconds")

start_time = time.perf_counter()

# build jacobi preconditioner
M = scipy.sparse.diags(1.0 / A.diagonal())

# transfer linear system from RAM to GPU memory
M = cupyx.scipy.sparse.csr_matrix(M)
A = cupyx.scipy.sparse.csr_matrix(A)
b = cupy.asarray(b)

# solve linear system
x_gpu, error = cupyx.scipy.sparse.linalg.cg(A, b, M=M, tol=1e-7)
assert(error == 0)

# transfer result to RAM from GPU memory
x_gpu = cupy.asnumpy(x_gpu)

elapsed_time = time.perf_counter() - start_time

print("Solving the linear system on GPU took", elapsed_time, "seconds")

print("Solution difference (mean squared error):", np.mean(np.square(x_gpu - x_cpu)))

# clip and reshape result vector
alpha = np.clip(x_gpu, 0.0, 1.0).reshape(h, w)

save_image("lemur_alpha.png", alpha)

However, there are some issues with this. The fastest method to solve these linear systems is conjugate gradient descent (CG) with a good preconditioner. The best preconditioner we found so far is the incomplete thresholded Cholesky preconditioner. With this preconditioner, CG converges in just a few iterations. The problem here is that this preconditioner can not be computed well in parallel, but GPUs are only fast for parallel tasks.
There are other preconditioners, like for example the Jacobi preconditioner, which can be computed in parallel. But with this preconditioner, CG takes hundreds or thousands of iterations to converge.
Another problem is that NVIDIA gaming GPUs have 64 times worse double precision performance compared to single precision (see https://en.wikipedia.org/wiki/List_of_Nvidia_graphics_processing_units#GeForce_30_series for reference), probably to make people buy the expensive premium GPUs. Unfortunately, alpha matting might run into convergence issues with single precision floating point.
Anyway, I get the following numbers with the code from above using an Intel Xeon Gold 6134 CPU and a Tesla-P100 GPU:
Solving the linear system on CPU took 1.2201764308847487 seconds
Solving the linear system on GPU took 1.1049338467419147 seconds
Solution difference (mean squared error): 7.32248139148202e-07

The GPU is slightly faster, but also costs twice as much as the CPU, which is running single threaded, so it still has performance to spare. Numba does not yet support multi-threading with ahead-of-time-compiled code, but when it does in the future, the CPU solver will probably be faster than the GPU solver.
We also provide a V-Cycle preconditioner, which could be implemented to run in parallel on the GPU and has reasonable convergence properties. Unfortunately, the memory cost is huge, especially for large images, so it is probably not worth the trouble.

You can use CuPy to solve the linear system in the expert example (using the lemur test images).
from pymatting import *
import numpy as np
import scipy.sparse
import cupy
import cupyx.scipy.sparse.linalg
import time

scale = 1.0

image = load_image("lemur.png", "RGB", scale, "box")
trimap = load_image("lemur_trimap.png", "GRAY", scale, "nearest")

# height and width of trimap
h, w = trimap.shape[:2]

# calculate laplacian matrix
L = cf_laplacian(image)

# decompose trimap
is_fg, is_bg, is_known, is_unknown = trimap_split(trimap)

# constraint weight
lambda_value = 100.0

# build constraint pixel selection matrix
c = lambda_value * is_known
C = scipy.sparse.diags(c)

# build constraint value vector
b = lambda_value * is_fg

# build linear system
A = L + C

start_time = time.perf_counter()

# Build incomplete cholesky preconditioner
A = A.tocsr()
A.sum_duplicates()
M = ichol(A)

# solve linear system with conjugate gradient descent
x_cpu = cg(A, b, M=M)

elapsed_time = time.perf_counter() - start_time

print("Solving the linear system on CPU took", elapsed_time, "seconds")

start_time = time.perf_counter()

# build jacobi preconditioner
M = scipy.sparse.diags(1.0 / A.diagonal())

# transfer linear system from RAM to GPU memory
M = cupyx.scipy.sparse.csr_matrix(M)
A = cupyx.scipy.sparse.csr_matrix(A)
b = cupy.asarray(b)

# solve linear system
x_gpu, error = cupyx.scipy.sparse.linalg.cg(A, b, M=M, tol=1e-7)
assert(error == 0)

# transfer result to RAM from GPU memory
x_gpu = cupy.asnumpy(x_gpu)

elapsed_time = time.perf_counter() - start_time

print("Solving the linear system on GPU took", elapsed_time, "seconds")

print("Solution difference (mean squared error):", np.mean(np.square(x_gpu - x_cpu)))

# clip and reshape result vector
alpha = np.clip(x_gpu, 0.0, 1.0).reshape(h, w)

save_image("lemur_alpha.png", alpha)

However, there are some issues with this. The fastest method to solve these linear systems is conjugate gradient descent (CG) with a good preconditioner. The best preconditioner we found so far is the incomplete thresholded Cholesky preconditioner. With this preconditioner, CG converges in just a few iterations. The problem here is that this preconditioner can not be computed well in parallel, but GPUs are only fast for parallel tasks.
There are other preconditioners, like for example the Jacobi preconditioner, which can be computed in parallel. But with this preconditioner, CG takes hundreds or thousands of iterations to converge.
Another problem is that NVIDIA gaming GPUs have 64 times worse double precision performance compared to single precision (see https://en.wikipedia.org/wiki/List_of_Nvidia_graphics_processing_units#GeForce_30_series for reference), probably to make people buy the expensive premium GPUs. Unfortunately, alpha matting might run into convergence issues with single precision floating point.
Anyway, I get the following numbers with the code from above using an Intel Xeon Gold 6134 CPU and a Tesla-P100 GPU:
Solving the linear system on CPU took 1.2201764308847487 seconds
Solving the linear system on GPU took 1.1049338467419147 seconds
Solution difference (mean squared error): 7.32248139148202e-07

The GPU is slightly faster, but also costs twice as much as the CPU, which is running single threaded, so it still has performance to spare. Numba does not yet support multi-threading with ahead-of-time-compiled code, but when it does in the future, the CPU solver will probably be faster than the GPU solver.
We also provide a V-Cycle preconditioner, which could be implemented to run in parallel on the GPU and has reasonable convergence properties. Unfortunately, the memory cost is huge, especially for large images, so it is probably not worth the trouble.

You can use CuPy to solve the linear system in the expert example (using the lemur test images).
from pymatting import *
import numpy as np
import scipy.sparse
import cupy
import cupyx.scipy.sparse.linalg
import time

scale = 1.0

image = load_image("lemur.png", "RGB", scale, "box")
trimap = load_image("lemur_trimap.png", "GRAY", scale, "nearest")

# height and width of trimap
h, w = trimap.shape[:2]

# calculate laplacian matrix
L = cf_laplacian(image)

# decompose trimap
is_fg, is_bg, is_known, is_unknown = trimap_split(trimap)

# constraint weight
lambda_value = 100.0

# build constraint pixel selection matrix
c = lambda_value * is_known
C = scipy.sparse.diags(c)

# build constraint value vector
b = lambda_value * is_fg

# build linear system
A = L + C

start_time = time.perf_counter()

# Build incomplete cholesky preconditioner
A = A.tocsr()
A.sum_duplicates()
M = ichol(A)

# solve linear system with conjugate gradient descent
x_cpu = cg(A, b, M=M)

elapsed_time = time.perf_counter() - start_time

print("Solving the linear system on CPU took", elapsed_time, "seconds")

start_time = time.perf_counter()

# build jacobi preconditioner
M = scipy.sparse.diags(1.0 / A.diagonal())

# transfer linear system from RAM to GPU memory
M = cupyx.scipy.sparse.csr_matrix(M)
A = cupyx.scipy.sparse.csr_matrix(A)
b = cupy.asarray(b)

# solve linear system
x_gpu, error = cupyx.scipy.sparse.linalg.cg(A, b, M=M, tol=1e-7)
assert(error == 0)

# transfer result to RAM from GPU memory
x_gpu = cupy.asnumpy(x_gpu)

elapsed_time = time.perf_counter() - start_time

print("Solving the linear system on GPU took", elapsed_time, "seconds")

print("Solution difference (mean squared error):", np.mean(np.square(x_gpu - x_cpu)))

# clip and reshape result vector
alpha = np.clip(x_gpu, 0.0, 1.0).reshape(h, w)

save_image("lemur_alpha.png", alpha)

However, there are some issues with this. The fastest method to solve these linear systems is conjugate gradient descent (CG) with a good preconditioner. The best preconditioner we found so far is the incomplete thresholded Cholesky preconditioner. With this preconditioner, CG converges in just a few iterations. The problem here is that this preconditioner can not be computed well in parallel, but GPUs are only fast for parallel tasks.
There are other preconditioners, like for example the Jacobi preconditioner, which can be computed in parallel. But with this preconditioner, CG takes hundreds or thousands of iterations to converge.
Another problem is that NVIDIA gaming GPUs have 64 times worse double precision performance compared to single precision (see https://en.wikipedia.org/wiki/List_of_Nvidia_graphics_processing_units#GeForce_30_series for reference), probably to make people buy the expensive premium GPUs. Unfortunately, alpha matting might run into convergence issues with single precision floating point.
Anyway, I get the following numbers with the code from above using an Intel Xeon Gold 6134 CPU and a Tesla-P100 GPU:
Solving the linear system on CPU took 1.2201764308847487 seconds
Solving the linear system on GPU took 1.1049338467419147 seconds
Solution difference (mean squared error): 7.32248139148202e-07

The GPU is slightly faster, but also costs twice as much as the CPU, which is running single threaded, so it still has performance to spare. Numba does not yet support multi-threading with ahead-of-time-compiled code, but when it does in the future, the CPU solver will probably be faster than the GPU solver.
We also provide a V-Cycle preconditioner, which could be implemented to run in parallel on the GPU and has reasonable convergence properties. Unfortunately, the memory cost is huge, especially for large images, so it is probably not worth the trouble.

Well! Thank you very much for your source code scheme and experimental data.
In fact, the problem I encountered is that when my sample images are not so hairy, in other words, the scene I want to solve is for alpha matting and cutout of person!
In my case, using the library you provided, it seems that there is no optimization for this scenario.
Yes it is! I also found out that using cupy, even if CG is performed on the GPU, the performance is really not very surprising! CG is indeed a big bottleneck, although we still don't think about real-time performance.
In addition, I found another library, which runs on the cpu, and its operating speed is acceptable.

Macro Forte's implementation has an optimization which improves performance if most pixels are already known. Can you share your image and the trimap so we can see if that is the reason?
Also, we recently introduced a similar optimization in version 1.1.3 for the estimate_alpha_cf function. It should be slightly faster if the trimap is mostly black and white. Maybe you can give it a try.
Here is an example which downloads the lemur test image/trimap and estimates the alpha matte with estimate_alpha_cf:
import time, os
from urllib.request import urlopen
from pymatting import estimate_alpha_cf, load_image, save_image

def download_file(url, filename):
    if os.path.isfile(filename): return
    with urlopen(url) as r:
        with open(filename, "wb") as f:
            f.write(r.read())

download_file("https://github.com/pymatting/pymatting/raw/master/data/lemur/lemur.png", "lemur.png")
download_file("https://github.com/pymatting/pymatting/raw/master/data/lemur/lemur_trimap.png", "lemur_trimap.png")

image = load_image("lemur.png", "RGB")
trimap = load_image("lemur_trimap.png", "GRAY")

for test in range(3):
    t = time.perf_counter()

    alpha = estimate_alpha_cf(image, trimap)

    dt = time.perf_counter() - t

    print("test", test, "-", dt, "seconds")

save_image("alpha.png", alpha)

For me, this takes 0.6 seconds for the lemur image while the code you linked takes 3 seconds. Times vary a bit when run multiple times (+-0.2 seconds).

Closed due to inactivity. If you find that this issue still exists, feel free to re-open.


TS2339: Property 'colors' does not exist on type 'ConstantsAPI' in Figma Plugin API

I'm working on a Figma plugin using the Figma Plugin API and TypeScript. I'm trying to access the figma.constants.colors object to get the FigJam base colors, but I'm encountering a TypeScript error.
Here's the code snippet that's causing the issue:
console.log(figma.constants.colors.figJamBase);

The error message I'm getting is:
TS2339: Property 'colors' does not exist on type 'ConstantsAPI'.

According to the Figma Plugin API documentation, the figma.constants.colors object should provide a set of color palettes, including figJamBase and figJamBaseLight, which map the names of all the FigJam base and light colors to their corresponding hex values.
I'm not sure why I'm getting this error. Any help would be appreciated.

Hi! This definitely seems to be incorrect in our typings file. You should be able to use figma.constants.colors.figJamBase safely, and we will update the typings so that they are correct!


Send bot metadata to client on connect

If we send metadata to the connecting client such as the URL of the REST server, we can alleviate the need to pass that configuration around in different places (the designer, the farmbotjs client, etc). #todos

We do this now.
All bot data is inside of the Auth token, so you only need a web app URL and a token now.


The CSRF session token is missing.

Actual Behavior
Everything works fine when the user is logged in, 400 Bad Request happens when I try to log the user in... same behavior is when I try to register a user (csrf_token is missing in the session when the user is anonymous)... have I missed something to configure maybe?
Note: We are not using the wtforms, we have our own custom scheme.
Thanks!
Environment

Python version: Python 3.9.12
wtforms version: WTForms==3.0.1

Hi. Please provide a reproducible example of your issue, ideally some piece of code we can copy/paste so we can see the behavior you are describing. Your messages just don't contain enough information so we can help you.

Note: We are not using the wtforms, we have our own custom scheme.

I don't understand. Are you or are you not using wtforms?

@azmeuk  Thanks for your quick reply, I now realized that I opened the issue in the wrong repo, it was meant for flask_wtf can we move this issue to flask_wtf please, or should I close here and reopen it in flask-wtf?
btw we are only using the CSRF protection, without wtforms, as I said. we have our own custom schema.
Thanks!


Naked domain to www domain redirection is broken

description
Calls to https://example.com no longer redirect to https://www.example.com
A 403 error is returned instead.
This is a regression introduced by #2.
It's possible an "S3 Origin" does not work correctly if the bucket is set to "Redirect requests", or it might need different bucket policies.
@tnleeuw can you please have a look?

I will have a look, I did not experience this myself. I might have to split
the origin definitions?
It might also be that it will take a little longer before AWS properly
picks it up?
It can take up to an hour before the redirects work correctly according to
posts which I've read. Until then, CloudFront might redirect to the bucket
URL which is private, therefore results in a 403.
--Tim
On Fri, 13 Apr 2018 at 20:29, Francesco Negri<EMAIL_ADDRESS>wrote:

description
Calls to https://example.com no longer redirect to https://www.example.com
A 403 error is returned instead.
This is a regression introduced by #2
https://github.com/buildo/terraform-aws-website/pull/2.
It's possible an "S3 Origin" does not work correctly if the bucket is set
to "Redirect requests", or it might need different bucket policies.
@tnleeuw https://github.com/tnleeuw can you please have a look?
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/buildo/terraform-aws-website/issues/4, or mute the
thread
https://github.com/notifications/unsubscribe-auth/ADitDSLPsRnBUqfe6i9W03kVjr1XUWg_ks5toO5ugaJpZM4TT4m0
.

Well I was sure that the redirection had worked but indeed on my site it
doesn't work (anymore) either.... I think I know how to fix this, will
probably have time to look at it Sunday / Monday.
My apologies for causing this regression 😕
On Fri, 13 Apr 2018 at 22:22, Tim van der Leeuw<EMAIL_ADDRESS>wrote:

I'll also have another look at it, either this weekend or Monday.
On Fri, 13 Apr 2018 at 22:21, Francesco Negri<EMAIL_ADDRESS>wrote:

@tnleeuw https://github.com/tnleeuw I've waited a few hours and it's
still not working. It's good to know it's working for you, though.  Thanks for your help. :)
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Some additional info:
the bucket itself is redirecting
$ curl -L http://testone.our.buildo.io.s3-website-eu-west-1.amazonaws.com
Testone

but Cloudformation isn't
$ curl -L https://testone.our.buildo.io
<?xml version="1.0" encoding="UTF-8"?>
<Error>AccessDenied<Message>Access Denied</Message><RequestId>25E0438A27AEE110</RequestId><HostId>aW60i6XKBHmAFTaHGZuTLnzkzzK2UVryq78AXUEd37XZFM8zPpCVo/YxvxgKYlA3U34Dk

All the resources, including the buckets, were created from scratch. I had to hardcode aws_route53_zone.zone.name in the module because I only have a hosted zone for buildo.io and not for testone.our.buildo.io, but it seems unlikely to be the cause of the problem.

but Cloudformation isn't

you mean Cloudfront?

Indeed I don't think that that would cause the problem. Thanks for the
additional info.
I think I'll have to change the code to create the CDN's separately, with
different origin configs. Alternatively to create the redirect bucket with
an Origin Policy similar to the first.
On Fri, 13 Apr 2018 at 22:30, Francesco Negri<EMAIL_ADDRESS>wrote:

Some additional info:
the bucket itself is redirecting
$ curl -L http://testone.our.buildo.io.s3-website-eu-west-1.amazonaws.com
Testone
but Cloudformation isn't
$ curl -L https://testone.our.buildo.io

AccessDeniedAccess Denied25E0438A27AEE110aW60i6XKBHmAFTaHGZuTLnzkzzK2UVryq78AXUEd37XZFM8zPpCVo/YxvxgKYlA3U34Dk
All the resources, including the buckets, were created from scratch. I had
to hardcode aws_route53_zone.zone.name in the module because I only have
a hosted zone for buildo.io and not for testone.our.buildo.io, but it
seems unlikely to be the cause of the problem.
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you mean Cloudfront?

Yes, obviously 😄
I edited my previous comment!

My apologies for causing this regression 😕

No problem, and thanks for working on this. Have a nice weekend!

Thanks and enjoy the weekend too!
On Fri, 13 Apr 2018 at 22:39, Francesco Negri<EMAIL_ADDRESS>wrote:

My apologies for causing this regression 😕
No problem, and thanks for working on this. Have a nice weekend!
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PR https://github.com/buildo/terraform-aws-website/pull/5 fixes the issue for me.


mobile version too tall

on pixel for instance:

better but the down arrow is just missing

so beautiful above the fold now ! thanks !


Use bash, exit on error of any command

Use bash, exit on error of any command (set -e)

Thanks! I am good to use bash. There may be cases where some command fails but the script is fine to continue executing - for instance if the encrypted nvram or vmsd file does not exist. Let me know if you think there are alternatives we should have in place - if not we can merge in the bash update.


How to add custom features in Alpha158? 如何在Alpha158中加入其它自定义的特征？

How to append custom features in Alpha158? 如何在Alpha158中加入其它自定义的特征？
Question 1
Hi! Qlib has already built some excellent datasets (including Alpha158 & Alpha360) with satisfying training & backtesting results. However, I am still wondering whether some custom features could be appended besides Alpha158 or not. Those custom features may include some features related to financial reports, and other technical features that haven't been involved in  Alpha158 yet. If so, how can I achieve this in codes?
您好！Qlib已经建立了一些优秀的数据集（包括Alpha158和Alpha360），它们具有令人满意的训练和回测结果。不过，我还想知道，基于Alpha158的数据集，是否还可以添加一些自定义特征。这些自定义特征可能会包括一些与公司财务报告相关的特征，以及尚未纳入Alpha158的其他技术指标。如果可以的话，应当如何在代码中实现这一点？
Question 2
I also have another question related to Alpha158. I notice that there are 2 types of pre-processing approaches towards Alpha158: one in workflow_config_mlp_Alpha158.yaml, the other in workflow_config_gru_Alpha158.yaml.
我还有一个关于Alpha158的问题。我注意到有2种预处理Alpha158的方式：一种在workflow_config_mlp_Alpha158.yaml中，而另一种在workflow_config_gru_Alpha158.yaml中。
The former drops a column VWAP0, fills NaN with CSZFillna, and then normalizes the dataset with CSZScoreNorm.
前者删去了VWAP0列，使用横截面均值——CSZFillna的方式补缺，并使用横截面Z分数CSZScoreNorm标准化。
data_handler_config: &data_handler_config
    start_time: 2008-01-01
    end_time: 2020-08-01
    fit_start_time: 2008-01-01
    fit_end_time: 2014-12-31
    instruments: *market
    infer_processors: [
        {
            "class" : "DropCol",
            "kwargs":{"col_list": ["VWAP0"]}
        },
        {
             "class" : "CSZFillna",
             "kwargs":{"fields_group": "feature"}
        }
    ]
    learn_processors: [
        {
            "class" : "DropCol",
            "kwargs":{"col_list": ["VWAP0"]}
        },
        {
            "class" : "DropnaProcessor",
            "kwargs":{"fields_group": "feature"}
        },
        "DropnaLabel",
        {
            "class": "CSZScoreNorm",
            "kwargs": {"fields_group": "label"}
        }
    ]
    process_type: "independent"

The latter chooses 20 columns, fills NaN with Fillna, and then normalizes the dataset with RobustZScoreNorm & CSRankNorm.
后者选择了20列，使用0——Fillna的方式补缺，并使用稳健Z分数RobustZScoreNorm和横截面排序百分数CSRankNorm标准化。
data_handler_config: &data_handler_config
    start_time: 2008-01-01
    end_time: 2020-08-01
    fit_start_time: 2008-01-01
    fit_end_time: 2014-12-31
    instruments: *market
    infer_processors:
        - class: FilterCol
          kwargs:
              fields_group: feature
              col_list: ["RESI5", "WVMA5", "RSQR5", "KLEN", "RSQR10", "CORR5", "CORD5", "CORR10",
                            "ROC60", "RESI10", "VSTD5", "RSQR60", "CORR60", "WVMA60", "STD5",
                            "RSQR20", "CORD60", "CORD10", "CORR20", "KLOW"
                        ]
        - class: RobustZScoreNorm
          kwargs:
              fields_group: feature
              clip_outlier: true
        - class: Fillna
          kwargs:
              fields_group: feature
    learn_processors:
        - class: DropnaLabel
        - class: CSRankNorm
          kwargs:
              fields_group: label
    label: ["Ref($close, -2) / Ref($close, -1) - 1"]

So, what are the reasons for using 2 different types of pre-processing approaches towards Alpha158? Are the pre-processing approaches related to models (the former for MLP while the latter for RNN)?
那么，对Alpha158数据集使用2种预处理方式的原因是什么？预处理方式是否与模型相关（前者用于MLP，而后者用于RNN）？
Thanks in advance!
谢谢！

I can answer your first question.
Sure, you can customize your datahandler by inheriting Alpha158 and rewriting its get_feature_config method, and you can call your customized handler like this link. The features related to financial reports is supported since Version v0.8.5, and an example of how to use the financial report feature is at this link, you can read the related docs for more details (such as how to prepare raw financial data)


Use Vec instead of Slice in ColumnReader

Is your feature request related to a problem or challenge? Please describe what you are trying to do.

Currently ColumnValueDecoderImpl and by extension ColumnReader accepts slices of [T::T] where T: DataType.
This was preserved by #1041 which extracted generics to allow using owned buffer constructions instead for the arrow read path, whilst preserving the existing API for non-arrow readers.
However, preserving this API has a couple of fairly substantial drawbacks:

A lot of the test coverage in the parquet crate uses the arrow APIs which use different implementations of ColumnValueDecoder
The finite capacity of the output buffers introduces challenges related to record truncation - https://github.com/apache/arrow-rs/issues/5150
The generics are pretty arcane and require some gymnastics to allow for slices that don't have a size separate from their capacity
Buffers must be pre-allocated and zeroed ahead of time, which is not only an unnecessary overhead, but for list will likely necessitate re-allocation once the correct number of values is ascertained

Describe the solution you'd like

I would like to update ColumnValueDecoderImpl to accept Vec<T> instead of [T::T]. This would not only simplify RecordReader, and improve its performance for nested data, but would eliminate issues like #5150
Describe alternatives you've considered

Additional context

label_issue.py automatically added labels {'parquet'} from #5193

label_issue.py automatically added labels {'parquet-derive'} from #5193

Hello together,
maintainer of odbc2parquet here. While there are certainly good reasons for this request, I mourn the loss of the old API. It allowed me to directly fill the buffers which were already bound to an existing cursor via the ODBC C-API. I can not use a Vec since reallocating/resizing it would invalidate the pointers. As of now I see no other way to use the newest parquet version other than to introduce an extra allocation.
Don't have any measurements around this, but hurts me a little.
Just some feedback. Keep up the good work.

I should add I only have to pessimize insertion and also only if the parquet and ODBC type are binary identical for required columns. So its not the most important thing in the world. Yet it was nice that in this case no additional copy had been needed.

allowed me to directly fill the buffers which were already bound to an existing cursor via the ODBC C-API

If it makes you feel any better, this would likely be subtly incorrect for data with repetition levels :smile:

Don't have any measurements around this, but hurts me a little.

I would be interested in any numbers where this represents a regression, mainly because https://github.com/apache/arrow-rs/pull/5193 represented a non-trivial performance uplift in many cases.

If it makes you feel any better, this would likely be subtly incorrect for data with repetition levels 😄

Only had flat, table like data, so I might have been lucky in the past.

I would be interested in any numbers where this represents a regression, mainly because https://github.com/apache/arrow-rs/pull/5193 represented a non-trivial performance uplift in many cases. I'd be willing to consider alternative suggestions to fixing https://github.com/apache/arrow-rs/issues/5150 if this represents a major regression for your workloads.

I have little reason to doubt you. Some tests are still failing, but I will just update. I would not have the time to set a benchmark up. Even if I would, there are so many variables (type of column, number of rows etc.) that its outcome unless mindbogglingly significant would not allow any conclusions. Nice to hear that you had some nice speedups though.


Laravel 10.x Shift

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[ ] laravel/ui

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[WIP] Add quasi-discrete spherical Bessel transform

This PR is built on #2 and adds the spherical Hankel transform discussed in #1. I ended up implementing the hyperspherical case actually, since it was only marginally more difficult than the cylindrical and spherical cases.
I still need to write tests and document the transform. I also need to verify that the approximation at the bottom of https://chrisbrahms.github.io/Hankel.jl/dev/derivations/#Integration-of-functions-1 follows in the general case.

Okay, all of the QDSHT functionality should be implemented and tested, so this PR is ready for review.
I still need to document the QDSHT type and a few methods (but these will be nearly identical to those for QDHT), and something about QDSHT should go in the docs; how would you like that to be structured?

Nice work!

Thanks! Your code, tests, and derivation were very nice, so it made it relatively easy to extend.

Since you've generalised this over dimensions as well, and just using n=1 results in the QDHT, it seems to me that having QDHT and QDSHT be separate entities makes little sense. So QDHT could just become the overarching type for everything, defaulting to p=0 and n=1, and perhaps an alias QDSHT could default to the spherical case. Or am I missing something?

No, you're quite right. The two should be entirely equivalent, and this is also currently tested.

The only thing to check would be that performance is identical (I use QDHTs in hot loops) but I can't see why it wouldn't be.

As for performance, there might be a slight decrease in performance moving from QDHT to QDSHT with n=1 from control flow checking n and a few powers, but it will be small, and it will be entirely handled in set-up. The only other performance decrease could come if you call onaxis in a loop, since we don't have the J00 constant anymore and have to compute it ourselves. But I'll test to make sure. Adding n to the type signature for QDHT would handle this and make aliasing easier.

re: docs, is there a reference that shows how to derive the SHT as a re-parameterisation of the HT? If not, ideally you'd take the time to add that to the derivations page.

No, there's not. There is a reference that generalizes the QDHT to the half-integer order (it actually predates the Yu paper but IIRC didn't do as extensive error analysis): https://doi.org/10.1016/0010-4655(87)90204-9. And no papers that I've seen handled the hyperspherical bessel function case, so I can add those derivations.

Since your new code encompasses pretty much everything from before, you could just edit the main docs page with the more general definitions and leave the QDHT as an important special case.

Sounds good! I'll get started harmonizing the two. I'll probably along the way remove the AbstractQDHT introduced in #2, since I don't anticipate another QDHT plan.

Actually, since the proposed changes would interact with a lot of the changes in #2, I'll wait until that PR is finalized and merged.

re: #2 vs #3, doesn't the proposed unification of QDHT and QDHST make most of #2 unnecessary? Essentially, you'd just edit QDHT to handle arbitrary dimensions and orders instead of adding abstraction and splitting into 2 types. The reorganisation into qdht.jl and utils.jl still makes sense to me. The only thing we'd lose with this approach is the specificity of the docstrings. I'm open to counterarguments though!

As for performance, there might be a slight decrease in performance moving from QDHT to QDSHT with n=1 from control flow checking n and a few powers, but it will be small, and it will be entirely handled in set-up. The only other performance decrease could come if you call onaxis in a loop, since we don't have the J00 constant anymore and have to compute it ourselves. But I'll test to make sure. Adding n to the type signature for QDHT would handle this and make aliasing easier.

Slowing down the constructor a little bit isn't a problem, at least not for me. It's the actual transform that needs to be fast (hence the convoluted definitions of dot!). Having both p and n part of the type signature absolutely makes sense, and then we could even keep the J00 constant and use that in the special case of n=1, p=0.

No, there's not. There is a reference that generalizes the QDHT to the half-integer order (it actually predates the Yu paper but IIRC didn't do as extensive error analysis): https://doi.org/10.1016/0010-4655(87)90204-9. And no papers that I've seen handled the hyperspherical bessel function case, so I can add those derivations.

Yes, that would be great. Makes me think that somebody should publish that...?

re: #2 vs #3, doesn't the proposed unification of QDHT and QDHST make most of #2 unnecessary? Essentially, you'd just edit QDHT to handle arbitrary dimensions and orders instead of adding abstraction and splitting into 2 types. The reorganisation into qdht.jl and utils.jl still makes sense to me. The only thing we'd lose with this approach is the specificity of the docstrings. I'm open to counterarguments though!

Good point, yeah, I'll open a new PR that copies over the minimal necessary changes from each PR.
Perhaps you already did this, but I also stumbled upon a more formal way to explain the approximation in https://chrisbrahms.github.io/Hankel.jl/dev/derivations/#Integration-of-functions-1 and (probably) also quantify its error. I'll include it in the derivation.

No, there's not. There is a reference that generalizes the QDHT to the half-integer order (it actually predates the Yu paper but IIRC didn't do as extensive error analysis): https://doi.org/10.1016/0010-4655(87)90204-9. And no papers that I've seen handled the hyperspherical bessel function case, so I can add those derivations.

Yes, that would be great. Makes me think that somebody should publish that...?

It'd be a pretty simple little paper and (probably?) not too hard to write, but I'll start with updating derivation.md and then see if I (we) want to polish it into a paper.

Good point, yeah, I'll open a new PR that copies over the minimal necessary changes from each PR.

Good plan!

Perhaps you already did this, but I also stumbled upon a more formal way to explain the approximation in https://chrisbrahms.github.io/Hankel.jl/dev/derivations/#Integration-of-functions-1 and (probably) also quantify its error. I'll include it in the derivation.

I basically found out that this works by accident, verified it numerically and did a little digging but couldn't find a more formal explanation. Adding that would be very useful!

I basically found out that this works by accident, verified it numerically and did a little digging but couldn't find a more formal explanation. Adding that would be very useful!

Yeah, I stumbled upon it by accident too. It turns out that the inner sum is a truncated expansion of the Fourier-Bessel series of the function f(r) = 1/2. Hence the absolute error of using 1/2 is just the truncation error.


have client side error

Why I got this error?

@Paulewas use Discord for support. Issues here are reserved for valid issues with the resource itself


App starting is slow when using EncryptedStorage with redux on Android

I was looking for a redux encrypted storage. I tried several other libraries, but none of them worked properly on Android till I came across this one. In this library, every thing is working properly, but the time between after the splash screen is done and the home screen rendering is a little bit slow, takes about 3 seconds, and sometimes randomly takes up to 6 seconds. Is there any configurations that can be done to make the decryption process faster, or maybe some part of the native code on Android needs to be optimized?

Are you performing multiple RNEncryptedStorage.getIem() at startup? This could explain the delay since the library doesn't yet expose a multiGet() so all calls are made individually.


Search for cross-seeds with data instead of torrents

#145
Previously #300
This commit allows for searching of cross-seeds using downloaded data instead of existing .torrent files. It adds two paramters, dataDirs, a list of directories of content to search through, and dataMode, which determines whether to use safe (exact) or risky (exact size, flexible name, single file/nested single file only) matching. Risky mode will require manual intervention to resume torrents, though it should result in more matches.
Limitations:

Currently only works in qBittorrent.
Must recheck any torrents added in risky mode
Will not automatically resume torrents
No daemon mode

Found a bug I need to sort out, lots of dataDirs checks fail if dataDirs is undefined (as it would be with an old config) since there are few actual null checks.

next step: move some of the reusable logic from QBittorrent.ts into dataFiles.ts

PSA - anyone running on the pr-344 or search_torrents_with_data tag now needs to specify a linkDir in config

ok i think i got all the nits. please remind me if i'm missing anything, but i think the remaining todos are:
now

[ ] merge searchees from loadTorrentDirLight and findSearcheesFromAllDataDirs (this might need some deduplication)
[ ] something about daemon mode?

[ ] webhook - is this done? not sure where we left it - happy to help but pls refresh my memory
[ ] rss - pretty sure this one's not done

[ ] hook up --single-searchee/--roots (or decide not to)
[ ] do a shitload of regression testing (me)
[ ] verify that behavior of findPotentialNestedRoots is indeed what we want (me)

later

we can clean up linking to only copy files that exist in the candidate

map all of the file paths in candidate over path.dirname, dedupe / create all of those dirs, then create all the files

Webhook: The webhook itself works with the param "path", however for some reason it seems torrents are not getting returned by indexers or they aren't getting compared for some reason. Please do look into it
--single-searchee: I think we can drop this command, but there does need to be some way for the webhook to search for matches based on a single specified file which is not possible right now.

oh also, with the removal of nonceOptions, this PR may now require a major version bump. Not sure how many people actually were depending on it though because I don't remember announcing it, it was only really relevant for Action.SAVE or rtorrent injection, and with rtorrent, it was just about where the temporary torrent file got saved during the injection process.

still trying to find some time to look at daemon mode, I haven't forgotten

ok i believe the issue with daemon mode is fixed. I'm inclined not to support RSS in this PR but we can work on that as a follow up


Push-Based Path Quality Aware Beaconing (WIP)

As my bachelor thesis, I intend to implement this algorithm into the SCION codebase. I've outline the reasoning, algorithm, and intended changes to the codebase in this design document. I hereby ask for comment on it's rationale and implementation details, after which I plan to start implementation.
Outline
During core beaconing, core ASs continuously have to decide which beacons to forward to which interfaces in order to keep the message complexity sufficiently low. Traditional algorithms have focussed on selecting paths with low hop count[2] or high diversity w.r.t. links travelled [3]. The goal of either is to provide each AS with a high quality set of paths to every other AS, such that their target application can (hopefully) select one that suits its needs.
Since service providers know which optimality criteria is required for each type of services (application) they provide, and they have customers all around world in all ISDs (and therefor core ASes), it is reaonable to let origin ASes to specify the optimality criteria of the path originating from them.
The changes outlined in the design document, and implemented in this PR, allow core-ASs to

specify optimality criteria which should be marked in beacons originating from specific interfaces of the AS
propagate beacons containing such criterias s.t. they construct paths that are approximately ideal w.r.t. these criterias

Timetable:

Intended Start of Implementation: 29th of December
Intended Deadline for Implementation: 14th of January

This change is

Hi @shitz
This is (a part of) the algorithm Ahad (@noorizea) and I have been discussing for a while and we decided to define a (or multiple) student project(s) to implement it. Therefore, we have already discussed its run time and theoretical aspects with Ahad. It is not yet documented but we'll be writing the paper very soon. On my side, I'll implement the algorithm in the simulator as well. If you like we can discuss it in a joint meeting with you and Ahad.
The algorithm consists of a pull-based and a push-based algorithm. In this project, @Nearoo is only implementing the push-based one. The pull-based one will need even more invasive changes to the codebase.
It would be great if we discuss the evaluation and deployment strategy. At the moment, for the evaluation, I plan to simulate the algorithms on large scale in the simulator, emulate the SCION code the students develop on a single machine, then on the SCIONLab network. For the deployment, these algorithms are optional, meaning that they can be run in parallel with the baseline algorithm, and if an AS does not support the specified optimizations in the beacons, it just ignores it.
We do not expect this code to be merged by Jan 14th at all. @Nearoo needs to implement this part and evaluate it by running on a single machine by then so that he can defend his thesis in February. In the future, either he himself or other students will continue to work on this implementation.
Bests,
Ali

a discussion (no related file):
Previously, matzf (Matthias Frei) wrote…
Thank you for the detailed write up of this proposal!
After thinking this through, I'm somewhat skeptical of this premise:

Since service providers know which optimality criteria is required for each type of services (application) they provide, and they have customers all around world in all ISDs (and therefor core ASes), it is reaonable to let origin ASes to specify the optimality criteria of the path originating from them.

The core-ASes under consideration here provide transit, they will not generally be aware of or concerned with applications offered by their (direct and indirect) customer ASes. Furthermore, I'd expect that for most core ASes every one optimisation target would be desirable for some customers in their "customer cone".
Consequently, it seems likely that the outcome is that core ASes, if they enable this proposed system, would enable all the supported optimization targets.
This suggests the following alternative approach; instead of this system that lets the beacon originator choose an optimisation target for each beacon, we describe quality aware beaconing as a recommended "best practice" beacon selection method for core-beaconing. The recommendation is simply to always include some beacons for each supported optimisation target (i.e. a few with lowest latency and a few with highest bandwidth) to each destination AS.
To me it seems that the result of such a recommendation would be effectively the same as the result of this more complex system proposed here.
The implementation of this would only require to implement these beacon selection functions, and no further beacon extensions would be necessary. It would be easier to integrate into the current system and it would fall back to the current beaconing scheme much more obviously and gracefully.

Hi Matthias,
Thanks a lot for your feedback and suggestions.
As it is a research project and Silas’s thesis would be used as a proof of concept, he will implement this proposal even if it does not get merged.
Today, I had a discussion with Sam and Ahad from Anapaya about the next steps in implementing the new beaconing algorithms. We will of course discuss all aspects thoroughly before implementation.
But regarding your comments:
Of course, if core ASes only provide transit, this proposal does not help too much. However, considering the ongoing direction of SCION deployment (e.g. Sunrise lets their customers have their own ISD), the proposal helps a lot, specially if the number of desired path properties increase in the future.
Of course each small company having its own ISD sounds crazy, but big companies and cloud providers constituting their own ISD is not unreasonable.
So, consider the case that for example Microsoft has its own core AS, and for different types of applications it provides, it needs different types of path. This specially helps when they need different types of paths at different locations. So, for example they can request low latency paths to some of their interfaces and high bandwidth paths to some other interfaces. Also, they can use this feature for traffic engineering.

This has become stale by now. It also seems that further discussions on the idea would be necessary before continuing to finalize an implementation.
Closing this for now. Feel free to re-open if you want to reactivate the work on this topic. Perhaps it would make sense to create a proposal as a github issue though, before continuing to work on the implementation.


[Node] Display all the json data on localhost

To be able to display all the recipe data in the json format in the server

I want to work on this under JWOC


To add TMX (Tiled Map) files support for opening and for drawing game levels design.

Tiled Map Editor: https://www.mapeditor.org/
Go package for TMX-files parsing: https://github.com/salviati/go-tmx
What to support:

Add *.tmx file support for opening with pattern graphics files (tiles).
Production ready structures and function for working with tile map.
Draw tiles due to map and layers data and player position (camera).

Engo package for example: https://engoengine.github.io/tutorials/05-tilemaps

This is an interesting idea, but I'd want this in another package rather than in Ebiten core.

This is an interesting idea, but I'd want this in another package rather than in Ebiten core.

It is good solution. Not all developers need TMX, but those who need just will install addon package.

Just want to add that I have a tmx parser here the one you listed is a couple versions behind and doesn't support external tilesets or resources in folders other than the one the tmx is in. Using that, it shouldn't take much work at all to get it working with ebiten

https://gitlab.com/beoran/ebsgo/-/blob/master/engine/tile/io.go
This uses allegro through al5go, but could be adapted to Ebiten relatively easily. Chances are that I will do that, eventually.

Just want to add that I have a tmx parser here the one you listed is a couple versions behind and doesn't support external tilesets or resources in folders other than the one the tmx is in. Using that, it shouldn't take much work at all to get it working with ebiten

Thank you! I will take a look on this package.

I've coincidentally been working on exactly this over the past couple of days.  Not nearly as well written or full featured as the other options mentioned here, but it's Ebiten (functions use ebiten.Image, DrawImageOptions, GeoM, etc.), which might be of interest.
Package tiled in https://github.com/jwlarocque/engine/
Very early WIP example: https://github.com/jwlarocque/game/
(Note that at the moment file paths in the Tiled .tmx/.tsx/.json files need to be relative to main.go, not the file in which they are found.)

BTW, as there are already some TMX parsing libraries [1], I think we'd need a library to render TMX structs using Ebiten or other libraries like Engo or Pixel.
[1] https://github.com/salviati/go-tmx, https://github.com/fardog/tmx, https://github.com/ilikeorangutans/tiled/tree/master/tmx, etc. Of course @beoran's and @jwlarocque's are ones of them.

how

But don't you think a native support for tmx would be good like pixel and engo does

I'm not sure what a native support means, but having a third party library that parses TMX and works with Ebiten sounds good.

In case this helps, I am doing a small tool that parses tmx files and gets the useful information so it can be rendered by Ebiten.
I've added an example on how to use the lib and render a basic TMX file with Ebiten.
Feel free to use the lib or copy the code! https://github.com/Rulox/ebitmx


how to pin the desktop?

how to pin the desktop? put to top windows.

what do you mean?

pin the desktopnote window to desktop, so it will always show in toplevel.

Currently the note window is only set to TopMost when it is docked (meaning when it would hide itself after a few seconds).
Same as the Windows 10 app Sticky Notes, when the note window is not docked, TopMost is not enforced. I didn't want to enforce it because the note windows cannot be minimized, and enforcing TopMost means that it will always be on top of other windows (unless the other window also has TopMost set to true), which is a bit intrusive.
Have you tried docking them?

Since there is no feedback, can this issue be closed?


Add pbaroni to clabot

Purpose of this pull request
This pull request (PR) adds pbaroni (Paolo Baroni) to the .clabot file.
Issue number: For PR #3183

Select the type of change:

[x] Minor Changes - Typos, formatting, slight revisions
[ ] Update Content - Revisions and updating sections
[ ] New Content - New features, sections, pages, tutorials
[ ] Site and Tools - Updates, maintenance, and new packages for the site, Gatsby, React, etc

Thanks, @JV0812.


Math magicians: React event

Math Magicians 🚀

Hi There 👋  In this PR

[ ] I created a new branch then and replace the favicon and fix the console error from my project.✔
[ ] Then Added the Calculation functionality to my project.✔
[ ] Modified some CSS styles to make my project look good.✔

Hi @muneebulrehman, 👋 Thanks a lot for reviewing my project. 🙂


[Security] intlMessage doesn't escape/encode the output

In https://github.com/linkedin/dustjs/wiki/Dust-Tutorial mentions
...
All output values are escaped to avoid Cross Site Scripting (XSS) unless you use filters:
...

Try it with strings.json
"ZRP_MSG": "We did not find results for {query}. Try the suggestions below or type a new query above."

and dust template
var str = ">
content%20injection
";

{@intlMessage _key="ZRP_MSG" query=str /}

I verified this. Thanks for reporting it.


is_valid is true, query function report errors

m = np.array([[0. ,1. ,0. ,1. ,0. ,1. ,1.],
[0. ,0. ,0. ,0. ,1. ,1. ,1.],
[0. ,0. ,0. ,1. ,0. ,1. ,1.],
[0. ,0. ,0. ,0. ,0. ,1. ,1.],
[0. ,0. ,0. ,0. ,0. ,0. ,0.],
[0. ,0. ,0. ,0. ,0. ,0. ,1.],
[0. ,0. ,0. ,0. ,0. ,0. ,0.]])
ops=['input', 'maxpool3x3',  'conv1x1-bn-relu' , 'conv3x3-bn-relu', 'conv3x3-bn-relu', 'conv3x3-bn-relu','output']
cell = api.ModelSpec(matrix=m, ops=ops)
print(nasbench.is_valid(cell))
m is a matrix I searched by autoshrink, is_valid is true
And then,
data = nasbench.query(cell)
for k, v in data.items():
print('%s: %s' % (k, str(v)))
It will report
KeyError                                  Traceback (most recent call last)
 in ()
----> 1 data = nasbench.query(cell)
2 for k, v in data.items():
3   print('%s: %s' % (k, str(v)))
~\Downloads\ECE590 NAS\nasbench\api.py in query(self, model_spec, epochs, stop_halfway)
235                              % self.valid_epochs)
236
--> 237     fixed_stat, computed_stat = self.get_metrics_from_spec(model_spec)
238     sampled_index = random.randint(0, self.config['num_repeats'] - 1)
239     computed_stat = computed_stat[epochs][sampled_index]
~\Downloads\ECE590 NAS\nasbench\api.py in get_metrics_from_spec(self, model_spec)
364     self._check_spec(model_spec)
365     module_hash = self._hash_spec(model_spec)
--> 366     return self.get_metrics_from_hash(module_hash)
367
368   def _check_spec(self, model_spec):
~\Downloads\ECE590 NAS\nasbench\api.py in get_metrics_from_hash(self, module_hash)
346       fixed stats and computed stats of the model spec provided.
347     """
--> 348     fixed_stat = copy.deepcopy(self.fixed_statistics[module_hash])
349     computed_stat = copy.deepcopy(self.computed_statistics[module_hash])
350     return fixed_stat, computed_stat
KeyError: '926a133285cb34c1a38eefe60e7586d4'
How to solve this problem

the type should be int


BACKLOG-21369 - Adds the pdi bits.

@pentaho/ackbar @bennychow For review.

Build Completed
:fire: This pull request has some issues. It would be preferable to fix them in order for it to be just perfect. See below for more details. Some links are also available below for further assistance in addressing those issues.
Build Commands
mvn -Dsurefire.runOrder=alphabetical -B -fn -f 'pom.xml' -pl 'core' -P '!assemblies' -amd clean install && mvn -B -f 'pom.xml' -pl 'core' -P '!assemblies' -amd site

Cleanup Commands
mvn -B -f 'pom.xml' -pl 'core' -P '!assemblies' -amd build-helper:remove-project-artifact

Changed files
  core/src/main/java/org/pentaho/di/core/database/GoogleBigQueryDatabaseMeta.java
  core/src/main/resources/kettle-database-types.xml

Unit Test Coverage
These statistics help you identify how your changes have affected the coverage of the following files. If a file is not in this list, then its coverage was not affected by your changes. To get some help interpreting these metrics, please refer to Jacoco's documentation.

:warning: Coverage Changes: <0.1% (click to expand)
:new: org.pentaho.di.core.database.GoogleBigQueryDatabaseMeta

Branch Coverage: 0% :exclamation:
Complexity Coverage: 5% :exclamation:
Instruction Coverage: 2.1% :exclamation:
Line Coverage: 3.6% :exclamation:
Method Coverage: 7.4% :exclamation:

org.pentaho.di.job.entries.evaluatetablecontent.JobEntryEvalTableContent

Branch Change: -1% :small_red_triangle_down:
Complexity Change: -1% :small_red_triangle_down:
Instruction Change: -0.2% :small_red_triangle_down:

org.pentaho.di.job.entries.ftpsget.JobEntryFTPSGet

Branch Change: -0.5% :small_red_triangle_down:
Complexity Change: -0.6% :small_red_triangle_down:
Instruction Change: -0.1% :small_red_triangle_down:

org.pentaho.di.job.entries.waitforsql.JobEntryWaitForSQL

Branch Change: -0.7% :small_red_triangle_down:
Complexity Change: -0.9% :small_red_triangle_down:
Instruction Change: -0.1% :small_red_triangle_down:

org.pentaho.di.trans.steps.dimensionlookup.DimensionLookupMeta

Branch Change: -1.2% :small_red_triangle_down:
Complexity Change: -0.7% :small_red_triangle_down:
Instruction Change: -0.3% :small_red_triangle_down:

org.pentaho.di.trans.steps.memgroupby.MemoryGroupByMeta

Branch Change: -1.1% :small_red_triangle_down:
Complexity Change: -1.3% :small_red_triangle_down:

org.pentaho.di.trans.steps.synchronizeaftermerge.SynchronizeAfterMergeMeta

Instruction Change: -0.1% :small_red_triangle_down:

org.pentaho.di.www.cache.CarteStatusCache

Instruction Change: -1.2% :small_red_triangle_down:
Line Change: -1.3% :small_red_triangle_down: