Update Rubix version to 0.3.16

Supersedes https://github.com/prestosql/presto/pull/4445
New version is a bugfix release. Among other it includes fix for
https://github.com/prestosql/presto/issues/3580

This PR updates Rubix to 0.3.15 but update was not smooth. The problems seem mostly to touch the testing code only though, not Presto itself.
I fixed some, but some remain.
Fixed:

updated integration and product tests to use new rubix jmx metrics
worked around issue that rubix jmx metrics are only registered on first use of CachingFIleSystem, when CFS.initialize() is called (see TestHiveCaching.initializeRubixStats method.

To be fixed:

proper solution for lazy metrics registration, those should be registered at rubix startup.
Integration test TestRubixCaching no longer work if we try to run all test mehods (every single one works). The problem is that each method is internally reinitializing Rubix and this is no longer allowed. CheckPreconditions.checkState(!initialized.get(), "LocalBookKeeper should be set before opening up the Filesystem to clients"); in CachingFileSystem.setLocalBookKeeper triggers on every test method but first.

Thanks @stagraqubole updated back to use counts. I (wrongly) recalled that these tests always operated on data sizes and did not check before doing changes.

Updated this PR for rubix 0.3.16 which includes changes needed for Presto.
PTAL @stagraqubole, @dain

Please ensure you send a documentation PR for this change @losipiuk .since it affects JMX metrics and ensure the PR gets merged with the same release as this feature. I can help with review. cc @electrum


How to calc count pages PDF after saveAs

Hi.
How i can calc count page from generated PDF from HTML?
i use header-html and i can write page count in pages via JS variable. But me need get page count in PHP after generate PDF.

Sorry, I can't help you with questions like these. This extension is only a wrapper around wkhtmltopdf to create PDF from HTML. There's no way to get back information about the PDF from wkhtmltopdf.
You could maybe try my other extension to analyse the created PDF afterwards: https://github.com/mikehaertl/php-pdftk#get-pdf-data


How dominant resource is calculated in DRF plugin?

Hello
I 'm wondering how dominant resource is calculated in DRF plugin file? Also, since DRF is a generalization of Max-Min fairness, I could not find any code which implements it. Could you please help me?
Cheers

please refer to https://github.com/kubernetes-sigs/kube-batch/tree/master/pkg/scheduler/plugins/drf

In the below structure, the dominant resource has been created but it has not been used in the codes.

type drfAttr struct {
share            float64
dominantResource string
allocated        *api.Resource
}
dominant resource should be calculated based on the working scheme of DRF.
Cheers

oh, it's calculated on the fly in calculateShare right now.


Updated title

Don't think "storyboard" makes as much sense here anymore. I would just make this "Script responses"

:tada: This PR is included in version 1.7.2 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


Intellisense is too slow when using interactive window and notebook due to jupyter taking a long time to return kernel results.

Note: Make sure there is no way for us to update the intellisense dynamically

This doesn't seem to be working.
Do the following:
# %%
import time
import sys

# %%
time.sleep(10)

Then try typing 'sys.' in the interactive window. No intellisense comes up.

Okay now it suddenly started working. Not sure what's going on. Also seems to skip jupyter intellisense if it's taking too long. Tried with a large dataframe and couldn't get the column names.


fix: add blog post description

Signed-off-by: Daniel Holbach<EMAIL_ADDRESS>

→ https://deploy-preview-1226--fluxcd.netlify.app/blog/


Switch Map Type Button Bleeds into Top Android Control Bar

Describe the bug
In the current UI, on a Pixel 2 the switch map button bleeds into the Android controls:

Virtual Device Details

Name: Pixel_2_API_28

CPU/ABI: Google Play Intel Atom (x86)
Target: google_apis_playstore [Google Play] (API level 28)
Skin: pixel_2
SD Card: 512M
fastboot.chosenSnapshotFile:
runtime.network.speed: full
hw.accelerometer: yes
hw.device.name: pixel_2
hw.lcd.width: 1080
hw.initialOrientation: Portrait
image.androidVersion.api: 28
tag.id: google_apis_playstore
hw.mainKeys: no
hw.camera.front: emulated
avd.ini.displayname: Pixel 2 API 28
hw.gpu.mode: auto
hw.ramSize: 1536
PlayStore.enabled: true
fastboot.forceColdBoot: no
hw.cpu.ncore: 4
hw.keyboard: yes
hw.sensors.proximity: yes
hw.dPad: no
hw.lcd.height: 1920
vm.heapSize: 256
skin.dynamic: yes
hw.device.manufacturer: Google
hw.gps: yes
hw.audioInput: yes
image.sysdir.1: system-images/android-28/google_apis_playstore/x86/
showDeviceFrame: yes
hw.camera.back: virtualscene
AvdId: Pixel_2_API_28
hw.lcd.density: 420
hw.arc: false
hw.device.hash2: MD5:55acbc835978f326788ed66a5cd4c9a7
fastboot.forceChosenSnapshotBoot: no
fastboot.forceFastBoot: yes
hw.trackBall: no
hw.battery: yes
hw.sdCard: yes
tag.display: Google Play
runtime.network.latency: none
disk.dataPartition.size:<PHONE_NUMBER>
hw.sensors.orientation: yes
avd.ini.encoding: UTF-8
hw.gpu.enabled: yes

To Reproduce
Steps to reproduce the behavior:

Open the app
Go to the home screen

Expected behavior
Button shouldn't bleed into other controls.

@shobhitagarwal1612 the button padding or position may need to be adjusted based on when WindowInsets become available. You can find other examples of this by searching in the code for "WindowInsets". Could you PTAL?

I missed this while building the feature because the emulator (android 10.0) I was using had resolution 480x800 and the button was well within the boundary. Thanks for pointing out the issue.


Ability to saving the files LIST on HuBiC from "List" Swift Explorer's tab

Ok, It's me again!
I come with a new fresh and useful idea (which can be useful as hell for logging or listing purpose).
Actually, Swift Explorer work in two modes.
1) Treeview
2) List
In TreeView mode we can see folders and files like a Tree view. (nothing anormal here!)
In List mode we can see folders and files like a text list. (This is all good here too).
Now, it will be fantastic and useful if we will are able to generate a Text-List of all Folders/Files within the actual Cloud Storage (OR from a folder selected).
(or XML why not, but .txt file too please!)
This mean, recursively.
Thanks by advance.

Would also like this feature to be implemented. Workaround now is to take screenshot and use OCR but it's a really bad way of doing this^^


Feat:Add upcoming events section

Describe the feature
Adding  an event calendar to inform users about upcoming events, workshops, or webinars.
Add ScreenShots

Record

[X] I agree to follow this project's Code of Conduct
[X] I'm a GSSOC'24 contributor
[X] I want to work on this issue

hello mam @Suchitra-Sahoo this feature will be great to add website,kindly please assign me this under gssoc!!


ModuleNotFoundError: No module named 'Swin3D.sparse_dl.attn_cuda'

thanks for your work~!
but when i run:
import torch
from Swin3D.models import Swin3DUNet
model = Swin3DUNet(depths, channels, num_heads,
window_sizes, quant_size, up_k=up_k,
drop_path_rate=drop_path_rate, num_classes=num_classes,
num_layers=num_layers, stem_transformer=stem_transformer,
upsample=upsample, first_down_stride=down_stride,
knn_down=knn_down, in_channels=in_channels,
cRSE='XYZ_RGB_NORM', fp16_mode=1)
model.load_pretrained_model(ckpt_path)
i got this bug: ModuleNotFoundError: No module named 'Swin3D.sparse_dl.attn_cuda'
emmm, what can i do???

Were you able to solve this problem ? because I am facing the same issue.

Could you please provide your python version?
And did you run the command python setup.py install?

I also encountered this problem. Here is my environment information
python:3.10
pytorch:2.5.1+
Ubuntu:20.04
CUDA:12.1
I have run python setup.py install and it shows that the installation is successful.
Here is my error message:
import Swin3D.sparse_dl.attn_cuda as attn_module
ModuleNotFoundError: No module named 'Swin3D.sparse_dl.attn_cuda'

Could you please provide your python version? And did you run the command python setup.py install?

I also encountered this problem. Here are my environment information
python:3.10
pytorch:2.5.1+
Ubuntu:20.04
CUDA:12.1
I have run python setup.py install and it shows that the installation is successful.
Here is my error message:
import Swin3D.sparse_dl.attn_cuda as attn_module
ModuleNotFoundError: No module named 'Swin3D.sparse_dl.attn_cuda'
What should I do? I look forward to your reply

Could you please provide your python version? And did you run the command python setup.py install?

I also encountered this problem. Here are my environment information python:3.10 pytorch:2.5.1+ Ubuntu:20.04 CUDA:12.1 I have run python setup.py install and it shows that the installation is successful. Here is my error message: import Swin3D.sparse_dl.attn_cuda as attn_module ModuleNotFoundError: No module named 'Swin3D.sparse_dl.attn_cuda' What should I do? I look forward to your reply

I solved this problem by this command, hope it helps you
python setup.py build_ext --inplace


Improve hostRequirements, Features support for dev containers that use GPUs

Dev containers can run on machines with GPUs and access them directly on Linux or through WSL on Windows. However, currently there is no direct support for a GPUs in the spec.
To enable GPU support, I'd propose we enhance the "hostRequirements" property to allow specifying GPU information.  If this information is present, we then automatically enable GPU support (e.g., via --gpus all).
I'd propose we support a form that simply adds a requirement for any GPU, with the option to specify more requirements for further validation. Here's a proposed format:
Just enabling/requiring any GPU
"hostRequirements": {
    "gpu": true

Specifying cores and memory:
"hostRequirements": {
    "gpu": {
        "cores": 2
        "memory": "4gb" // Same value format as memory for the machine
    }
}

and with type
"hostRequirements": {
    "gpu": {
        "cores": 2
        "memory": "4gb"
        "type": "nvidia"
    }
}

To allow Dev Container Features (#61) to require a GPU (e.g., in an NVIDIA CUDA feature), I'd propose we also allow hostRequirements to be specified in devcontainer-features.json.

I generally like this - however I'd really like to be able to have a devcontainer that supports GPUs when available but doesn't require them.
For my specific use case, we have some libraries that can use GPUs, but also fall back to CPUs if they are not available. Currently the developers need to manually add/remove the -gpus all.
My sugestion would be to extended this proposal with something like:
"hostRequirements": {
    "gpu": {
        "optional": true
    }
}

(I appreciate that mixing 'requirements' and optional elements seems a bit counter intuitive, however I can't think of a better option).

we then automatically enable GPU support (e.g., via --gpus all).

This flag isn't present in podman, and isn't part of the CDI spec, btw.  You're supposed to set things up differently in podman (although you can also install a global hook).

Wrote down what we agreed on for the implementation here: https://github.com/devcontainers/spec/issues/82


[MAS1.3.1] [Screen Reader-Live Chat] Screen reader is not reading the Time information when the bot or user send the message.

Actual Result:
Screen reader is not reading the Time information when the bot or user send the message
Screen reader is reading as User said “how are “button
Role is defined for bot echo and user messages text.
Expected Result:
Screen reader should read the Time information when the bot or user send the message
Screen reader should read as “A minute ago User said how are “
Role(Button) should be removed for user and bot echo messages texts
Note: Issue is repro’ing with NVDA. Please refer the attachment as <MAS1.3.1_Live chat_NVDA.wmv>
MAS1.3.1_Live chat_NVDA.zip
Same issue observed in the Mac also. Please refer the attachment for more information (Screen reader is not reading the Time information_MAC)
Repro Steps:
Turn on the narrator

Open the Bot Framework V4 Emulator.
2.Welcome tab screen gets opened
Navigate to the Open a bot and select it
4.Open bot dialog gets opened and connect the pen bot
5.Live chat screen gets opened
6.Naviagte to the "How are " text message
Observe the issue

User Impact:
Users who rely on AT will be affected if the screen reader is not reading the descriptive information then the screen reader user will skip the feature
Test Environment:
OS Build: Version 1903(OS Build 18362.239)
Browser: Edge
Application: Bot Framework V4 Emulator
Screen reader: Narrator
OS: MacOs Version 10.15
Application: Bot Framework V4 Emulator (Version 4.5.2-80829)
MAS Reference Link:
Sharepoint Link
MAS1.3.1_Live chat.zip

Screen reader is not reading the Time information_Mac.zip

I'm fairly confident this will be fixed when we bump Web Chat in Emulator. https://github.com/microsoft/BotFramework-WebChat/pull/2278

Waiting for this one until towards the end of our audit since the bump to React 16.9+ will cause merge conflicts with PRs.

Verified in latest bot emulator version 4.5.2-82861 with NVDA(2019.2) Issue partially fixed Hence we are reactivating this bug.
Screen reader reading the date information but time info is not narrating .
Please refer the attachment:
1759.zip
Bug 1759.zip
Note: Issue still repro'ing for both Win32 and MAC
For MAC version-4.5.2-82590 and Mac version-10.15(Beta)

@Kumar2608 the first video is reading the time stamp (Windows) as well as the date. It looks like this bug is only repro-ing on Mac. Can I get confirmation?

@Kumar2608 I have checked this both on Windows and Mac and both are reading both the date and time. I have a recording of the Mac repro, but unfortunately I am having WiFi problems and I am unable to upload the video yet. I will update this thread once I get that video up.

@Kumar2608, here's that video. My apologies for the bad quality.
timestamp.zip

As per dev issue got fixed hence we are closing this bug.


quit throwing away STDERR-- it provides valuable debugging information

Tonight I thought qutebrowser-profile was failing. Nothing happened when I ran it.
Then I made this change locally so that STDERR was printed and qutebrowser shared a crucial detail: The browser window happened an opened an existing instance (on a desktop that was hidden).

I've re-implemented qutebrowser-profile in Python which solves a few headaches with its implementation. With this PR in mind I added --show-stdio (disabled by default) to pass through stdin/out/err to the calling terminal.


Gateway proxy http request 404

Reference Links： https://go-zero.dev/docs/tutorials/gateway/grpc
This is completely in accordance with the official demo example. I don't know why the request is 404.
gRPC request

gateway http request

$ goctl -v
goctl version 1.6.4 windows/amd64
$ protoc --version
libprotoc 3.19.4
$  protoc-gen-go --version
protoc-gen-go.exe v1.33.0
$  protoc-gen-go-grpc --version
protoc-gen-go-grpc 1.3.0

Sorry, the config file in docs was not correctly indented. I've modified it.

OK, thanks for your help


show_2D warning in 02_intro_sandstone_parallel_roi.ipynb

Also in 03_preprocessing cell [28]

And [9] in 04_FBP_CGLS_SIRT

Also in 01_into_walnut - cell [13]

closed in CIL. Notebooks will be fixed in next CIL release. https://github.com/TomographicImaging/CIL/issues/1353


Renaming cancelled when using arrow keys at end of text

Description
When going to the end of the file with arrow keys it will cancel the rename and highlight the next file. It shouldn't do this as renaming long file name becomes hard to do.
Steps To Reproduce
No response
Expected behavior
It should just hit the end of text and not cancel the rename.
Files Version
<IP_ADDRESS>
Windows Version
10.0.19043.1151
Relevant Assets
No response

Closing since this is fixed in <IP_ADDRESS>


Screen sharing feature UI adjustment and code refactor

In this PR, I tried to tidy things up especially the UI. As a follow-up of #9, in sum, this PR have done the following things:

UI adjustment: added a select box for selecting a QR source and moved the auto submit checkbox to the bottom of the page
Auto submit checkbox state is now persistent by utilizing localStorage
Refactored praesentia.js
I also re-organized the static files for nimiq/qr-scanner as it looks quite messy (this should be in another PR, but I guess that's okay)

What do you think? @Noth3r
Feel free to test and/or give suggestions to it.

Nice PR. It works perfectly. But I have a little suggestion to stick with the worker because in my pc if I create the worker manually, my chrome has lower CPU usage. How about yours?

In nimiq/qr-scanner docs

As an optional third parameter a manually created QR scanner engine instance to be reused can be specified. This improves performance if you're scanning a lot of images. An engine can be manually created via QrScanner.createQrEngine(QrScanner.WORKER_PATH) (async). By default, no engine is reused for single image scanning.

@Noth3r Nice catch, I didn't even know that. I can't test its performance, but we are definitely scanning a lot of images (when screen sharing) and are having performance issues. I also noticed that by not using a reusable worker, the browser requests the worker file every time it scans a frame or an image (I think this is what causes the higher CPU usage).

Let me wire up the changes.

Does it look good to you? @Noth3r

Yep works perfectly. Nice one @p4kl0nc4t 🎉

Merged, thanks!


[move-lang] Expanded known attribute system

Added checked locations for known attributes
Added abilities to have known attributes split by section

Motivation

Will hopefully allow for some future work on natives

Test Plan

added tests

I'm wondering if there should also be a way to specify what attributes can occur with other attributes, e.g., having some way of specifying that the following is an invalid combination of attributes:

It is a good question, but I'm trying not to overdo it too much now. Right now, all I know is that all attributes need their locations+uniqueness checked, as it greatly reduces the complexity of adding other known attributes (like for natives) since doing this check requires a full AST traversal. Whereas something like pairs/sets of attributes is a bit easier to check manually.
But if we see a common pattern emerging, we can always add the support

/land


Scratch org password not being updated where created in a flow

Since this change (https://github.com/SalesforceFoundation/CumulusCI/commit/fde28ca7345e9ef052dffdbebc20d5247910a261) I've not been able to get a new scratch org password generated when creating an org with the dev_org flow. When the new scratch org is created, it is created with a new password, but org info does not display the new password.
cci org info dev will give me the password of a previous org instead of the new one and I find that I'm not actually able to log in with the new credentials.
Based on what I'm looking at, it looks like when BaseFlow goes to refresh the oauth token and finds no scratch org, it runs create_org in ScratchOrgConfig. cci org scratch dev org_name uses create_scratch_org in the keychain, so it makes sense that the password generation is being handled differently.
I've reverted this change locally and everything has gone back to working as expected.
This is still true after the changes in #639.

I'm unable to reproduce the issue as of 4370d869b07877d22d2e7840db5fd85d4b376155. Here are my steps:
$ cci org scratch dev org_name
$ cci org info org_name
$ cci org scratch_delete org_name
$ cci flow run dev_org --org org_name
$ cci org info org_name

When I do this I can see the username and password have been updated, and logging in with the new credentials works.
I'm closing this one but please feel free to continue conversation here if needed.


Clarification that B9STool is "boot.nds" and OLD/NEW FIRM clarification too

Hello again! There has been quite a number of people getting confused one where "boot.nds" comes from in the DSiWare guides. Can you mention to "copy boot.nds" from the B9STool .zip?
I also wanted to mention, on those pages, that the OLD/NEW FIRM doesn't specifically say to download it for O3DS/N3DS, but only "for the target console": Can you also make this more clear to avoid any potential confusion?
Thanks!

B9STool doesn't have a .zip files in the releases.


Adance benchmark old dependency httplex

When I tried running banchmarks on the advanced-benchmark branch, following the wiki's instructions, I got that the "golang.org/x/net/lex/httplex" dependency is missing. This library was merged with httpguts.

The branch is not updated.


Make freeze, freeze & mute, and unmute verbs work on disconnected players.

About the PR

This makes the freeze, freeze & mute, and unfreeze verb work on any entity.
Why / Balance

The verbs do not require an ICommonSession to function.
Admins often wish to apply these verbs to disconnected players.
Technical details

I moved the code out of the if block for the actorcomponent.
Media

[x] I have added screenshots/videos to this PR showcasing its changes ingame, or this PR does not require an ingame showcase

Breaking changes

Changelog

:cl:
ADMIN:

tweak: Freeze, freeze & mute, and unfreeze verbs now work on any entity. Not just connected players.

I also want to make it so all the verbs are not in a giant if block which could just be outside and return but that would create a huge diff so I'll just make a separate command when this is closed or merged. I should also probably clean up more than that.


[Task]

Description
mongodb monitoring support custom connection timeout param
Task List

[ ] mongodb monitoring support custom connection timeout param

Bot detected the issue body's language is not English, translate it automatically. 👯👭🏻🧑🤝🧑👫🧑🏿🤝🧑🏻👩🏾🤝👨🏿👬🏿

Can you provide more details about this issue

Can you provide more details about this issue

hi, now we can monitoring mongodb by input ip, username, password and some params. But we can not custom config the connect timeout time when try connect to mongodb. Like this,

Can you provide more details about this issue

hi, now we can monitoring mongodb by input ip, username, password and some params. But we can not custom config the connect timeout time when try connect to mongodb. Like this,

We can try using MongoClientSettings
https://www.mongodb.com/zh-cn/docs/drivers/java/sync/current/fundamentals/connection/mongoclientsettings/


Chat - Compose box not highlighted after sending and copying a message

If you haven’t already, check out our contributing guidelines for onboarding and email<EMAIL_ADDRESS>to request to join our Slack channel!

Version Number: 9.0.2-0
Reproducible in staging?: Y
Reproducible in production?: Y
If this was caught during regression testing, add the test name, ID and link from TestRail: https://expensify.testrail.io/index.php?/tests/view/4672050
Issue reported by: Applause - Internal Team
Action Performed:

Log in to New Expensify
Navigate to any chat
Send a message
Copy the message
Type something in compose box

Expected Result:
Compose box should be highlighted as it is focused
Actual Result:
Compose box is not highlighted after copying a message
Workaround:
Unknown
Platforms:

Which of our officially supported platforms is this issue occurring on?

[ ] Android: Native
[x] Android: mWeb Chrome
[ ] iOS: Native
[ ] iOS: mWeb Safari
[ ] MacOS: Chrome / Safari
[ ] MacOS: Desktop

Screenshots/Videos
Add any screenshot/video evidence

https://github.com/Expensify/App/assets/78819774/adff6725-d54b-4246-a2e2-3479e15f9d14
View all open jobs on GitHub

@joekaufmanexpensify  FYI I haven't added the External label as I wasn't 100% sure about this issue. Please take a look and add the label if you agree it's a bug and can be handled by external contributors

We think that this bug might be related to #vip-vsp

I can reproduce this. However, this is a pretty niche set of reproduction steps, since it only happens after copying a message when you immediately go to send another AND requires being on android mobile web.
It also has a clear workaround (tapping out and back into the compose box after copying a message fixes this). So I'm not really convinced there is much user impact here.

Since we paused #vip-vsb, this issue doesn't feel important enough to prioritize fixing to override that the project is paused. Even if it weren't paused, I'd be in the camp of doing nothing until we get feedback from actual customers on this.

Closing for now.


Improve Debian package updates

Scraping packages.debian.org is unreliable and slow. Debian QA offers a madison webpage where the latest version can be queried and there is a simple REST API on the backend that we can use. rMadison from the devscripts should be a good template.

Merged PR #2


unable to connect to ssl://data.logentries.com:443:-1

I keep getting this randomly but as far as I know without any configuration changes in our Symfony 2.8 application. Am I doing something wrong in configuration or is this a bug?
Here's my stack trace:
[2017-06-22 10:39:58] php.DEBUG: fsockopen(): php_network_getaddresses: getaddrinfo failed: Name or service not known {"type":2,"file":".../vendor/monolog/monolog/src/Monolog/Handler/SocketHandler.php","line":206,"level":28928} [] [2017-06-22 10:39:58] php.DEBUG: fsockopen(): unable to connect to ssl://data.logentries.com:443:-1 (php_network_getaddresses: getaddrinfo failed: Name or service not known) {"type":2,"file":".../vendor/monolog/monolog/src/Monolog/Handler/SocketHandler.php","line":206,"level":28928} [] [2017-06-22 10:39:58] request.CRITICAL: Uncaught PHP Exception UnexpectedValueException: "Failed connecting to ssl://data.logentries.com:443 (0: php_network_getaddresses: getaddrinfo failed: Name or service not known)" at .../vendor/monolog/monolog/src/Monolog/Handler/SocketHandler.php line 281 {"exception":"[object] (UnexpectedValueException(code: 0): Failed connecting to ssl://data.logentries.com:443 (0: php_network_getaddresses: getaddrinfo failed: Name or service not known) at.../vendor/monolog/monolog/src/Monolog/Handler/SocketHandler.php:281) [stacktrace] #0 .../vendor/monolog/monolog/src/Monolog/Handler/SocketHandler.php(269): Monolog\\Handler\\SocketHandler->createSocketResource() #1 .../vendor/monolog/monolog/src/Monolog/Handler/SocketHandler.php(251): Monolog\\Handler\\SocketHandler->connect() #2 .../vendor/monolog/monolog/src/Monolog/Handler/SocketHandler.php(57): Monolog\\Handler\\SocketHandler->connectIfNotConnected() #3 .../app/cache/dev/classes.php(5771): Monolog\\Handler\\SocketHandler->write(Array) #4 .../app/cache/dev/classes.php(6273): Monolog\\Handler\\AbstractProcessingHandler->handle(Array) #5 .../app/cache/dev/classes.php(6352): Monolog\\Logger->addRecord(200, '{\"eventType\":\"t...', Array)

Well, the logs are saying Failed connecting to ssl://data.logentries.com:443 (0: php_network_getaddresses: getaddrinfo failed: Name or service not known)
This is a network error on your system. The DNS resolution of data.logentries.com failed

It is attempting to name resolve the domain name including the port number
Notice the first instance in the stack trace:
unable to connect to ssl://data.logentries.com:443:-1 (php_network_getaddresses: getaddrinfo failed: Name or service not known)

OK, this looks like a PHP issue on my system, works in command line but not from a web request.


Changed the default value for Het calling stringency from 5 to 30

Please review

I agree with your changed @asmirnov239, feel free to merge.


changed property names to match with what api json uses

I was getting None types for the schedule start and end, and noticed the key names in the raw element we create didn't all match with what the api uses.
"recurrenceType" was right, but the rest such as "start_time" are expected to just be "start."

Oof my bad


W tensorflow/core/framework/op_kernel.cc:1152] Not found

Hi,
What is the reason this error is happening ?
Restored model parameters from ./deeplab_resnet.ckpt
2017-05-05 15:23:06.615207: W tensorflow/core/framework/op_kernel.cc:1152] Not found: /home/VOCdevkit/SegmentationClassAug/2008_003519.png
2017-05-05 15:23:06.615207: W tensorflow/core/framework/op_kernel.cc:1152] Not found: /home/VOCdevkit/JPEGImages/2008_003519.jpg
Traceback (most recent call last):
File "train.py", line 253, in
main()
File "train.py", line 242, in main
loss_value, images, labels, preds, summary, _ = sess.run([reduced_loss, image_batch, label_batch, pred, total_summary, train_op], feed_dict=feed_dict)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 778, in run
run_metadata_ptr)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 982, in _run
feed_dict_string, options, run_metadata)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1032, in _do_run
target_list, options, run_metadata)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1052, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.OutOfRangeError: FIFOQueue '_1_create_inputs/batch/fifo_queue' is closed and has insufficient elements (requested 10, current size 0)
[[Node: create_inputs/batch = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_UINT8], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](create_inputs/batch/fifo_queue, create_inputs/batch/n)]]
Caused by op u'create_inputs/batch', defined at:
File "train.py", line 253, in
main()
File "train.py", line 141, in main
image_batch, label_batch = reader.dequeue(args.batch_size)
File "/home/yared/tensorflow-deeplab-resnet-master/deeplab_resnet/image_reader.py", line 179, in dequeue
num_elements)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/training/input.py", line 917, in batch
name=name)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/training/input.py", line 712, in _batch
dequeued = queue.dequeue_many(batch_size, name=name)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/data_flow_ops.py", line 458, in dequeue_many
self._queue_ref, n=n, component_types=self._dtypes, name=name)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 1328, in _queue_dequeue_many_v2
timeout_ms=timeout_ms, name=name)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 768, in apply_op
op_def=op_def)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2336, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1228, in init
self._traceback = _extract_stack()
OutOfRangeError (see above for traceback): FIFOQueue '_1_create_inputs/batch/fifo_queue' is closed and has insufficient elements (requested 10, current size 0)
[[Node: create_inputs/batch = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_UINT8], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](create_inputs/batch/fifo_queue, create_inputs/batch/n)]]

First, please check that the files can indeed be found on those paths:

2017-05-05 15:23:06.615207: W tensorflow/core/framework/op_kernel.cc:1152] Not found: /home/VOCdevkit/SegmentationClassAug/2008_003519.png
2017-05-05 15:23:06.615207: W tensorflow/core/framework/op_kernel.cc:1152] Not found: /home/VOCdevkit/JPEGImages/2008_003519.jpg

I downloaded the VOCdevkit file and placed it in Home directory. But, didn't found it. could this be related with the tensorflow version? I am using tensorflow  1.1 and python 2.7 .

If you cannot find the dataset, then this is the problem.
TF and python versions are not related to it.

Thanks, for your response. It can read load the image. but, it can't read the mask/label. The file is there i checked it but it can't load it. I don't know why?
Restored model parameters from ./deeplab_resnet.ckpt
2017-05-06 23:04:46.554659: W tensorflow/core/framework/op_kernel.cc:1152] Not found: /home/yared/Desktop/pro/annot/image(27).png
Traceback (most recent call last):
File "train.py", line 254, in
main()
File "train.py", line 243, in main
loss_value, images, labels, preds, summary= sess.run([reduced_loss, image_batch, label_batch, pred, total_summary, train_op], feed_dict=feed_dict)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 778, in run
run_metadata_ptr)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 982, in _run
feed_dict_string, options, run_metadata)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1032, in _do_run
target_list, options, run_metadata)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1052, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.OutOfRangeError: FIFOQueue '_1_create_inputs/batch/fifo_queue' is closed and has insufficient elements (requested 10, current size 0)
[[Node: create_inputs/batch = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_UINT8], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](create_inputs/batch/fifo_queue, create_inputs/batch/n)]]
Caused by op u'create_inputs/batch', defined at:
File "train.py", line 254, in
main()
File "train.py", line 141, in main
image_batch, label_batch = reader.dequeue(args.batch_size)
File "/home/yared/tensorflow-deeplab-resnet-master1/deeplab_resnet/image_reader.py", line 179, in dequeue
image_batch, label_batch = tf.train.batch([self.image, self.label], num_elements)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/training/input.py", line 917, in batch
name=name)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/training/input.py", line 712, in _batch
dequeued = queue.dequeue_many(batch_size, name=name)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/data_flow_ops.py", line 458, in dequeue_many
self._queue_ref, n=n, component_types=self._dtypes, name=name)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 1328, in _queue_dequeue_many_v2
timeout_ms=timeout_ms, name=name)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 768, in apply_op
op_def=op_def)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2336, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1228, in init
self._traceback = _extract_stack()
OutOfRangeError (see above for traceback): FIFOQueue '_1_create_inputs/batch/fifo_queue' is closed and has insufficient elements (requested 10, current size 0)
[[Node: create_inputs/batch = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_UINT8], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](create_inputs/batch/fifo_queue, create_inputs/batch/n)]]

It stars training and stops and brings the error ...
Restored model parameters from deeplab_resnet.ckpt
2017-05-07 12:55:25.806612: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:1152] Unknown: NewRandomAccessFile failed to Create/Open: pro : Access is denied.
; Input/output error
2017-05-07 12:55:25.806612: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:1152] Unknown: NewRandomAccessFile failed to Create/Open: pro : Access is denied.
; Input/output error
2017-05-07 12:55:26.647734: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.94GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
2017-05-07 12:55:26.728924: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.59GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
2017-05-07 12:55:26.790851: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.59GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
2017-05-07 12:55:26.839325: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.85GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
2017-05-07 12:55:26.868058: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.88GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
The checkpoint has been created.
step 0   loss = 4.713, (13.539 sec/step)
step 1   loss = 3.497, (0.669 sec/step)
2017-05-07 12:55:39.661197: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:1152] Out of range: FIFOQueue '_1_create_inputs/batch/fifo_queue' is closed and has insufficient elements (requested 2, current size 1)
[[Node: create_inputs/batch = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_UINT8], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](create_inputs/batch/fifo_queue, create_inputs/batch/n)]]

Seems like some files from the list cannot be read. Make sure that path to the files in the list are valid.
Regarding the labels, it looks like you are not using VOC dataset: if that is the case, you need to have the format of your segmentation masks coinciding with the format of the VOC images as per the DeepLab setup (i.e., without a colour map).

@DrSleep Images in 'SegmentationClassAug' are already labelled? Every pixel in each image is in the range of 20?

Already labelled. <= 20 and 255 (the 'void' label)
On 8 May 2017 at 07:25, Zhengtian Xu<EMAIL_ADDRESS>wrote:

@DrSleep https://github.com/DrSleep Images in 'SegmentationClassAug'
are already labelled? Every pixel in each image is in the range of 20?
—
You are receiving this because you were mentioned.
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.

My RGB label is just like this. And i configured it on utils.py ... is there any other place also do i have to modify?
Impervious surfaces (RGB: 255, 255, 255)
Building (RGB: 0, 0, 255)
Low vegetation (RGB: 0, 255, 255)
Tree (RGB: 0, 255, 0)
Car (RGB: 255, 255, 0)
Clutter/background (RGB: 255, 0, 0)

You need to convert RGB vectors into 1-D labels: e.g., Background -> 0, Car
-> 1, and etc.
On 8 May 2017 at 10:29, Yaredoh<EMAIL_ADDRESS>wrote:

My RGB label is just like this. And i configured it on utils.py ... is
there any other place also do i have to modify?
Impervious surfaces (RGB: 255, 255, 255)
Building (RGB: 0, 0, 255)
Low vegetation (RGB: 0, 255, 255)
Tree (RGB: 0, 255, 0)
Car (RGB: 255, 255, 0)
Clutter/background (RGB: 255, 0, 0)
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/DrSleep/tensorflow-deeplab-resnet/issues/79#issuecomment-299805320,
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Please take a look here: https://github.com/martinkersner/train-DeepLab#data-conversions (the second paragraph).
Also this function should be useful to perform the conversion: https://github.com/martinkersner/train-DeepLab/blob/master/utils.py#L91

Thank you, DrSleep. I think that is why the labeled image is not loading. I will look at it.

Hello DrSleep,
This code is converts to 2D labels? We can not used it for 1-D convert ?
`def convert_from_color_segmentation(arr_3d):
arr_2d = np.zeros((arr_3d.shape[0], arr_3d.shape[1]), dtype=np.uint8)
for c, i in palette.items():
    m = np.all(arr_3d == np.array(c).reshape(1, 1, 3), axis=2)
    arr_2d[m] = i

return arr_2d`

It converts to a 2d array (array of pixels), where each value is a 1-d
label. The code that I linked can be used without a problem.
On 11 May 2017 5:22 pm, "Yaredoh"<EMAIL_ADDRESS>wrote:

Hello DrSleep,
This code is converts to 2D labels? We can not used it for 1-D convert ?
`def convert_from_color_segmentation(arr_3d):
arr_2d = np.zeros((arr_3d.shape[0], arr_3d.shape[1]), dtype=np.uint8)
for c, i in palette.items():
m = np.all(arr_3d == np.array(c).reshape(1, 1, 3), axis=2)
arr_2d[m] = i
return arr_2d`
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.

Thanks. I will use it.

python fine_tune.py --not-restore-last
BATCH_SIZE = 4 DATA_DIRECTORY = '/home/yared/Desktop/tensorflow-deeplab-resnet-master/dataset' DATA_LIST_PATH = 'dataset/train_tf.txt' IGNORE_LABEL = 255 INPUT_SIZE = '1000,1000' LEARNING_RATE = 1e-4 NUM_CLASSES = 6 NUM_STEPS = 20000 RANDOM_SEED = 1234 RESTORE_FROM = 'deeplab_resnet.ckpt' SAVE_NUM_IMAGES = 2 SAVE_PRED_EVERY = 100 SNAPSHOT_DIR = './snapshots_finetune/'
Label shape
`
np.array(Image.open('dataset/annot/image(1).png')).shape
(1000, 1000)`
Train_tf.txt
/images/image(1).png /annot/image(1).png  /images/image(3).png /annot/image(3).png  /images/image(5).png /annot/image(5).png  /images/image(7).png /annot/image(7).png  /images/image(9).png /annot/image(9).png /images/image(11).png /annot/image(11).png  /images/image(13).png /annot/image(13).png /images/image(15).png /annot/image(15).png  /images/image(17).png /annot/image(17).png  /images/image(19).png /annot/image(19).png  /images/image(21).png /annot/image(21).png /images/image(23).png /annot/image(23).png  /images/image(25).png /annot/image(25).png  /images/image(27).png /annot/image(27).png /images/image(29).png /annot/image(29).png
I converted all the label files to 1D with ..
`palette = {(255,255,255) : 0 ,
(0,0, 255) : 1 ,
(0,255,0) : 2,
(0,255,255) : 3,
( 255,255,0) : 4,
(255,0,0) : 5
      }

def convert_from_color_segmentation(arr_3d):
arr_2d = np.zeros((arr_3d.shape[0], arr_3d.shape[1]), dtype=np.uint8)
for c, i in palette.items():
    m = np.all(arr_3d == np.array(c).reshape(1, 1, 3), axis=2)
    arr_2d[m] = i

return arr_2d

for l_f in tqdm(label_files):
arr = np.array(Image.open(label_dir + l_f))
arr_2d = convert_from_color_segmentation(arr)
Image.fromarray(arr_2d).save(new_label_dir + l_f)
`
error : I gave it 4 batch it considers only two.
`tensorflow.python.framework.errors_impl.OutOfRangeError: FIFOQueue '_1_create_inputs/batch/fifo_queue' is closed and has insufficient elements (requested 2, current size 0)
[[Node: create_inputs/batch = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_UINT8], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](create_inputs/batch/fifo_queue, create_inputs/batch/n)]]
Caused by op u'create_inputs/batch', defined at:
File "fine_tune.py", line 207, in
main()
File "fine_tune.py", line 125, in main
image_batch, label_batch = reader.dequeue(args.batch_size)
File "/home/yared/Desktop/tensorflow-deeplab-resnet-master/deeplab_resnet/image_reader.py", line 179, in dequeue
num_elements)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/training/input.py", line 917, in batch
name=name)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/training/input.py", line 712, in _batch
dequeued = queue.dequeue_many(batch_size, name=name)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/data_flow_ops.py", line 458, in dequeue_many
self._queue_ref, n=n, component_types=self._dtypes, name=name)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 1328, in _queue_dequeue_many_v2
timeout_ms=timeout_ms, name=name)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 768, in apply_op
op_def=op_def)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2336, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/home/yared/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1228, in init
self._traceback = _extract_stack()
OutOfRangeError (see above for traceback): FIFOQueue '_1_create_inputs/batch/fifo_queue' is closed and has insufficient elements (requested 2, current size 0)
[[Node: create_inputs/batch = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_UINT8], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](create_inputs/batch/fifo_queue, create_inputs/batch/n)]]
`
Please, could you check my dataset? Let me sent you by email. What is wrong with it.

I understand the problem now. The way I generated the data list was wrong. That was the problem.
## we want /train/file1.png /labels_tf/file1.png with open('dataset/train_tf.txt', 'w+') as f:     for el in trn_lst:         el = el.decode('utf-8')[:-5]         f.write('/images/{}.png /annot/{}.png\n'.format(el, el))
I should have to use the above code to generate my data list. That is why it was not reading it.  Thanks for your information.


Made Issue and pr template

#3 Added .github and added ISSUE_TEMPLATE and Pull_request_template.md

Thanks @adityasimant for your contribution 🎉


SipSignallingPort flag spelling change

The New/Set/Get-CSOnlinePSTNGateway commands SipSignallingPort flag has now been changed to be spelt with only one 'L' (ie. SipSignalingPort). All of the documentation here needs to be updated to reflect this. You will see this change reflected in the PowerShell command docs here: https://docs.microsoft.com/en-us/powershell/module/skype/set-csonlinepstngateway?view=skype-ps

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

ID: df318fdb-6d58-86f8-de31-6eca533a9746
Version Independent ID: a2248abf-bdf0-2c22-2604-74b482156684
Content: Configure Direct Routing - Microsoft Teams
Content Source: Teams/direct-routing-configure.md
Service: msteams
GitHub Login: @CarolynRowe
Microsoft Alias: crowe

@jamescussen Thank you for submitting feedback and contributing to the docs. We are currently investigating this.

@jamescussen Thank you for reaching out and helping improve MS Docs. It looks like the typo has been fixed in the interim. Please confirm from your side.

@jamescussen Thank you for submitting feedback. We understand that this issue has been resolved.
Please feel free to re-open this issue if there is a specific area of the docs that we can improve or make better. Thank you


Add support for VisionOS

Im not exactly sure how hard this would be, but curious if adding support for VisionOS platform would be possible?
Of course I can use VisionOS (Made for iPad) target, but you lose the native look and feel of the platform by doing so.

Hey @ismyhc
Thanks for opening an issue, this is totally possible. I just created a PR, https://github.com/GigaBitcoin/secp256k1.swift/pull/491, let me know if this works for you or if any additional changes might be needed. 😁

Hey @ismyhc 👋
Thanks for opening an issue, this is totally possible. I just created a PR, #491, let me know if this works for you or if any additional changes might be needed. 😁

Awesome!
So, I think it's working as expected, but something to note. And this happens on main branch too, when I add the package via package manager, it also adds zkp.
When I try and build, it get 70 duplicate errors. If I remove zkp framework it builds.

Just created a new release including the change https://github.com/GigaBitcoin/secp256k1.swift/releases/tag/0.16.0
For the 70 duplicate errors you're seeing, this is expected because the libraries secp256k1 and zkp this package publishes are effectively the same thing. Basically, libsecp256k1 has a base version and an experimental version where the experimental version is nearly identical except it includes additional features not yet ready for Bitcoin.
If you found any of this helpful, I would greatly appreciate it if you could star this repo 😁

Just created a new release including the change https://github.com/GigaBitcoin/secp256k1.swift/releases/tag/0.16.0
The 70 duplicate errors you're encountering are expected. This is because the secp256k1 and zkp libraries published by this package are essentially identical. Essentially, libsecp256k1 has a base version and an experimental version. The experimental version is almost the same as the base version but includes additional features not yet ready for Bitcoin.
If you found any of this helpful, I would greatly appreciate it if you could star this repo 😁

Awesome! Thanks for the quick turnaround. Star coming up!


Use full URLs in template identifiers

This pull request solves this issue:
https://github.com/EGI-FCTF/cloud-info-provider/issues/15

:-1:
Could you squash the fixup commits?


'URL is invalid' with some URL

Hi, I'm using guzzle 5.3 ('guzzlehttp/guzzle' v5.3.x-dev, 'guzzlehttp/ringphp' v1.1.0, 'guzzlehttp/streams' v 3.0.0) with laravel 4.2 and  I got this error while trying to get HTML stream of some website  (getbootstrap.com in this case and with other website too):
Error creating resource: [message] URL is invalid: getbootstrap.com [file] /.../vendor/guzzlehttp/ringphp/src/Client/StreamHandler.php.
How can I solve this error? is that a 'bug' or just a 'normal behavior' with such URL?
Thanks !

What URL are you using?

this URL : getbootstrap.com ! (without http(s) prefix)

Can you try with http(s)://? Not sure if the stream handler can guess the protocol for you.

Yes, this is the prob: the stream handler can't guess the protocol!
I try it with 'http' prefix and it's work.

So is your issue resolved then? :smile:

You can say ! ^___^
Thanks !


NOTICK suspend count

The suspend count in the current implementation of the Fiber cache does not work correctly meaning that all checkpoints end up being deserialised.
This changes fixes this issue by ensuring the suspension count is always updated before the cache is updated, and that the correct suspension count is added to the cache value.

I don't think this change is sufficient as the cache needs to be updated too.
I changed the get method on the cache to this to add some logging:
override fun get(key: FlowKey, suspendCount: Int): FlowFiber? {
        val fibre = cache.getIfPresent(key)
        return if(null == fibre) {
            logger.info("Fibre not found in cache: ${key.id}")
            null
        } else if (fibre.suspendCount == suspendCount) {
            logger.info("Fibre found in cache: ${key.id}")
            fibre.fiber
        } else {
            logger.info("Fibre found in cache but at wrong suspendCount (${fibre.suspendCount} <-> $suspendCount): ${key.id}")
            null
        }

//        return cache.getIfPresent(key)?.takeIf { it.suspendCount == suspendCount }?.fiber
    }

Running this in the combined worker confirms that it never hits the cache, only messages like these are logged:
Fibre found in cache but at wrong suspendCount (2 <-> 3): 82130e29-14e9-4fbc-92cb-901145b995b4-INITIATED
...
Fibre found in cache but at wrong suspendCount (5 <-> 6): 82130e29-14e9-4fbc-92cb-901145b995b4-INITIATED

Generally LGTM, but technically this is my PR so I can't approve it


Correct the Typo in the code segment in the doc which will lead to errors

Correct the Typo in the code segment in the doc [1] which will lead to errors
[1] https://docs.wso2.com/display/IS550/Private+Key+JWT+Client+Authentication+for+OIDC
Below code segment ” should be as " . Otherwise it will be displayed as an XML error in identity.xml if you copy and paste from the doc.
  <Property name=”TokenEndPointAlias">sample url</Property>

Updated by correcting the quotes in [1]
https://docs.wso2.com/display/IS550/Private+Key+JWT+Client+Authentication+for+OIDC


Feature/azure

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rust-script >= 0.23.0 fails with current version of snakemake

Snakemake version
8.25.1
Describe the bug
rust-script>=0.23.0 fails with the current version of snakemake since snakemake provides an outdated command line.
Logs

Minimal example
Use rust-script with a version >= 0.23.0, with a snakefile
workflow/Snakefile
---
rule all:
    input:
        "bla.txt"

rule bla:
    output:
        "bla.txt"
    script:
        "scripts/bla.rs"

and a rust script
workflow/scripts/bla.rs
---
std::fs::File::create(&snakemake.output[0]).unwrap();

The snakemake execution will fail with either the argument '--dep <dep>' cannot be used multiple times or unexpected argument '--features' found.

Thanks for reporting this @jackerschott. The issue seems to be that the conda-forge package for rust-script is stuck on v0.22.0, hence why this didn't get flagged by failing tests (as the tests use v0.22.0).
I'll try and get the conda-forge package updated so we can get a fix in for this

It seems like the issue still exists even after updating the conda package to 0.35. Probably there has been some change after v0.22 causing some incompatibility issue.


How to make yt-dlp to not download again same video if title and size match even if it does not exist in the archive?

DO NOT REMOVE OR SKIP THE ISSUE TEMPLATE

[X] I understand that I will be blocked if I intentionally remove or skip any mandatory* field

Checklist

[X] I'm asking a question and not reporting a bug or requesting a feature
[X] I've looked through the README
[X] I've verified that I have updated yt-dlp to nightly or master (update instructions)
[X] I've searched known issues and the bugtracker for similar questions including closed ones. DO NOT post duplicates
[X] I've read the guidelines for opening an issue

Please make sure the question is worded well enough to be understood
How to make yt-dlp to not download again same video if title and size match even if it does not exist in the archive?
I have a youtube channel with many videos.
I deleted the archive.txt. However all videos exist except a few ones maybe.
How I can make yt-dlp to not download videos that match BOTH title and size and add them to the archive?
command that is use: yt-dlp  --cookies-from-browser firefox  --limit-rate 800k --write-description --embed-metadata --download-archive archive.txt -o "%(title)s_[%(id)s].%(ext)s" https://www.youtube.com/channel/videos
Provide verbose output that clearly demonstrates the problem

[X] Run your yt-dlp command with -vU flag added (yt-dlp -vU <your command line>)
[X] If using API, add 'verbose': True to YoutubeDL params instead
[X] Copy the WHOLE output (starting with [debug] Command-line config) and insert it below

Complete Verbose Output
yt-dlp -vU
[debug] Command-line config: ['-vU']
[debug] Encodings: locale UTF-8, fs utf-8, pref UTF-8, out utf-8, error utf-8, screen utf-8
[debug] yt-dlp version<EMAIL_ADDRESS>from yt-dlp/yt-dlp [f10589e34] (zip)
[debug] Python 3.11.2 (CPython x86_64 64bit) - Linux-6.1.0-15-amd64-x86_64-with-glibc2.36 (OpenSSL 3.0.11 19 Sep 2023, glibc 2.36)
[debug] exe versions: ffmpeg 5.1.4-0 (setts), ffprobe 5.1.4-0
[debug] Optional libraries: Cryptodome-3.11.0, brotli-1.0.9, certifi-2022.09.24, mutagen-1.46.0, requests-2.28.1, sqlite3-3.40.1, urllib3-1.26.12, websockets-None
[debug] Proxy map: {}
[debug] Request Handlers: urllib
[debug] Loaded 1798 extractors
[debug] Fetching release info: https://api.github.com/repos/yt-dlp/yt-dlp/releases/latest
Latest version<EMAIL_ADDRESS>from yt-dlp/yt-dlp
yt-dlp is up to date<EMAIL_ADDRESS>from yt-dlp/yt-dlp)

This is probably easiest to do with some external script.
You can fetch the playlist data as json to stdout with yt-dlp --dump-json --flat-playlist $channelurl, this will give you the video URL, Title, Duration, and various other details.
Then compare those titles to what you have, and launch yt-dlp to download videos you don't already have.
I don't think it's possible to predict the size of a video before downloading it, but the playlist will at least tell you the video duration and you can compare that to an existing video, though it might be a second or two different from the downloaded video duration.

Not replacing existing video files is already the default behavior.


CUDA and NVIDIA Driver error in WSL2

Environment
Windows build number: 21327
Your Distribution version: Ubuntu 18.04
Whether the issue is on WSL 2 and/or WSL 1: WSL2

Steps to reproduce
I had installed WSL and configured CUDA and NVIDIA drivers. Everything was running perfectly fine and the code successfully getting executed on GPU. Meanwhile, WSL got closed automatically and now is showing error "RuntimeError: Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from http://www.nvidia.com/Download/index.aspx"
Then I re-installed the NVIDIA driver and CUDA by following instructions on https://docs.nvidia.com/cuda/wsl-user-guide/index.html . But when I execute "./BlackScholes", I get an the error:

Nvidia-smi.exe is working fine

Expected behavior
When I run the ./BlackScholes, I should get output like

Actual behavior
getting above posted error in ./BlackScholes and " No NVIDIA derivers found error" while executing program on GPU
Has anyone encountered such issue? Kindly help

This is a known issue, @craigloewen-msft  posted it yesterday over at #6617

/dupe #6617
This is known and fixed internally, we are working on getting a build out for it! More details in the linked post. : )


Bedrock offline punish issue

Describe the bug
Bedrock players with * before their username are not able to be interacted with (unpunished, punished) if they are offline.
To Reproduce
Steps to reproduce the behavior:

Try to punish offline bedrock player

Server Information:

Sever Software: Paper 1.19.1
Database: sqlite
Java Version: 17

Additional information
plugin ver 1.2.3

Describe the bug Bedrock players with * before their username are not able to be interacted with (unpunished, punished) if they are offline.
To Reproduce Steps to reproduce the behavior:

Try to punish offline bedrock player

Server Information:

Sever Software: Paper 1.19.1
Database: sqlite
Java Version: 17

Additional information plugin ver 1.2.3

This isn't really a plugin or spigot issue.
This is a feature request to support Floodgate/Geyser players and I'll label it as such. This will be added to the todo list of things to add.
Thank you for your suggestion.


Unreasonable amount of time spent in getting function string

After a simple profiling of a covalent example, it was found that almost 98% of the total time (to dispatch) was spent in get_serialized_function_str inside which, It seems like getting imports is main the culprit. We need to modify/move this function so that dispatching a job doesn't take a long time when a lot of electrons are involved.
Example used for profiling:
@ct.electron
@qml.qnode(qml.device('default.qubit', wires=1))
def calculate(x):
    for _ in range(30):
        qml.RX(x, wires=0)
        qml.RY(x, wires=0)
    return qml.expval(qml.PauliZ(0))

@ct.lattice
def parallalize(x_list):
    values=[]
    for x in x_list:
        values.append(calculate(x))
    return values

job_id=parallalize.dispatch(x_list=np.arange(50))

Time taken to dispatch ~ 2-3 minutes
Afterwards the following in covalent/_shared_files/utils.py : get_serialized_function_str was commented out,
# imports = _get_imports_from_source()
ct_decorators = []  # _get_cova_imports(imports)

Then the time taken gets reduced to ~ 0.005 seconds
This issue blocks the PR https://github.com/AgnostiqHQ/covalent/pull/66 as it will most likely amplify the impact.

related to #66

Difference between the develop branch and the PR https://github.com/AgnostiqHQ/covalent/pull/123.


Error (cannot build dynamic articulation with more than 64 links) when loading some instances with loader.load_kinematic(urdf_path)

System:

OS version: MacOS Big Sur
Python version (if applicable): Python 3.8.10
SAPIEN version (pip freeze | grep sapien): sapien==1.0.0rc2

Describe the bug
I downloaded the script from https://sapien.ucsd.edu/docs/latest/tutorial/rendering/camera.html and modified the index of the instance and got a bug.
original:
    loader = scene.create_urdf_loader()
    loader.fix_root_link = True
    urdf_path = '../assets/179/mobility.urdf'
    # load as a kinematic articulation
    asset = loader.load_kinematic(urdf_path)
    assert asset, 'URDF not loaded.'

mine:
    loader = scene.create_urdf_loader()
    loader.fix_root_link = True
    urdf_path = '../assets/13027/mobility.urdf'
    # load as a kinematic articulation
    asset = loader.load_kinematic(urdf_path)
    assert asset, 'URDF not loaded.'

and I got this message:

[2021-07-07 14:14:52.532] [SAPIEN] [error] cannot build dynamic articulation with more than 64 links
[1]    35806 segmentation fault  /opt/anaconda3/envs/detection/bin/python

It seems that asset = loader.load_kinematic(urdf_path) does not work.
This is the 13027 folder in the dataset (which contains a keyboard with 100+ parts)

I observed this error when there are too many parts in one instance, and I have not been able to render images for many instances in the Keyboard category. How can I fix that problem?
Thanks!

Thanks for the report and it has been fixed and pushed to https://github.com/haosulab/SAPIEN-Release/tree/nightly
You can build the Linux version with docker_build_wheels.sh immediately.
Mac version will need to wait for the next release, which should happen in about a week.

Thanks for updating!
However, I tried this version on my Ubuntu server as well as my Macbook:
git submodule update --init --recursive
sudo ./docker_build_wheels.sh

Release Mode
Using bin path /opt/python/cp36-cp36m/bin/python
Using include path /opt/python/cp36-cp36m/include/python3.6m
Running command
====================Version Data====================
Git Revision Number: 60553ec95809a028c0c1554ac091155e144d51c3
Git Branch: nightly
Build Datetime: ********
Version Number: change_me_at_build_time
Host Name: ********
====================================================

I ended up receiving the following error:
auditwheel: error: cannot access ./dist/sapien-change_me_at_build_time-cp39-cp39-linux_x86_64.whl. No such file

How can I fix that? Thanks!

Changing the content of /python/VERSION to an actual version number (e.g. 1.0, 2.0) should probably fix the issue.

Thanks, I am able to build SAPIEN on my server.
However, I get the following error when running the 'camera.py' from  https://sapien.ucsd.edu/docs/latest/tutorial/rendering/camera.html .

[1]    69322 segmentation fault (core dumped)  python camera_original.py

and it returns 139.

I found that it was caused by this line:
renderer = sapien.VulkanRenderer()
How to fix it?
Thanks!

Do you mean a single line renderer = sapien.VulkanRenderer() crashes on your server? This has not happened to me. What is the hardware on your server? I have only tested with Nvidia GPU so far.

Yes. For example, with the following code:
    print('1')
    engine = sapien.Engine()
    print('2')
    renderer = sapien.VulkanRenderer()
    print('3')
    engine.set_renderer(renderer)

I got:
1
2
[2021-07-12 22:28:18.353] [svulkan2] [error] GLFW error: X11: The DISPLAY environment variable is missing
[2021-07-12 22:28:18.353] [svulkan2] [warning] Continue without GLFW.
[1]    88373 segmentation fault (core dumped)  python camera.py

('3' never got printed)
If I set offscreen_only=True:
    print('1')
    engine = sapien.Engine()
    print('2')
    renderer = sapien.VulkanRenderer(offscreen_only=True)
    print('3')
    engine.set_renderer(renderer)

I got:
1
2
[1]    88869 segmentation fault (core dumped)  /home/*****/miniconda3/envs/sapien/bin/python

both returns 139.
I am using Nvidia GPU as well.

Does it also happen with the release version of SAPIEN?
Yes - try install vulkan-utils and what is the result of vulkaninfo?
No - It does not make sense at all to me, but just in case, make sure you install the compiled wheels in the wheelhouse folder.

Yes. When I used the the release version of SAPIEN, I still got the error "segmentation fault" as shown above.
After I use the command ssh -X to connect with my server, install vulkan-utils and run vulkaninfo, it returns the error
ERROR: [Loader Message] Code 0 : /usr/lib/i386-linux-gnu/libvulkan_radeon.so: wrong ELF class: ELFCLASS32
ERROR: [Loader Message] Code 0 : /usr/lib/i386-linux-gnu/libvulkan_intel.so: wrong ELF class: ELFCLASS32
[1]    157893 segmentation fault (core dumped)  vulkaninfo

However, when I run dpkg --print-architecture, it returns
amd64

And when I run dpkg --print-foreign-architectures, it returns
i386

Besides, when I change my code into
renderer = sapien.VulkanRenderer(offscreen_only=True)

I still got the same error as shown above.

if vulkaninfo does not work, it means your driver is not configured properly for Vulkan and SAPIEN will certainly crash. However, I am not sure why your vulkaninfo tries to use AMD and Intel cards. Maybe you can try setting environment variable VK_ICD_FILENAMES=/usr/share/vulkan/icd.d/nvidia_icd.json (Make sure this file actually exists, if not, you have an incomplete Nvidia driver installation), and test vulkaninfo and SAPIEN again.


calclimit test for mmo results in instable behaviour

In traffic.performance.legacy.performanc.py  in the function calclimits seems to be a small bug.
In line 228 there is a test for maximum mach number. If you set the speed above this maximum mach number the limit speed is set to this maximum mach number minus 0.01.
limspd      = np.where((M > mmo), vmach2cas((mmo - 0.01), alt), limspd)
This results in an oscillating  behaviour where the pilot.tas speed is set up and down all the time when operating at max speed.
My suggestion is to make the test equal to the new limit the speed is set to:
So M > mmo - 0.01 and vmach2cas((mmo - 0.01), ...
Or M > mmo and vmach2cas((mmo), ...
Wkr,
René

Thanks René, implemented in 901f27d.


chore(interpreter): rename wrapping_* opcodes

Wrapping doesn't make sense here, these should match the actual opcode name as defined in the yellow paper.

It's EVM opcodes, this is not the place for docs


P100 stopped working all of a sudden with HomeKit

Describe The Bug:

All of a sudden, my Tapo P100 has stopped working all of a sudden without me changing anything. I can still control it using the Tapo app, however. (also, using the 'accessories' tab in the Homebridge UI doesn't work either.) I have removed the accessory/plugin from Homebridge and re-added it, and it didn't help...
To Reproduce:

not sure
Expected behavior:

Turn the plug on and off (doesn't happen)
Logs:
Nothing showing in logs

Plugin Config:
{
            "name": "Tapo Smart Platform",
            "username": "****",
            "password": "****",
            "devices": [
                {
                    "name": "Fan",
                    "host": "<IP_ADDRESS>",
                    "type": "Plug"
                }
            ],
            "platform": "TapoP100"
        }

Environment:

Plugin Version: homebridge-tapo v1.4.7
Homebridge Version: v1.3.4
Node.js Version: v14.17.3
NPM Version: v6.14.13
Operating System: hb-service (i think)

@apatsufas Any ideas on how to fix this?

I have also noticed that there are no logs whatsoever for this plugin, so I have no idea what was happened

Ok, i sorted it... Somehow removing "type": "plug" fixed it... very odd

Hello @ChopsKingsland. The issue you are describing seems weird. Indeed if no type is defined the plug-in defaults to the plug type. It also seems weird you are not seeing any logs. My best guess is that something went wrong with the cached state of the accessory in homebridge went wrong.

Just to add some extra context to anyone like me running into 111 Error: connect like Errors.
@ChopsKingsland 's comment of removing the type: "plug" item in the config.json file fixed the issue for me too. Even after removing/installing homebridge-tapo and Updating Homebridge itself etc.
Not sure why this change suddenly made it start working again 🤷🏻   but give it a go if you're running into similar errors.
@apatsufas Here's the previous erroneous logs from my Homebridge UI FYI:
[15/11/2021, 17:07:12] [Tapo Smart Platform] 111 Error: connect EHOSTUNREACH 192.XXX.X.XX:XX
[15/11/2021, 17:07:12] [Tapo Smart Platform] Get Device Info failed

Other information:
Plugin Version: homebridge-tapo v1.4.9
Homebridge Version: v.1.3.6
P100 Firmware Version: 1.4.9
P100 Hardware Version: 1.20.0

@James-Bovis thank you for your feedback. I have one question that might help me identify the issue. Are you setting the configuration manually in the config file or are using the plugin settings UI in Homebridge UI?

@apatsufas I set the plug-in up originally in the Homebridge UI first where I selected the “Plug” option as the device type in the drop down menu.
To remove the device type option, I edited the JSON directly in the Homebridge UI editor.
Hopefully that answers your question :)


Drag offset is incorrect in Firefox

Steps to reproduce:
1. git clone git@github.com:moroshko/react-chessboard.git
2. cd react-chessboard
3. npm install
4. npm start
5. Open http://localhost:3000/examples/dist/index.html in Firefox
6. Click on the "+" of the King, and start dragging
You'll see that the cursor is no longer on the "+"

(In Chrome, the cursor stays on the "+", which is the expected behaviour)
Firefox 38.0.5
OS X Yosemite 10.10.3

Retina?

@gaearon Nope

Unfortunately I don't have time to fix this in the following three weeks (I'm preparing for a conference talk). The problem is likely to be in this function. It's trying to get around browser bugs with Retina/non-Retina screens, but it's possible that non-Retina Firefox behavior is wrong. I'd gladly accept a PR fixing it.

I'm closing because I'm unable to reproduce and I don't have a Retina-less screen. As I wrote above, there is a specific place in code where these calculations happen, so it shouldn't be hard to fix and send a PR once you reproduce the problem reliably.


Incomplete doc for RasterStatus::kSkipAndRetry

The doc for RasterStatus::kSkipAndRetry seems incomplete.
  // Frame is dropped and a new frame with the same layer tree is
  // attempted.
  //
  // This is currently used to wait for the thread merger to merge
  // the raster and platform threads.
  //
  // Since the thread merger may be disabled,
  kSkipAndRetry,

And it has been like this since it was added.

Also, the doc for kEnqueuePipeline has an extra ".

I would like to take this one if no one's working on it.

I would like to take this one if no one's working on it.

That would be really helpful!

Awesome then could you assign this to me??

I would like to work on this issue. can you assign this to me?

Hi, feel free to submit a PR. The assignment doesn't mean much.

I have sent the PR

Hi @dkwingsmt ,
I've addressed the incomplete documentation for RasterStatus::kSkipAndRetry in compositor_context.h.
In the PR, I've clarified the behavior when the thread merger is disabled and provided insights into potential performance implications when threads aren't merged. This addition offers a clearer understanding of the enum value's purpose and behavior.
Please review the PR when you have a moment. Thanks!

hey @dkwingsmt , any update??

Fixed by https://github.com/flutter/engine/pull/44880.


Linux: Build with use_static_cpp=yes by default

This enables -static-libgcc -static-libstdc++ which help make custom Linux
builds more portable (official builds have been using this option for years).

Note: I need to do some tests before merging as for official builds on Ubuntu 14.04 i386 I'm actually not using those, I probably ran into issues in the past and forgot to document them...
https://github.com/godotengine/godot-build-scripts/blob/master/build-linux/build.sh#L15-L17
Edit: "Solved", see below.

Note: Distro packagers should typically set this option to no to keep using the distro-provided shared libgcc and libstdc++. This option is only for builds that need to be shared with users on other distros (which is the main use case for custom Godot builds, but not the one Linux distro packages).

Note: I need to do some tests before merging as for official builds on Ubuntu 14.04 i386 I'm actually not using those, I probably ran into issues in the past and forgot to document them...

Ah I did document the issue in the commit log: https://github.com/godotengine/godot-build-scripts/commit/3319757d9d5c650a7fbcaeef7585287f0408a007
The problem is that it seemed to cause crashes on Ubuntu 18.04 i386 for some reason: https://github.com/godotengine/godot/issues/31743#issuecomment-573013032.

I amended the commit to apply that change only to 64-bit, as we still need to figure out why it would crash on Ubuntu 18.04 i386 with that option. Likely a Ubuntu bug, but nasty enough not to make this the default for i386.
I was lazy so this outright forces use_static_cpp off for 32-bit, but making an architecture-specific option with different default values and still the possibility to override it is a bit of a pain.

Cherry-picked for 3.2.4.


Fix enum mapping for bundleBehaviour and sourceType

Motivation
Fix native asset graph compatibility with legacy js asset graph.
Changes

Added mapping for bundle behaviour in getAssetGraph
Added mapping for source type in getAssetGraph

Checklist

[ ] Existing or new tests cover this change

Looks like I broke a test with this change. Looking into it before merging.


Install turicreate on Google colab

Has anyone managed to install turicreate in colab. I have the following dependencies error:
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
xarray-einstats 0.2.2 requires numpy>=1.21, but you have numpy 1.18.5 which is incompatible.
tensorflow-probability 0.16.0 requires gast>=0.3.2, but you have gast 0.2.2 which is incompatible.
tables 3.7.0 requires numpy>=1.19.0, but you have numpy 1.18.5 which is incompatible.
librosa 0.8.1 requires resampy>=0.2.2, but you have resampy 0.2.1 which is incompatible.
jaxlib 0.3.14+cuda11.cudnn805 requires numpy>=1.19, but you have numpy 1.18.5 which is incompatible.
jax 0.3.14 requires numpy>=1.19, but you have numpy 1.18.5 which is incompatible.
datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.
albumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.2.9 which is incompatible.

nvcc version es :
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Mon_Oct_12_20:09:46_PDT_2020
Cuda compilation tools, release 11.1, V11.1.105
Build cuda_11.1.TC455_06.29190527_0

Any advice to be able to use it on colab ?

That error message is usually nothing to worry about. You should still be able to import turicreate.
However getting turicreate to use Google colab GPUs is probably not going to happen. TuriCreate is only setup to use a few old versions of TensorFlow.


[BEAM-3013] Prototyping lull-tracking for Python

r: @charlesccychen
cc: @bjchambers
This change is to allow the state sampler in Python to report when too much time has been spent on the same state (default: 5 minutes). When more than 5 minutes have been spent, the worker will report it.
This change requires the sampling thread (normally a pure-C thread) to acquire the GIL, to access the logging module. For this, I laid out a convention to acquire locks in a certain order - to avoid deadlocks.

Run Python PostCommit

jenkins: retest this please

jenkins: retest this please

jenkins: retest this please

jenkins: retest this please

jenkins: retest this please

Changes Unknown when pulling ee53714c2d108c57ae6fadd92110db81a47acf8b on pabloem:lull-tracking-py into ** on apache:master**.

Changes Unknown when pulling f0ec52eb4fa995efde233cbf322295cd05200bda on pabloem:lull-tracking-py into ** on apache:master**.

Changes Unknown when pulling f0ec52eb4fa995efde233cbf322295cd05200bda on pabloem:lull-tracking-py into ** on apache:master**.

Changes Unknown when pulling 55e23e7e1012b978e2f1dc427da163aa88d5c2ac on pabloem:lull-tracking-py into ** on apache:master**.

Run Python PostCommit

Changes Unknown when pulling 902d7dc8ddab4ac054becc469444a7c7fe9a5378 on pabloem:lull-tracking-py into ** on apache:master**.

@charlesccychen let me know if this seems reasonable. Here's a screen shot of a job that ran with this.

Run Python PostCommit

Changes Unknown when pulling 4770be2ef358571870942f25db48576798ee87a8 on pabloem:lull-tracking-py into ** on apache:master**.

Changes Unknown when pulling 4770be2ef358571870942f25db48576798ee87a8 on pabloem:lull-tracking-py into ** on apache:master**.

Changes Unknown when pulling 4770be2ef358571870942f25db48576798ee87a8 on pabloem:lull-tracking-py into ** on apache:master**.

Changes Unknown when pulling 4770be2ef358571870942f25db48576798ee87a8 on pabloem:lull-tracking-py into ** on apache:master**.

@charlesccychen I've enabled the StateSamplerInfo to communicate time since transition for the progress reporter.

Changes Unknown when pulling 3bc34eb5eaee80a75d69ba5df90bddc5f4b79980 on pabloem:lull-tracking-py into ** on apache:master**.

Changes Unknown when pulling 5a1945e9ab18e057aedd0011ea6e289157f9c1f8 on pabloem:lull-tracking-py into ** on apache:master**.

Ben has no experience with the Python SDK. @chamikaramj could you merge?

@chamikaramj  could you merge please?

Retest this please

Retest this please

Run Python PreCommit

Run Python PreCommit

Looks like there's a conflict in 'statesampler.pyx'. Could you rebase and fix that ?

Finally passed. Thanks Cham.


Is it possible to create a structure to create related lessons without losing the advantages of having many voices involved in the process?

Based on suggestion at PyCAR 15 feedback thread
@mikejcorey writes:

Could we organize a (small) committee of Python folks to facilitate this? The group could take suggestions and feedback such as what's happening on this thread, post a recommendation, get some more feedback, and take a yea-nay vote?
I hate committees as much as the next journalist, but Python has made a big impact on the NICAR community, and I don't want to ruin it by big-footing ourselves into the rest of the conference.

@esagara writes:

Can we standardize curriculum throughout the Python track (standardize may not be the right word)? Can we make it so concepts learnt in an intro course at the beginning of the day/conference are reinforced/expanded upon in more advanced classes further on in the day/conference? It would also help if we split up the main PyCAR course to sessions throughout the week. We could fill in gaps where needed from the more advanced classes.

@chrislkeller writes:

I think my own stumbling point in thinking through this is mentioned in your last heading: without losing the advantages of having many voices involved in the process. The gorgeous thing about NICAR is someone can obtain knowledge and share it with others in a really direct way. No one wants to lose that. No one wants a curriculum committee to thumbs up or thumbs down sessions.
But I too felt those who want to learn would benefit from core concepts being taught, explained and demonstrated over and over - repetition, practice and muscle memory of you will. Landmarks, touchstones, repeated use of terms, doing and seeing are all valuable when it comes to learning.
And this speaks to the scope of what we did with PyCAR right? Devil's advocate: If there are two sessions in which participants will be scraping websites, did we need to do that during PyCAR?

We've made an attempt to centralize planning of different coding avenues (Python, R, Ruby, JS) by having a couple of volunteers in each help organize "tracks" that range from novice to more intermediate/advanced. The other goal here by doing this is to help keep lines of communication open between teachers ahead of the conference while everyone plans there classes. We'll see if and how it works and adjust accordingly for 2017.