feat: separate service port and allow configure container port

Allow configuration of container port
Separate container port from service port. Useful for situtation when container can run on port that does not require root user (>1024) where service port can directly be 80 or 443 to be mapped accordingly to a domain name
Change hostname to <IP_ADDRESS> otherwise external service might never send a request to the pod
FIx a document error where additionalEnv is dict but example is list

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

The default is already set inside charts/langfuse/values.yaml so upgrading the port wont require one to set the field, unless user would like to override or intentionally unset that value. Helm does use this values file as the default value not just an example one. The same goes for other fields like .Values.service.port  or .Values.langfuse.nodeEnv as they dont have any fallback value inside the chart logic.

My bad you're right, I got confused because on our side we have a custom Values.yaml :)

Let me know if you want to cover this case. Personally, I find it a bit excessive since we will have to loop the envs and figure out whether PORT has already been set.

It's possible using additionalEnvs but I agree that it's an edge case and we should not cover it

This is exactly why I made the update, because in the old document, the default value for it is [] which is an empty list. I just updated that to {}

You're right also for this one, I read the contrary.
Everything looks good for me for this PR, thanks! cc @marcklingen

thanks for your review @mautini and for the contribution @luong-komorebi!


fixed a path in docs

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thanks @voith


current consumption with BLE Nano 2

I've been trying to get my BLE Nano 2 current consumption down.  Right now I have it at ~2.8mA with DCDC enabled.
If I call sd_app_evt_wait() in my loop right after the application starts up, my current consumption drops to ~0.33mA.  Once I use a central (my iPhone) to connect to the Nano 2, the current consumption jumps up to 2.8mA and stays there even after the central disconnects, and even if I call sd_app_evt_wait() again in my loop.
My sketch looks roughly like this..
BLEService tempService("CCC0");
BLEFloatCharacteristic tempCharacteristic("CCC1", BLERead | BLENotify);
BLEDescriptor tempDescriptor("2901", "Temperature");

void setup(void)
{
	ble.setDeviceName("temp");
	ble.setAdvertisedServiceUuid(tempService.uuid());
	ble.addAttribute(tempService);
	ble.addAttribute(tempCharacteristic);
	ble.addAttribute(tempDescriptor);

	ble.setEventHandler(BLEConnected, connectHandler);
	ble.setEventHandler(BLEDisconnected, disconnectHandler);

	ble.begin();
}

void loop(void)
{
	ble.poll();
        sd_power_dcdc_mode_set(NRF_POWER_DCDC_ENABLE);
        sd_app_evt_wait();
}

2.8mA is pretty good, but I'd like it go back down to 0.33mA :D

Hi @gtalusan,
Are you using the RedBear core?

Hi @sandeepmistry,
I'm using your arduino-nRF5 core.

@gtalusan Were you able to fix the problem? I'm currently trying to get lower than 1.2mA in advertising
I found lot of articles/forums where people say they have around 0.1-0.2mA consumption, but I'm not able to replicate that. Also everyone writes that in DEEP SLEEP mode it consumes only 6uA, which I also wasn't able to replicate as my board consumes around 350uA in DEEP SLEEP mode.
Maybe you had some luck with lowering current consumption?

@unCleanCode Sort of... I hard reset the core and go to sleep right away.

And what's your current consumption after that?
How did you hard reset it?

It's down to 0.33mA.
        connected = false;
	ble.setEventHandler(BLEConnected, [=] (BLECentral &central) {
		connected = true;
	});
	ble.setEventHandler(BLEDisconnected, [=] (BLECentral &central) {
		sd_nvic_SystemReset();
	});

and in the event loop,
	if (!connected) {
		sd_power_dcdc_mode_set(NRF_POWER_DCDC_ENABLE);
		sd_power_mode_set(NRF_POWER_MODE_LOWPWR);
		sd_app_evt_wait();
	}

Thanks! I'll test it today
Were you ever using DEEP SLEEP mode?

Nope, didn't get that far.. my IoT device (temp sensor) runs for weeks being polled twice an hour on a beefy 18650.  I put a solar panel and TP4056 charge circuit on it and it'll go forever.

My device is also powered by 2x18650 3000mAh. Simple calculations shown me that most of the current consumed in advertising mode when device is waiting for connection and doing no useful job, so DEEP SLEEP mode can increase device lifetime from 15days to around 90 !!!

Wow, I just found that my second board works perfectly fine with exactly the same code (consumptio in advertising is below 100uA), but second one is around 300-400uA !
Do you know what, except the code itself device saves when power is off? Maybe there is some kind of factory reset?

I hope this is relevant to @gtalusan 's issue and possibly leads to a bug fix/clarification: I have an ID107 (NRF51882) fitness tracker board and I just had a very similar problem. My current consumption was about 60 µA after reset, then after the first connect and disconnect it was in the mA range.
I found out that the reason is that sd_app_evt_wait() always immediately returns after the first connection, so the device never really goes to sleep. More poking revealed that there is an interrupt pending after leaving ble.poll() which causes sd_app_evt_wait() to return immediately. The interrupt number is 22 which is SWI2_IRQn or also known as SD_EVT_IRQn. I don't really know if poll() is supposed to clear the pending interrupt but I think it should and this might be a bug. As far as I've understood this interrupt is supposed to tell the application that there was a BLE event. So I think after poll() has handled all events it should not be pending when leaving poll(). By the way I also tried calling poll() in a loop until the interrupt is cleared but it never gets cleared and so that loop is stuck.
What works for me is manually clearing the pending interrupt after leaving poll() in the main loop:
#include <nrf_nvic.h>//interrupt controller stuff

void loop() {
  // wait for event/interrupt (low power mode)
  sd_app_evt_wait();
  // some event woke us up --> poll peripheral
  blePeripheral.poll(); //this does not clear SD_EVT_IRQn for some reason, even in a loop
  sd_nvic_ClearPendingIRQ(SD_EVT_IRQn); //this fixes low power as the stuck IRQ is cleared
}

This then gives me the same power consumption as after reset when disconnecting.
The reason @gtalusan 's code works is I think because the reset also clears the pending interrupt. I am also unsure if my manual clearing of the interrupt might drop events important for the BLE peripherial. I think that poll() should actually exit without an pending interrupt, but maybe @sandeepmistry can shine some light on that.

@arglurgl good catch. I've noticed this behavior on my project as well.
NRF51822 with S110 doesn't stay in sleep mode after connecting/disconnecting so I just made it non connectable and broadcast the data for now. I'll have to give your code a try tonight.

Got a chance to test @arglurgl s fix and can confirm (in my case anyway) that adding sd_nvic_ClearPendingIRQ(SD_EVT_IRQn); in the main loop after sleeping that it does indeed go back to sleep properly. Thanks @arglurgl !

@gtalusan and @arglurgl
I am developing a project based on nrf51822 and use @sandeepmistry Arduino core for it.
My Problem:
After following all of your valuable comments, I wrote a code for the project. It turns out that in Advertising mode the nrf51822 consumes 1.76mA and when connected to a central device(in this case my phone) it is 4.98mA. I don't understand where I am going wrong. 😕 ❓
I cannot get the board to consume 0.33mA even after following gtalusan's comment and arglurgl's comment
My code:
#include <BLEPeripheral.h>
#include <nrf_nvic.h>
//////////////
// Hardware //
//////////////
#define LED_PIN    20// LED on pin 20
#define LED_ACTIVE LOW // Pin 20 LED is active low
#define LED_DEFAULT LOW
///////////////////////
// BLE Advertisments //
///////////////////////
const char * localName = "nrf51822 LED";

BLEPeripheral blePeriph;
BLEService bleServ("58be27e8-f4f0-43e7-9997-34166889a7c3");
BLECharacteristic ledChar("58be27e8-f4f0-43e7-9997-34166889a7c3", BLERead | BLEWrite | BLENotify, 20);
bool connectedToCentral = false;
const unsigned char* ledState = NULL;
const char* ledison = "ON";

void setup()
{
  Serial.begin(115200); // Set up serial at 115200 baud
  pinMode(LED_PIN, OUTPUT);
  digitalWrite(LED_PIN, !LED_ACTIVE);

  setupBLE();
}

void loop()
{
  blePeriph.poll();
  ledState = ledChar.value();
  if (!blePeriph.connected()) {
    sd_power_dcdc_mode_set(NRF_POWER_DCDC_ENABLE);
    sd_power_mode_set(NRF_POWER_MODE_LOWPWR);
    sd_nvic_ClearPendingIRQ(SD_EVT_IRQn); //this fixes low power as the stuck IRQ is cleared
    sd_app_evt_wait();
  }
  else
  {
    if (ledChar.written())
    {

      if (memcmp(ledison, ledState, 2) == 0)
      {
        digitalWrite(LED_PIN, LED_ACTIVE);
        ledChar.setValue(ledison);
      }

      else if (memcmp((const char*)"OFF", ledState, 2) == 0)
      {
        digitalWrite(LED_PIN, !LED_ACTIVE);
        ledChar.setValue("OFF");
      }

    }

  }
}
void setupBLE()
{
  // Advertise name and service:
  blePeriph.setDeviceName(localName);
  blePeriph.setLocalName(localName);
  //blePeriph.setManufacturerData(manufacturer, 26);
  blePeriph.setAdvertisedServiceUuid(bleServ.uuid());

  // Add service
  blePeriph.addAttribute(bleServ);

  // Add characteristic
  blePeriph.addAttribute(ledChar);
  blePeriph.setEventHandler(BLEConnected, connectHandler);
  blePeriph.setEventHandler(BLEDisconnected, disconnectHandler);

  // Now that device6, service, characteristic are set up,
  // initialize BLE:
  blePeriph.begin();
  sd_ble_gap_tx_power_set(-12);

  // 300ms; in multiples of 0.625ms.
  blePeriph.setAdvertisingInterval(412);

  // Set led characteristic to default value:
  //ledChar.setValue(!LED_ACTIVE);
}

void connectHandler(BLECentral& central) {
  // central connected event handler
  Serial.print(F("Connected event, central: "));
  Serial.println(central.address());
  connectedToCentral = true;
}

void disconnectHandler(BLECentral& central) {
  // central disconnected event handler
  Serial.print(F("Disconnected event, central: "));
  Serial.println(central.address());
  sd_nvic_SystemReset();
}

Please help!

One remark: Did you reset and power-cycle the board after uploading? If not, the JTAG hardware stays activated an draws additional current. Try disconnecting everything after flashing and then only reconnecting power.

Right !!I just did that. Now it draws around 0.3ma
But after using the SPI library for interfacing with LORA- Ra01 it uses 1.4ma even after removing the sed connections and power cycling

@arglurgl
When I'm using sd_power_dcdc_mode_set(NRF_POWER_DCDC_ENABLE); with nRF52840 E-Byte E73-2G4M08S1C modulem I get consumption increase to 30-35mA instead of 6-6.5mA after this command is executed in my code - the issue is somehow related to NRF_POWER_DCDC_ENABLE on that module. Removing sd_power_dcdc_mode_set(NRF_POWER_DCDC_ENABLE); solves the 30mA issue.
Any ideas?


Map layer names one to one and allow Dwgs, Cmts and Eco layers

Using the exact layer names in Inkscape would allow you to choose front or back from your drawing. Additionally we should allow the Dwgs, Cmts and Eco layers (KiCad 4.0.7 seems to load them without complaints).
So the table from the README would become:

Inkscape layer name
KiCad layer(s)
KiCad legacy
KiCad pretty

F.Cu
F.Cu
Yes
Yes

B.Cu
B.Cu
Yes
Yes

F.Adhes
F.Adhes
Yes
Yes

B.Adhes
B.Adhes
Yes
Yes

F.Paste
F.Paste
Yes
Yes

B.Paste
B.Paste
Yes
Yes

F.SilkS
F.SilkS
Yes
Yes

B.SilkS
B.SilkS
Yes
Yes

F.Mask
F.Mask
Yes
Yes

B.Mask
B.Mask
Yes
Yes

Dwgs.User
Dwgs.User
Yes
Yes

Cmts.User
Cmts.User
Yes
Yes

Eco1.User
Eco1.User
Yes
Yes

Eco2.User
Eco2.User
Yes
Yes

Edge.Cuts
Edge.Cuts
Yes
Yes

F.Fab
F.Fab
--
Yes

B.Fab
B.Fab
--
Yes

F.CrtYd
F.CrtYd
--
Yes

B.CrtYd
B.CrtYd
--
Yes

My pull request #26 does this, If you are interested you could test my branch of this project.
The owner doesn't look very active anymore so I have no clue how long it will take for this to be merged.

Thanks, I am now using svg2shenzhen as it's a better workflow for me and has all the layers mapped one to one.


GPU memory exhaustion errors

via email from Samantha Esteves:

I’m really interested in getting GPU Richardson-Lucy deconvolution working on my machine (Windows10, Quadro M2200 4GB) and am running through the CElegans example notebook. But I get an out of memory error when I runt the deconvolution cell. I’m wondering if this is a true error (GPU requires more than 4GB of memory for this example?) or if there is a configuration error I should be looking into?

The fix in this case was to change the padding mode used on the images to avoid resizing them to the next highest power of 2 along each dimension:
# Use pad_mode = 'none' instead of default 'log2'
algo = fd_restoration.RichardsonLucyDeconvolver(n_dims=3, pad_mode='none').initialize()

Additionally, configuring these options will override the default TF behavior where it will attempt to preallocate nearly 100% of GPU memory for every python process (or jupyter kernel) using it, which can be problematic even with a single process:
session_config = tf.ConfigProto()
# allow_growth=True will allocate memory as needed rather than preemptively
session_config.gpu_options.allow_growth = True
session_config.gpu_options.per_process_gpu_memory_fraction = 1.0
res = {ch: algo.run(acqs[ch], niter=100, session_config=session_config) for ch in acqs}


libc issue on Ubuntu 20.04 LTS

Hello,
Last version of difftastic (0.39) introduce a dependancy on libc6 (>= 2.32)
difft -V
./difft: /lib/x86_64-linux-gnu/libc.so.6: version `GLIBC_2.33' not found (required by ./difft)
./difft: /lib/x86_64-linux-gnu/libc.so.6: version `GLIBC_2.32' not found (required by ./difft)
./difft: /lib/x86_64-linux-gnu/libc.so.6: version `GLIBC_2.34' not found (required by ./difft)

But on Ubuntu 20.04 LTS there is only libc6 2.31
apt-cache policy libc6
  Installed: 2.31-0ubuntu9.9
  Candidate: 2.31-0ubuntu9.9

Previous version of Difftastic works:
difft --version
Difftastic 0.38.0

Regards,

The same for me, I am on RHEL:
$ difft --version
difft: /lib64/libc.so.6: version `GLIBC_2.33' not found (required by difft)
difft: /lib64/libc.so.6: version `GLIBC_2.32' not found (required by difft)
difft: /lib64/libc.so.6: version `GLIBC_2.34' not found (required by difft)

Looks like ubuntu-latest on GitHub has changed to 22.04: https://github.blog/changelog/2022-11-09-github-actions-ubuntu-latest-workflows-will-use-ubuntu-22-04/
I'll change it back to 20.04 for the next release.

I've released 0.40.


Changing the height and the width of the circle

Signed-off-by: vzaisun<EMAIL_ADDRESS>

done yeah

done yeahh


Unit 5 [HANDS-ON BUG]: Training won’t run on A100 GPU

I have Colab Pro, so I’m trying to do the hands-on for Unit 5 on an A100 GPU, but I’m running into this error when I try to run mlagents-train:
/usr/local/lib/python3.10/dist-packages/torch/cuda/__init__.py:145: UserWarning:  NVIDIA A100-SXM4-40GB with CUDA capability sm_80 is not compatible with the current PyTorch installation. The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_70. If you want to use the NVIDIA A100-SXM4-40GB GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/
It seems the version of PyTorch used by the lab (torch-1.11.0) is out-of-date. I tried upgrading to the latest PyTorch and ran into the following 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. mlagents 0.31.0.dev0 requires torch<=1.11.0,>=1.8.0, but you have torch 2.0.1+cu118 which is incompatible.
I’m not sure if you can do anything about this at the moment or if ML-Agents needs to be updated first. I will pick one of the other GPUs and try again. If the bug can’t be fixed at the moment, I suggest adding a note to the top of the Colab about which GPUs are supported.
Link to my colab:
https://colab.research.google.com/drive/1tBgTYLTtswy2XQJycNg4HgW92eE2eD0L?usp=sharing
Material

Did you use Google Colab?
Yes

I have verified that training does work on V100 runtimes

Thanks for the info, we currently updating the ML Agents version with the official one since we're merging our Hugging Face integration in it.
I keep you updated.

We updated all the units with official integration of MLAgents 🤗 .
I'm closing the issue


API tweaks

When I call the API's then they are all handled via just the 2 re-usable funcitons

Refactoring for map usage


Memcache key warning

Change key is generated in get_many to make it compatible with Memcached.

@utek could you please write more about the problem you were facing?

@tvavrys
(tox) utek@DESKTOP-1M8UQ34:django-memoize$ tox -e django111-py27
GLOB sdist-make: django-memoize/setup.py
django111-py27 inst-nodeps: django-memoize/.tox/.tmp/package/1/django-memoize-2.2.0.zip
django111-py27 installed: DEPRECATION: Python 2.7 will reach the end of its life on January 1st, 2020. Please upgrade your Python as Python 2.7 won't be maintained after that date. A future version of pip will drop support for Python 2.7. More details about Python 2 support in pip, can be found at https://pip.pypa.io/en/latest/development/release-process/#python-2-support,coverage==4.5.4,Django==1.11.26,django-memoize==2.2.0,freezegun==0.3.12,funcsigs==1.0.2,mock==3.0.5,python-dateutil==2.8.1,pytz==2019.3,six==1.13.0
django111-py27 run-test-pre: PYTHONHASHSEED='2805323082'
django111-py27 run-test: commands[0] | coverage run runtests.py
Creating test database for alias 'default'...
System check identified no issues (0 silenced).
...............django-memoize/.tox/django111-py27/local/lib/python2.7/site-packages/django/core/cache/backends/base.py:245: CacheKeyWarning: Cache key contains characters that will cause errors if used with memcached: u':1:tests.tests.Adder.add.<tests.tests.Adder object at 0x7f6dc329f710>_memver'
  'used with memcached: %r' % key, CacheKeyWarning
django-memoize/.tox/django111-py27/local/lib/python2.7/site-packages/django/core/cache/backends/base.py:245: CacheKeyWarning: Cache key contains characters that will cause errors if used with memcached: u':1:tests.tests.Adder.add.<tests.tests.Adder object at 0x7f6dc329f850>_memver'
  'used with memcached: %r' % key, CacheKeyWarning
.django-memoize/.tox/django111-py27/local/lib/python2.7/site-packages/django/core/cache/backends/base.py:245: CacheKeyWarning: Cache key contains characters that will cause errors if used with memcached: u':1:tests.tests.Adder.add.<tests.tests.Adder object at 0x7f6dc329f8d0>_memver'
  'used with memcached: %r' % key, CacheKeyWarning
django-memoize/.tox/django111-py27/local/lib/python2.7/site-packages/django/core/cache/backends/base.py:245: CacheKeyWarning: Cache key contains characters that will cause errors if used with memcached: u':1:tests.tests.Adder.add.<tests.tests.Adder object at 0x7f6dc329f910>_memver'
  'used with memcached: %r' % key, CacheKeyWarning
........
----------------------------------------------------------------------
Ran 24 tests in 0.112s


Write directly to j's stdin and skip csv parsing

I had some problems with excel-stream:

did not support European Excel files (1,23 instead of 1.23)
csv-stream didn't handle j's quoted keys very well, resulting in keys like "name or name".

I first tried replacing the csv-stream dependency with the superior csv-parser, which solved problem 2. But I then realized j can output JSON too. It writes the raw numbers in that case (and takes care of problem 1), so excel-stream doesn't need to coerce anything. And of course, no CSV parsing necessary. Additionally, excel-stream writes directly to j's stdin with this PR.

Oh, and a third problem that's solved with this PR: j sometimes wrote two newlines at the end, which csv-stream (and csv-parser too) turned into an object with empty values.

Final note: indirectly, this PR is functionally tested by tabular-stream, which tests excel-stream with an xlsx, xls and ods file. Tests just passed on travis and appveyor. Only thing I didn't test is excel-streams CLI.


Understanding hap_eval results on latest combined small and large variant GIAB T2T benchmark

The latest GIAB draft T2T benchmark has shifted to a single VCF combining small and structural variants.
I've noticed that hap_eval's assessment of a given SV sample is substantially impacted by shifting to this new benchmark. I demonstrate the effect below on one public example VCF, but a similar trend appears with other SV callers and sequencing inputs. If we download an example SV VCF and the last two versions of the GIAB T2T draft benchmark as follows:
# Example SV VCF
wget https://downloads.pacbcloud.com/public/revio/2022Q4/HG002-rep1/analysis/HG002.m84011_220902_175841_s1.GRCh38.pbsv.vcf.gz
wget https://downloads.pacbcloud.com/public/revio/2022Q4/HG002-rep1/analysis/HG002.m84011_220902_175841_s1.GRCh38.pbsv.vcf.gz.tbi

# 20231107 T2T benchmark
wget -P NIST_HG002_DraftBenchmark_defrabbV0.012-20231107 https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data/AshkenazimTrio/analysis/NIST_HG002_DraftBenchmark_defrabbV0.012-20231107/GRCh38_HG002-T2TQ100-V1.0_stvar.vcf.gz
wget -P NIST_HG002_DraftBenchmark_defrabbV0.012-20231107 https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data/AshkenazimTrio/analysis/NIST_HG002_DraftBenchmark_defrabbV0.012-20231107/GRCh38_HG002-T2TQ100-V1.0_stvar.vcf.gz.tbi
wget -P NIST_HG002_DraftBenchmark_defrabbV0.012-20231107 https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data/AshkenazimTrio/analysis/NIST_HG002_DraftBenchmark_defrabbV0.012-20231107/GRCh38_HG002-T2TQ100-V1.0_stvar.benchmark.bed

# 20240215 T2T benchmark
wget -P NIST_HG002_DraftBenchmark_defrabbV0.015-20240215 https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data/AshkenazimTrio/analysis/NIST_HG002_DraftBenchmark_defrabbV0.015-20240215/GRCh38_HG2-T2TQ100-V1.0.vcf.gz
wget -P NIST_HG002_DraftBenchmark_defrabbV0.015-20240215 https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data/AshkenazimTrio/analysis/NIST_HG002_DraftBenchmark_defrabbV0.015-20240215/GRCh38_HG2-T2TQ100-V1.0.vcf.gz.tbi
wget -P NIST_HG002_DraftBenchmark_defrabbV0.015-20240215 https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data/AshkenazimTrio/analysis/NIST_HG002_DraftBenchmark_defrabbV0.015-20240215/GRCh38_HG2-T2TQ100-V1.0_stvar.benchmark.bed

Then given a hap_eval cmdline similar to this for each case:
hap_eval \
  --reference /path/to/GRCh38.fasta \
  --base NIST_HG002_DraftBenchmark_defrabbV0.012-20231107/GRCh38_HG002-T2TQ100-V1.0_stvar.vcf.gz \
  --interval NIST_HG002_DraftBenchmark_defrabbV0.012-20231107/GRCh38_HG002-T2TQ100-V1.0_stvar.benchmark.bed \
  --comp HG002.m84011_220902_175841_s1.GRCh38.pbsv.vcf.gz \
  --thread_count 8 >| t2t_20231107.stdout

The previous and latest GIAB T2T draft benchmark results are:
$ tail -2 t2t_20231107.stdout
Counter({'MM': 19571, 'MX': 920, 'FP': 579, 'FN': 550, '??': 139, 'XX': 71})
precision 0.9197 recall 0.9209 f1 0.9203
$ tail -2 t2t_20240215.stdout
Counter({'MM': 20364, 'MX': 402, 'FN': 360, '??': 146, 'XX': 39, 'FP': 10})
precision 0.9715 recall 0.9556 f1 0.9635

I'd like to get some insight as to whether the assessment on the newest benchmark should still be considered valid, or if this single-VCF benchmark format is interfering with hap_eval's design in a way that's biasing the result.

@ctsa we have found including small variants in the sv benchmark vcf improves variant comparisons which probably accounts for at least some of the performance improvements you are experiencing. We also made a number of changes to how the benchmark regions are defined, see text from the README, https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data/AshkenazimTrio/analysis/NIST_HG002_DraftBenchmark_defrabbV0.015-20240215/README.md, below. I assume these are responsible for the bulk of the difference in performance between the 20231107 and 20240215 versions of the benchmark.
- A single vcf is provided for small and structural variant benchmark sets and should be used for benchmarking either small and structural variants.
- This version of the benchmark now merges segdups and satellites within 40kb before checking if the assembly has any breaks in the alignment inside the repeat regions, so that it more conservatively excludes nearby satellites and segdups if there is a break in the alignment inside a satellite or segdup.
- Fixed issue with code not excluding dip.bed edges as intended.
- VDJ excluded from small variant and structural variant benchmark regions.

Thanks for pointing out these details @nate-d-olson. It will be great if the benchmark improvements explain at least some of the difference, but it's such a large change that it would be helpful to know if this shift in format would be expected to violate assumptions in hap_eval's design, etc. I won't have time to directly look at the shifted FP/FN cases for a bit so this would be helpful in deciding whether to transition to the new format.

The inclusion of SNVs and indels into the benchmark VCF will affect hap_eval's assessment. We can see this by filtering small events from benchmark VCF (with bcftools view -i '(ILEN >= 50 || ILEN <= 50)').
Here is my evaluation using original 20240215 VCF:
Counter({'MM': 20325, 'MX': 425, 'FN': 360, '??': 146, 'XX': 55, 'FP': 10})
precision 0.9697 recall 0.9537 f1 0.9616

And after bcftools to remove SNVs/indels:
Counter({'MM': 20395, 'MX': 981, 'FN': 483, '??': 134, 'XX': 126, 'FP': 30})
precision 0.9413 recall 0.9221 f1 0.9316

The 20231107 VCF produces the same results with or without the bcftools filter:
Counter({'MM': 19062, 'MX': 1303, 'FP': 579, 'FN': 550, 'XX': 197, '??': 139})
precision 0.8958 recall 0.8970 f1 0.8964

hap-eval will exclude small variants after clustering, which allow the small variants to contribute to a larger SV. Additionally, this allows multiple small events to be combine to match a larger event.
Including smaller events has a few different effects on the overall evaluation:

The size of some clusters will be extended due to nearby small variants, without including another nearby SV. This adds to the denominator of the difference threshold, changing some borderline cases from MX or XX to MM.
Small variants can "bridge" nearby SVs into larger clusters. This is why the total number of evaluated clusters is reduced when small variants are included as multiple SVs are included in a larger cluster. This reduces the number of FP and FN calls.
Small variants can make some clusters too complex, resulting in warnings for too many phasing combos and increasing the number of ?? clusters.

Thanks @DonFreed! I think I understand how to interpret the assessment differences with small variants now.


imake cannot exec cpp-5

imake reports "imake: Cannot exec /usr/local/Cellar/gcc/5.1.0/bin/cpp-5.".
My system actually has gcc installed from homebrew, and it's 5.2 instead of 5.1:
/usr/local/bin/cpp-5 -> ../Cellar/gcc/5.2.0/bin/cpp-5
I guess directing imake to look for cpp-5 from /usr/local/bin would fix.
Thanks!

Looks like we're currently hard-coding the version of GCC that exists at the time you installed imake: https://github.com/Homebrew/homebrew-x11/blob/master/imake.rb#L31-L33
So currently this means you have to reinstall imake whenever you upgrade GCC. There should be a better way to do this.

Gcc was installed on my system as a dependency required by imake. There was no gcc in any version in my system previously. It could be that gcc5.2 reporting itself 5.1?

Fix in #111; will merge when it's ready.

Thanks Misty!

Heh, was just about to look at this. Thanks Misty :bow:

Should be fixed; can you upgrade imake and retry?

It works great right now! Thanks for the fix!


Window function support

Is your feature request related to a problem? Please describe.
Windows functions: functions that are applied over windows of data. Here is a great illustration from DuckDB:

Valid expressions that can be run over windows are:

Aggregation expressions (e.g. sum(), mean())
Window expressions (e.g. first(), last())

In this proposal, the Window API is similar to the PySpark API.

We will create a new group of Expressions called WindowExpressions (similar to how we have "aggregation expressions")
Unlike aggregation expressions however, WindowExpressions do not change the cardinality of the dataframe/partitions
WindowExpressions also have attached context of the WindowSpec that they should run over
WindowSpec consists of:
a. (Non-optional, for now) partition_by: a column to partition the overall dataframe by - windows do not cross partition boundaries
b. (Optional) order_by: an expression to order each partition by
c. (Optional) row_between OR range_between: the granularity of each frame within each partition. Defaults to (START_PARTITION, END_PARTITION). row_between defines each frame by how many rows before/after the current row to consider as part of the frame (+1 row, -1 row). range_between defines a range of values that defines each frame (e.g. (-1 minute, +1 minute)).
Aggregation Expressions can also be run over a WindowSpec. In this case, they would not change the cardinality of the data, and will automatically be "broadcasted" over all data in the window.

As an initial implementation, Daft will not support:

WindowSpec without a partition_by ("global window specs")
WindowExpressions without a WindowSpec ("window expressions over a global window spec")

Proposed API:
To mirror the duckdb simple examples:
-- generate a "row_number" column with containing incremental identifiers for each row
SELECT row_number() OVER () FROM sales;
-- generate a "row_number" column, by order of time
SELECT row_number() OVER (ORDER BY time) FROM sales;
-- generate a "row_number" column, by order of time partitioned by region
SELECT row_number() OVER (PARTITION BY region ORDER BY time) FROM sales;
-- compute the difference between the current amount, and the previous amount,
-- by order of time
SELECT amount - lag(amount) OVER (ORDER BY time) FROM sales;
-- compute the percentage of the total amount of sales per region for each row
SELECT amount / sum(amount) OVER (PARTITION BY region) FROM sales;

from daft.exprs import Function as F, Window

# generate a "row_number" column with containing incremental identifiers for each row
df.with_column("row_number", F.row_number())  # ERROR: Daft will not support this global WindowSpec

# generate a "row_number" column, by order of time
df.with_column("row_number", F.row_number().over(Window(sort_by=["time"]))) # ERROR: Daft will not support this global WindowSpec

# generate a "row_number" column, by order of time partitioned by region
df.with_column("row_number", F.row_number().over(Window(partition_by=["region"], sort_by=["time"])))

# compute the difference between the current amount, and the previous amount, by order of time
df.with_column("prev_amount", col("amount").lag(1)) \
    .with_column("amount_diff", col("amount") - col("prev_amount"))

# compute the percentage of the total amount of sales per region for each row
df \
    .with_column("region_sum", df["amount"].sum().over(Window(partition_by=["region"]))) \  # ERROR: This is a global window spec
    .with_column("pct_sales_per_region", col("amount") / col("region_sum"))

Here are the examples with frames:
DuckDB:
-- Row-based ranges
SELECT points,
    sum(points) OVER (
        ROWS BETWEEN 1 PRECEDING
                 AND 1 FOLLOWING) we
FROM results;

-- Value-based ranges
SELECT "Plant", "Date",
    avg("MWh") OVER (
        PARTITION BY "Plant"
        ORDER BY "Date" ASC
        RANGE BETWEEN INTERVAL 3 DAYS PRECEDING
                  AND INTERVAL 3 DAYS FOLLOWING)
        AS "MWh 7-day Moving Average"
FROM "Generation History"
ORDER BY 1, 2;

# ERROR: Daft won't support global window specs
df.select("points", col("points").sum().over(Window(rows_between=(-1, 1))))

# ERROR: Daft won't support global window specs
df.select("points", col("points").sum().over(Window(range_between=(datetime.timedelta(days=-3), datetime.timedelta(days=3))))))

See Also:

DuckDB Windowing: https://duckdb.org/docs/sql/window_functions.html#aggregate-window-functions
PySpark Windowing: https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.Window.html

This kind of operations are essential.
polars rolling functions are a good reference too: https://docs.pola.rs/api/python/stable/search.html?q=rolling


Add support for trackHeight to Slider on iOS

This pull request adds support for a trackHeight prop to the Slider component.
tagging @lacker and @mkonicek because I deleted the last repo and had to create a new PR, so here we are. Old one was #11518
Tested by confirming in UIExplorer that the change works, but I can't get figure out how to update the UIExplorer expected result screenshot / get integration tests to pass. Visually you can confirm it works:

@lacker @mkonicek any issues with this? i couldn't find docs on how to update the integration test screenshots, but if you can point me in the right direction i'll do it

Honestly, it's been five months. I found another way to do this that didn't involve being ignored on a fairly trivial pull request


Revert "Replace Type's primitiveType getter with getContainedType"

Reverts PolymerLabs/arcs#2684
This should let me see if Travis will pass again with my last change removed.

Seems that I've introduced some issues, requesting a revert for now.


linuxKernel.kernels: update

Description of changes

Things done

Built on platform(s)

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

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[ ] Tested, as applicable:

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

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
23.05 Release Notes (or backporting 22.11 Release notes)

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

[x] Fits CONTRIBUTING.md.

To whoever merges this: please merge https://github.com/NixOS/nixpkgs/pull/218694 at the same time (to group the rebuilds together), assuming OfBorg is happy with it by then.

There's also https://github.com/NixOS/nixpkgs/pull/218282

Dupe of #218282

Duplicate of #218282, closing.

I tried searching for an existing PR but couldn't find it, sorry for the noise. 😓

No worries! The PR's title is usually "Linux kernel updates $date" for the future :)


Pylance server keep on restarting on big project

Environment data

Language Server version: v2022.9.41
OS and version: Ubuntu 20.04.5 LTS, 64-bit, Memory 31,2 GiB, Intel® Core™ i5-8500 CPU @ 3.00GHz × 6
Python version (& distribution if applicable, e.g. Anaconda): 3.10 and several projects on 3.6-3.8

Repro Steps

Launch VS Code,
Open a workspace with a lot of microservices (I have 105 folders and each is a project itself)
Wait for Python Language Server to start.

Expected behavior
Server starts.
Actual behavior
Server either keep on restarting or report it will not due to reoccurring error. The advice from https://github.com/microsoft/pylance-release/issues/3307 to use "openFilesOnly" did not help. If change "python.analysis.logLevel" to "Trace" while server keeps restarting, it will crush and will report "The server will not be restarted". If relaunch VS Code, it automatically opens previously opened project (my 105 folder workspace) and keeps trying to restart the language server forever.
Unfortunately, I cannot provide you with the full log, as the project is proprietary.
Logs

<--- Last few GCs --->

[386654:0x140c0274c000]    46915 ms: Mark-sweep (reduce) 10.4 (15.1) -> 10.4 (12.1) MB, 194.4 / 0.0 ms  (average mu = 0.063, current mu = 0.001) last resort; GC in old space requested
[386654:0x140c0274c000]    47108 ms: Mark-sweep (reduce) 10.4 (12.1) -> 10.3 (12.1) MB, 193.0 / 0.0 ms  (average mu = 0.024, current mu = 0.000) last resort; GC in old space requested

<--- JS stacktrace --->

FATAL ERROR: CALL_AND_RETRY_LAST Allocation failed - JavaScript heap out of memory
[Info  - 11:09:04 AM] Connection to server got closed. Server will restart.
[Info  - 11:09:05 AM] (389994) Pylance language server 2022.9.41 (pyright 59bdc42e) starting

<--- Last few GCs --->

[420468:0x25f4025e4000]    42784 ms: Mark-sweep (reduce) 11.1 (15.9) -> 11.1 (12.9) MB, 99.1 / 0.0 ms  (average mu = 0.024, current mu = 0.003) last resort; GC in old space requested
[420468:0x25f4025e4000]    42804 ms: Mark-sweep (reduce) 11.1 (12.9) -> 11.1 (12.9) MB, 19.5 / 0.0 ms  (average mu = 0.019, current mu = 0.001) last resort; GC in old space requested

<--- JS stacktrace --->

FATAL ERROR: CALL_AND_RETRY_LAST Allocation failed - JavaScript heap out of memory
[Error - 11:16:47 AM] The Pylance server crashed 5 times in the last 3 minutes. The server will not be restarted. See the output for more information.

Please create a pyrightconfig.json file in your project's root directory and add the following to this file:
{
    "verboseOutput": true
}

Then reload your project and reproduce the out-of-memory condition. The output should now include more details. Look for lines in the output logs that start with "Heap stats: ". Please provide the last few of these heap stat outputs prior to the crash.

Adding pyrightconfig.json with suggested setting did not help much as there are no lines start with "Heap stats: ". I tried to place this config into directory which is being opened as multi-root workspace (/home/sommary/work/root/<my_company_name>) and in its parent directory (/home/sommary/work/root) also.
So I've collected full logs. In them I have replaced my company name and projects names. I hope this will let you figure out the reason of the issue.
python_language_server_output_redacted.txt

OK, the fact that you're using a multi-root workspace is a really important detail that you didn't previously mention. How many workspace roots do you have in your project?
When pylance is used in a multi-root workspace configuration, it creates a new instances of the type checker service for each root. Each service instance manages its own in-memory cache of types as it performs type checking, and it empties this cache if it determines that its cache could overflow the available heap space. However, each type checker service instance doesn't have knowledge of the other instances. I suspect what's happening here is that the sum total of memory used by all of the type checker service instances is consuming all of the memory in the heap without any one service instance knowing that it is in danger of doing so.
We'll need to discuss potential mitigations or workarounds. In the meantime, potential workarounds might include reducing the number of workspace roots (and potentially even switching to a single-root workspace), adding a pyrightconfig.json in a subset of the root directories that includes an "exclude": "." — effectively telling the type checker not to attempt any type checking for any files under that root, or opening a single workspace root at a time in your editor.

There are like 100 workspace roots in the project. Using multi-root workspace is more appropriate than opening a single workspace root because I often work with several projects at the same time in a day. And the next day my task may involve other combination of projects.
I'll try to follow you advice about excluding some roots and let you know.
Do you consider to rework current logic of type checker for multi-root workspace in not so distant future?

I've added some additional logic to track heap consumption across multiple type evaluator service instances. This should prevent the crashes you're seeing when using pylance with a project with many workspace roots.

This issue has been fixed in prerelease version 2022.10.11, which we've just released. You can find the changelog here: CHANGELOG.md


The mask doesn't take into account values with a decimal point

Firstly I'd like to say thanks for sharing this plugin its been a real help for my work.
The mask (with a precision of x) doesn't take into account the decimal point in the value passed to it.
e.g. with a precision of 2
Value 1.00 would be displayed as 0.01
Value 100.00 would be displayed as 1.00
Is there an option I'm missing or was the mask designed this way?
Kind Regards
Richard

@richardho sorry for taking so long to reply here. the precision parameter is designed to you set up how many decimal places you wan't to allow. I don't know if I got what you wanna do, but if you still have problems with this, just comment here and I promise I will look at this ASAP.

@plentz Thank you for coming back to me.  The point I'm was trying to make was that if your existing dB data already has decimal places contained within it the maskMoney({precision:2}) call doesn't take them into account when displaying the data to the screen.
e.g. the dB record = 1.5 but on the page it would appear as 0.15
My next point I feel is relevant to the data type of the field.  When you correct the data to being 1.50 and write it back to the database, the number is again stored as 1.5 and I'm back to square one.  I do believe however that this is due to my database column being a NUMBER datatype so it only stores numbers without any 'unnecessary' padding, so if I was to configure the column to be a VARCHAR2 then it would have retained the zero and then it would have appeared correctly on further interrogations of the data but this intern would then generate its own problems when I need to perform calculations with the values.   This is obviously not your issue, but I just wanted to illustrate where I was coming from.
I hope this clears up my initial query.
Richard


Fix typo in roadmap.

Serializtion => Serialization

Hi @agriffard, I'm your friendly neighborhood .NET Foundation Pull Request Bot (You can call me DNFBOT). Thanks for your contribution!
You've already signed the contribution license agreement. Thanks!
The agreement was validated by .NET Foundation and real humans are currently evaluating your PR.
TTYL, DNFBOT;

This is a duplicate of https://github.com/dotnet/corefxlab/pull/1003.


Moto E (XT1022) Has No Audio on Recorded Video

Recording a video shows the image but without any apparent audio.

False alarm -- problem was with my development machine.


[Task] Write Esc Run GCP doc

Currently blocked on this guide for the same reason that I am blocked on the Azure guide.
In the current state, it seems like the dynamic credentials functionality for ESC is only able to be used for pulumi up and (I think?) CI/CD automation assuming said automation leverages environment variables.


mason-lspconfig don't recognize cmakelang

Problem description
I can manually install cmakelang server within :Mason ui, but mason-lspconfig.nvim with following minimal conf :
return {
    "williamboman/mason-lspconfig.nvim",
    dependencies = {
        "williamboman/mason.nvim",
        "neovim/nvim-lspconfig",
    },
    opts = {
        ensure_installed = {
            "cmakelang", -- cmake
        },
    }
}

throws warning :
mason-lspconfig.nvim [mason-lspconfig.nvim] Server "cmakelang" is not a valid entry in ensure_installed. Make sure to only provide lspconfig server names.

Why do you think this is an issue with mason-lspconfig.nvim?
cmakelang should be a valid entry for  mason-lspconfig as it is installable by MasonInstall command
Neovim version (>= 0.7)
NVIM v0.9.4
Build type: RelWithDebInfo
LuaJIT 2.1.1692716794
Operating system/version
ubuntu
I've manually reviewed the Nvim LPS client log (:LspLog) to find potential errors

[x] Yes

I've recently downloaded the latest plugin version of mason.nvim, mason-lspconfig.nvim, and nvim-lspconfig

[X] Yes

Affected language servers
cmakelang
Steps to reproduce
Just try to include cmakelang in ensure_installed
Actual behavior
Warning :
Server "cmakelang" is not a valid entry in ensure_installed

Expected behavior
Install cmakelang automatically
LspInfo
N/A

LspLog
No response
Healthcheck
mason: require("mason.health").check()

mason.nvim ~
- OK mason.nvim version v1.8.1
- OK PATH: prepend
- OK Providers:
  mason.providers.registry-api
  mason.providers.client
- OK neovim version >= 0.7.0

mason.nvim [Registries] ~
- OK Registry `github.com/mason-org/mason-registry version: 2023-10-30-common-movie` is installed.

mason.nvim [Core utils] ~
- OK unzip: `UnZip 6.00 of 20 April 2009, by Debian. Original by Info-ZIP.`
- OK wget: `GNU Wget 1.20.3 built on linux-gnu.`
- OK curl: `curl 7.68.0 (x86_64-pc-linux-gnu) libcurl/7.68.0 OpenSSL/1.1.1f zlib/1.2.11 brotli/1.0.7 libidn2/2.2.0 libpsl/0.21.0 (+libidn2/2.2.0) libssh/0.9.3/openssl/zlib nghttp2/1.40.0 librtmp/2.3`
- OK gzip: `gzip 1.10`
- OK tar: `tar (GNU tar) 1.30`
- OK bash: `GNU bash, version 5.0.17(1)-release (x86_64-pc-linux-gnu)`
- OK sh: `Ok`

mason.nvim [Languages] ~
- WARNING luarocks: not available
  - ADVICE:
    - spawn: luarocks failed with exit code - and signal -. luarocks is not executable
- WARNING Composer: not available
  - ADVICE:
    - spawn: composer failed with exit code - and signal -. composer is not executable
- WARNING PHP: not available
  - ADVICE:
    - spawn: php failed with exit code - and signal -. php is not executable
- OK Ruby: `ruby 2.7.0p0 (2019-12-25 revision 647ee6f091) [x86_64-linux-gnu]`
- OK node: `v20.9.0`
- OK Go: `go version go1.21.3 linux/amd64`
- OK RubyGem: `3.1.2`
- WARNING julia: not available
  - ADVICE:
    - spawn: julia failed with exit code - and signal -. julia is not executable
- OK python: `Python 3.8.10`
- OK java: `Picked up _JAVA_OPTIONS: -Djava.util.prefs.userRoot=/home/stabei/.config/java`
- OK cargo: `cargo 1.73.0 (9c4383fb5 2023-08-26)`
- OK javac: `Ok`
- OK npm: `10.1.0`
- OK pip: `pip 23.3.1 from /home/stabei/.local/lib/python3.8/site-packages/pip (python 3.8)`
- OK python venv: `Ok`

mason.nvim [GitHub] ~
- OK GitHub API rate limit. Used: 0. Remaining: 5000. Limit: 5000. Reset: Mon 30 Oct 2023 02:23:10 PM EDT.

### Screenshots or recordings

_No response_

Hey! This is because there's a mapping missing between mason <-> lspconfig. PR is very much welcomed (see for example https://github.com/williamboman/mason-lspconfig.nvim/pull/304), else I'll get around to it soon.

Thanks, I will post a PR as soon as I 've some free time


Basic ember setup

Hej guys,
I'm fully new to ember and drf, so I hope I won't bother. I had some problems getting used to the available adapters, so I was lucky when I found your app. I used your example to integrate it. I got the basic api running, which returns a queryset.
{
    "meta": {
        "next": null,
        "next_link": null,
        "page": 1,
        "previous": null,
        "previous_link": null,
        "count": 1,
        "total": 1
    },
    "recipe": [
        {
            "pk": 1,
            "name": "Foo",
            "ingredients": [
                2,
                1
            ],
            "portions": 1,
            "date_created": "2014-12-30T20:54:32.523138Z",
            "date_updated": "2014-12-30T20:54:32.523138Z"
        }
    ]
}

Now I had to setup ember like that to make use of the api response:
    App = Ember.Application.create();

    App.Router.map(function() {
        this.resource('index', {path: '/'});
    });

    App.IndexRoute = Ember.Route.extend({
        model: function() {
            return $.getJSON('/api/recipes').then(function(data) {
                return data.recipe;
            });
        }
    });

Now I would like to ask, if there's any way to generate the ember routes dynamically?
Do you know an app example, which includes the ember setup and which helps greenhorns like me to kickstart their ember-drf experience?
Thanks a lot!

Generating routes at runtime is an advanced topic; I'd want to be sure that you really want to do that before you head down that path. With that being said this talk from Ember Conf covered that topic a little IIRC.
What I might suggest is to use Ember CLI and generate code with that. It comes with Ember Data and should work right out of the box with this Django adapter. All Ember docs should still apply except instead of using globals like App.IndexRoute you'll be using ES6 modules.
npm install ember-cli
and then generate some code with:
ember g model recipe
ember g route recipes
ember g route recipes/edit
and then you can run it:
ember serve
and open <IP_ADDRESS>:4200 in your browser.

Thanks @jerel I'll give it a try!


Set custom donation/contribution tip based on percentage and not just fixed dollar/euro amount

User story
As a donor, I can set a custom platform tip percentage so that I can make my tip bigger/smaller based on donation size but am not limited to 10%, 15%, 20%. I'd love to be able to set a 1-5% tip for Open Collective. As a Collective admin, I'd love to be able to set the standard/suggested tip to a custom percentage the same way I can set the default suggested donation amount.
Best solution for this problem
This would look like an additional dropdown + number input. There is already a custom amount option so there just needs to be a way to set it to a percentage rather than a fixed dollar amount.
MVP
A dropdown for % vs $ next to the amount input box.
Metrics
How many people use the feature is the best indication of need/demand/impact
Documentation
Some documents might need to be updated to explain the feature so people know about it and are comfortable using it. Some in-page explanation/UI will likely encourage its use.

Triage Template (team only)
This template is for members of the team to triage for prioritisation. For more guidance see https://www.loom.com/share/369ab467fbc64dec848085d38ff57ca0:
P1 high frequency, high impact
P2 low frequency, high impact
P3 high frequency, low impact
P4 low frequency, low impact
Examples of high impact - a problem affects users during an essential process (expenses and payments > onboarding and registration > contributing) with no workaround.
High frequency - >10% of users affected (measured as a proportion of total potential users for this case).

Hi @CaptainStack, you can pick "Other" in the drop-down, then set any amount you wish to contribute:

@Betree Yes you can, but you cannot set that custom amount to a custom percentage like say 1%. The lowest amount you can donate based on percentage is 10% as one of the fixed dropdown options, but if you wanted to donate a custom amount based on percentage you'd have to convert to dollars/euros first.

It seems relatively easy and clear to me, but forwarding the feedback to @opencollective/design in case they want to integrate something for the next contribution flow iteration. Thank you!

My only other thought is that when you set up a donation tier you cannot set the default Open Collective tip. I believe it defaults to 15%. While I am very happy to contribute to Open Collective, and am even very happy to see what strikes me as a relatively high and strong default, I do ultimately think the default tip should be configurable by the collective admin. Just my opinion!

Could be resolved by https://github.com/opencollective/opencollective/issues/4897

My only other thought is that when you set up a donation tier you cannot set the default Open Collective tip. I believe it defaults to 15%. The closet you can come to setting another default value here is to modify the query parameters in the URL, which I consider a hack, albeit a relatively nice to have and easy to use one.

The problem with 'not' being able to set the default tip is it could be perceived as misleading or not worth all the fees (compared to other platforms) to consumers/customers of certain types of groups (such as nonprofits).
For instance, OpenProducer is/was planning on using its collective to process everything from tax deductible donations, sponsorships, ticket sales, and a variety of services. To the consumer/donor, the platform tip looks like an additional fee being passed on to them on top of the advertised/quoted price.
For example what looks to be a monthly sponsorship at $100/month....

...defaults to a $115/month charge

As @CaptainStack noted, we can set the default to "No Thank You" by modifying the query parameters in an embed URL, but that could introduce further confusion/distrust if sponsors/donors are paying a different price via the collective tier.
As noted in our ongoing Slack discussion on the topic, this is probably less of an issue for supporters of open source projects (hosted by https://opencollective.com/opensource) - that said, it doesn't even look like OSC collectives default to a platform tip (let alone provide a way to set some options).
https://opencollective.com/mautic/contribute/usd100-month-20890/checkout
https://opencollective.com/obsproject/contribute/silver-sponsor-8101/checkout?interval=month&amount=750
https://opencollective.com/phpfoundation/contribute/backers-34283/checkout?interval=month&amount=5
If the default tip is only applicable to OCF hosted collectives, I understand the previous (and unresolved concerns) in https://github.com/opencollective/opencollective/issues/4268

It looks our OCF hosted collectives no longer have the ability to modify the query parameters in the URL. So basically...as I tried to point out in https://github.com/opencollective/opencollective/issues/6252#issuecomment-1371332212 we're locked into passing an additional charge to donors, sponsors, ticket buyers, and other customers that will have no idea what Open Collective is.
Am I missing something or is the 15% default tip something that OCF collectives need to pass on to their customers and run the risk of misleading them?

Platform Tips are part of Open Collective business model and are essential to the platform's sustainability. It's not possible to consider turning that off without an alternative revenue model.

this is probably less of an issue for supporters of open source projects (hosted by https://opencollective.com/opensource)

Open Source Collective doesn't have platform tips enabled because we share half our revenue with Open Collective Inc. on every transaction. Open Collective Foundation doesn't charge a fee on credit card donations and Open Collective Inc. adds the tip element on those transactions only.
I thought that would be useful context 👍

@BenJam @znarf I appreciate the additional context from the platform/engineering side. My one thought/recommendation as a longtime, active community member/contributor is... had I known 1) this was only an issue with OCF collectives (not sure about self-hosted); 2) people like myself, @CaptainStack, and probably several others wouldn't have the ability adjust the default (not eliminate the tip) so not to fool/mislead our customers (and their customers) after being called out for 'abusing' the system... I would not have switched one collective from OSC to OCF and onboarded two others.
As an OCF customer, I have to admit (which I've done in the same Slack discussion and parallel one in #ocf) that I feel like this should have been brought up as a potential red flag during preliminary vetting discussions where we were very clear about our use cases (some examples here) and supporters.

Platform Tips are part of Open Collective business model and are essential to the platform's sustainability. It's not possible to consider turning that off without an alternative revenue model.

Putting my community hat back on, I totally understand and have tried to be very proactive in terms of enabling community contributions (code and funds). But as an OCF customer, the platform (in its current state) is now unusable so we may need to reevaluate OCF as a host and if/how we'll use the platform.

Open Source Collective doesn't have platform tips enabled because we share half our revenue with Open Collective Inc. on every transaction. Open Collective Foundation doesn't charge a fee on credit card donations and Open Collective Inc. adds the tip element on those transactions only.

I feel like this is a missed opportunity since most OSC collectives (and their supporters) understand that Open Collective is open source, would have no problems with the tip (at least being available), and would be more likely to tip!
Thinking about this now... after getting more and more feedback from y'all and other collective/team members. I'd strongly recommend the tip be available across all hosts and we give the collective admins the ability to set the defaults on a per/tier basis. Pretty sure @CaptainStack has already done a much better job describing the functionality in this issue and the Slack discussions. In the short term, could you please give us back the ability to set the default to "No Thank You" by modifying the query parameters in an embed URL? All the people/collectives I'm aware of are doing this for their customers while at the same time are extremely aware and supportive of the need to help contribute and sustain the Open Collective platform and team.

When editing a recurring contribution, it's not possible to edit an ACH payment method or add a new one.

I would not have switched one collective from OSC

Just to play this out: your $100 credit card donation through Open Source Collective would have attracted a $10 fee from Open Source Collective, $5 of which Open Source Collective pays to Open Collective Inc. so you're net $90 (ignoring payment processor costs). A $100 credit card donation through Open Collective Foundation attracts no fee, you get $100, and the user can decide to accept the optional tip. It's their choice.
There's a bit of history and a statistical outcome that's important here. Three years ago, Open Collective Inc. changed its pricing to allow hosts that do not charge fees to use the platform for free. Platform tips were introduced around this time to enable Open Collective Inc. to recoup some of the cost of keeping the platform free for these users.
Why the 15% default? Well, after some experimentation, we found that 15% was the point at which Open Collective Inc. would cover the cost of providing the platform for free to these hosts. Last month 55% of users accepted a tip, averaging to a 7.6% tip on just over 3,000 eligible contributions. As you can see this is a close (but, importantly, optional) match to the amount Open Source Collective pays Open Collective Inc. on every transaction.
So, there it is, tips keep the platform free for hosts that do not charge fees and the default is set to 15% tip because this is the default that covers the cost of keeping the platform free.

OSC collectives (and their supporters) understand that Open Collective is open source, would have no problems with the tip (at least being available), and would be more likely to tip!

The philosophy applied here is that we don't charge fees on transactions that Open Collective Inc. already benefits from. We may experiment with switching to platform tips in the future, but for the moment we're happy supporting Open Collective Inc. as we are.

First off, I appreciate all the continued detail and as a 'Community Contributor group' member I'm hopeful I'll have the opportunity to contribute and help sustain the platform.
As a customer setting up to go all-in with Open Collective, OpenProducer simply can't and won't run the risk of misleading our customers, clients, and supporters by selling a sponsorship/donation/service tier at quoted price and then:

they tip because they think they'd be supporting us
they don't even notice the extra charge until after the fact
we have to spend a lot of time educating our customers (and their customers) about Open Collective, open source, and why it's important to support something that might not even be aware of (or care about)
they choose another service/provider that doesn't attempt to pass an additional cost to them (or their customers and supporters)

We were OSC hosted and simply would not have applied to OCF if we'd known about these potential issues. I'd say this is an edge case, but I'm seeing more and more music/arts/media orgs hosted by OCF and I can't imagine we're the only ones who share these fears and concerns.
Similar situation with the Drupal Contribution collective we just brought online. I would have recommended OSC and am very concerned that several other OCF hosted Drupal collectives (like these event-related ones) are or could run similar issues.
With Drupal beginning to enable funding tools on Drupal sites (including drupal.org), I'd imagine most would either use OSC or another platform/tool (internal or external).
I'd imagine there could similar dynamic/dilemma with an even larger open source project and OCF hosted community collective.
Unlike Drupal (that for a variety of reasons was an early adopter), the largest open source project/economy on the planet hasn't embraced Open Collective (as an alternative to Patreon or internal/external solutions). I'd assume having to explain these issues won't help with the already steep learning curve.
These issues would be resolved by making the tip behavior available and consistent across all hosts. More projects and orgs would adopt (and use!) Open Collective = more contributors and funds to sustain the (open source) Open Collective platform and team.

These issues would be resolved by making the tip behavior available and consistent across all hosts.

Let's just say this was possible. In additon to giving collective admins the ability to set default tips for each tier... what if they could hide or disable in exchange for paying a platform fee (similar to these folks)?
If you try to make a donation on their demo, you'll see they also provide good inspiration for donors/supporters to covering the fees.

After a bit more follow-up w/ Mike in #ocf :raised_hands: I think the best path forward (at least for OCF collectives I'm part of/supporting/advising) is to use (or continue to use) external platforms for fundraising (some examples here) and adhere to their fee structure for these types of transactions.
At the same time our OSC hosted contributor collective (if enabled) can help with some of the tasks outlined at the bottom of https://github.com/opencollective/opencollective/issues/6252#issuecomment-1385812818.

Here's another example of a platform that allows users to set defaults. It's to cover the fees, so not exactly the same. Still think something like https://github.com/opencollective/opencollective/issues/6252#issuecomment-1384886976 that enables admins options on setting or hiding defaults (for a fee) would enable them best serve their customers/supporters while increasing revenue to sustain the platform/team (if the tip was also an option on OSC collectives).
Admin

Donate form

@gusaus These comments are off-topic with the original issue, let's move this discussion elsewhere.
We will not bring back the platform tip parameter in the contribution flow, it's unfair to other collective admins (who are not tech-savvy enough to integrate an embedded flow with the tips disabled) and unfair to the Open Collective platform. More details at https://github.com/opencollective/opencollective/issues/6376.
We do acknowledge that if you link directly outside of the "Step details" in the contribution flow, contributors won't be offered the ability to customize the tip, and that can be perceived as a hidden fee. We've documented https://github.com/opencollective/opencollective/issues/6377 to discuss and find a solution that will be fair for everyone.

We do acknowledge that if you link directly outside of the "Step details" in the contribution flow, contributors won't be offered the ability to customize the tip, and that can be perceived as a hidden fee. We've documented https://github.com/opencollective/opencollective/issues/6377 to discuss and find a solution that will be fair for everyone.

Is #6377  specific to the embed or also evaluating solutions that customers/collective admins could control?


SSL / TLS?

I'm using this to serve some stuff which my app then displays in a WKWebView. Given that Apple really want us using https, is SSL / TLS on your radar? I see you recently added it in the sockets dependency, so I'm hopeful :)

I think adding SSL support would be easy considering that Socket.swift has it. Actually once I had thought adding it, then I decided I'll add it on demand. So since you are in need, I'll add it :) Unfortunately I am and will be really really busy these days. Probably I can do it at the next weekend. Thank you for your interest :)

Wow, thanks! Love how much cleaner your code is than a certain highly-starred similar project... :see_no_evil:

Thank you for your appreciation :)

This is awesome! Can't wait to try it out :)

Hey! I thought I had left a comment here after closing via https://github.com/BiAtoms/Http.swift/commit/1d1e26835cb10c46299022be5d9fb1eca33943e9 . Seems that I hadn't. Sorry for that. You can reach me at gitter if you want to discuss something about Http.swift

Will definitely drop in and say hi on Gitter!
I found it a bit tricky to get this to build. Since I use Carthage in my project, I'm building this separately using the workspace included with this project to build the two frameworks I need (Http.swift and Sockets.swift). But running pod install on a fresh checkout of this repo just kept installing v2.1.0 of Sockets.swift, not the newly-required v2.2.0.
In the end I got it working by modifying the Podfile like so:
  # Pods for HttpSwift
  pod 'Socket.swift', :git => 'https://github.com/BiAtoms/Socket.swift.git', :branch => 'master', :tag => '2.2.0'

I'm guessing my problems are almost certainly due to my lack of understanding Cocoapods, but I mention it here in case there's some tiny config error somewhere in the project or on Cocoapods.org or something.

The build is passing in travis ci, so I am sure about my side. Your pod repo might be out of date. Remove :git => ... stuff and try pod install --repo-update it should work. As regards the carthage, it's in my queue ;)

You're right — thanks a lot! The --repo-update was key... it builds just fine now.


Update Jaeger version to 1.14

Please provide a description for what this PR is for.
This PR updates the Jaeger version to 1.14 and changes the prometheus metrics and readiness probe port to use the admin endpoint.
And to help us figure out who should review this PR, please
put an X in all the areas that this PR affects.
[ ] Configuration Infrastructure
[ ] Docs
[x] Installation
[ ] Networking
[ ] Performance and Scalability
[x] Policies and Telemetry
[ ] Security
[ ] Test and Release
[ ] User Experience
[ ] Developer Infrastructure

cc @clyang82

@objectiser: The following test failed, say /retest to rerun them all:

Test name
Commit
Details
Rerun command

lint_istio
6af3bd51729230daaca84200732d1a69e8a76a97
link
/test lint_istio

Instructions for interacting with me using PR comments are available here.  If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository. I understand the commands that are listed here.

/test lint_istio

Regarding the lint error, we do this confusing thing where we rebase your
PR with latest changes in HEAD and then run the tests. So if its failing
here but passes locally you may need to rebase
On Tue, Oct 1, 2019 at 10:14 AM Gary Brown<EMAIL_ADDRESS>wrote:

/test lint_istio
—
You are receiving this because your review was requested.
Reply to this email directly, view it on GitHub
https://github.com/istio/istio/pull/17522?email_source=notifications&email_token=AAEYGXO7MZU7U74PSLSRTATQMOAQNA5CNFSM4I4HXPO2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEACAXKA#issuecomment-537136040,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AAEYGXMBCJH7M5SRAXMQOVTQMOAQNANCNFSM4I4HXPOQ
.

@howardjohn @objectiser
When the changes would be released?
I see the old helm chart in 1.3.2 release
https://storage.googleapis.com/istio-release/releases/1.3.2/charts/istio-1.3.2.tgz

This will be in 1.4.0 shipping next month https://github.com/istio/istio/wiki/Istio-Release-1.4

@howardjohn is there any chance to release it as quick-fix to 1.3.x?

@howardjohn
Agree with @goruha . All 1.3.x releases are broken. Can we have a patch in 1.3.x please?

/cherrypick release-1.3

@howardjohn: #17522 failed to apply on top of branch "release-1.3":
error: Failed to merge in the changes.
Using index info to reconstruct a base tree...
M	install/kubernetes/helm/istio/charts/tracing/templates/deployment-jaeger.yaml
M	install/kubernetes/helm/istio/charts/tracing/values.yaml
Falling back to patching base and 3-way merge...
Auto-merging install/kubernetes/helm/istio/charts/tracing/values.yaml
CONFLICT (content): Merge conflict in install/kubernetes/helm/istio/charts/tracing/values.yaml
Auto-merging install/kubernetes/helm/istio/charts/tracing/templates/deployment-jaeger.yaml
Patch failed at 0001 Update Jaeger version to 1.14

In response to this:

/cherrypick release-1.3

Instructions for interacting with me using PR comments are available here.  If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository.

Already done on 1.3: https://github.com/istio/istio/pull/18274


Set AssigneReviewers correctly on new submissions. Show review button.

Should add some test to make sure this does not happen again.
Sent with GitHawk

Discussed in Slack.


Highlight current transaction or transactions being signed

Currently when the user queues up many transactions (like when adding liquidity)  they are prompted to sign many transactions in a row without knowing what each transaction is for.  It would be nice to show the particular order  they are currently signing, or group of orders when bulk transaction signing as possible.

Closing for now, gotta prioritize stuff and this is low IMO


Proposal: Max Parallel execution at workflow level and template level

Summary:
If there are a lot of steps in parallel to be run, either because there are lots of parallel steps or you are doing dynamic withItems which allows a generated number of steps to be run in parallel, we may want to limit max parallel executing Pods in a given workflow. This will allow other workflows to not starve (assuming there are resource limitation set at cluster level, if resource limitatio are not set it will allow the cluster to not starve other things) which have more sequential steps.
Proposal:

Introduce spec.maxParallelExecution to limit parallelization of a given workflow.

Also have a spec.templates.steps.step.withItems.maxParallelExecution to limit parallelization when doing generated or explicit parallel steps within a loop.

Intended Behavior:

When spec.maxParallelExecution is set then we will run at most that many pods in parallel during the whole workflow.
When spec.templates.steps.step.withItems.maxParallelExecution is set then the parallel fan-out steps in that step will run at most that many pods in parallel while still obeying spec.maxParallelExecution limitation if it is also set

/cc @javierbq

Implemented parallelism controls at both workflow and template level in commit 0517096c32cd4f2443ae4208012c6110fbd07ab6. Examples:
examples/parallelism-limit.yaml
examples/parallelism-template-limit.yaml

Hi, does the feature exist ? I couldn't see anything in the documentation to limit the number of pods running concurrently in a loop withParam.
Thanks

I don't think you can do exactly what you described.
However, take a look at using semaphores in the workflow, which seems to be the closest thing from your request.


Release TDS archive

I want to add package to ConTeXt LMTX docker image without having to compile the source files.

You can find the release tarballs on CTAN:

lt3luabridge.doc.tar.xz
lt3luabridge.source.tar.xz
lt3luabridge.tar.xz

Namely, the "TDS archive" is obtained by unpacking files lt3luabridge.doc.tar.xz and lt3luabridge.tar.xz.
Is this sufficient for you?


Reset stores not working globally

Reset stores not working since last update using this code in the main.ts:
import { akitaConfig } from "@datorama/akita";

akitaConfig({
  resettable: true
});

When I call resetStores() I get message:

You need to enable the reset functionality

@danzrou

Pushing a PR soon, noticed it this morning.


API consistency improvements

This way it would be the same as schemathesis.{hooks,serializers,auth}.register.
Maybe the next step could look like this:
import schemathesis

@schemathesis.check
def my_check(response, case):
    pass

@schemathesis.target
def big_response_size(context):
    pass

@schemathesis.hook
def before_call(context, case):
    pass

@schemathesis.serializer
class MessagePackSerializer:
    ...

@schemathesis.auth
class TokenAuth:
    ...

@schemathesis.openapi.format
def visa_cards():
    return st.from_regex(r"\A4[0-9]{15}\Z").filter(luhn_validator)

schemathesis.openapi.format("visa_cards", st.from_regex(r"\A4[0-9]{15}\Z").filter(luhn_validator))

+ checks should receive context as well

Codecov Report

Merging #1656 (17c9290) into master (240b6fa) will decrease coverage by 0.07%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master    #1656      +/-   ##
==========================================
- Coverage   98.96%   98.88%   -0.08%
==========================================
  Files          95       95
  Lines        7645     7648       +3
  Branches     1580     1281     -299
==========================================
- Hits         7566     7563       -3
- Misses         48       52       +4
- Partials       31       33       +2

Impacted Files
Coverage Δ

src/schemathesis/cli/__init__.py
99.20% <ø> (-0.02%)
:arrow_down:

src/schemathesis/__init__.py
100.00% <100.00%> (ø)

src/schemathesis/checks.py
100.00% <100.00%> (ø)

src/schemathesis/targets.py
100.00% <100.00%> (ø)

src/schemathesis/specs/openapi/validation.py
76.47% <0.00%> (-11.77%)
:arrow_down:

src/schemathesis/cli/callbacks.py
98.84% <0.00%> (-1.16%)
:arrow_down:

src/schemathesis/utils.py
96.93% <0.00%> (-0.77%)
:arrow_down:

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


build: new icon set gulp process

Description

Added a script to convert from strokes to fills using https://docs.oslllo.com/svg-fixer/master/#/getting-started/introduction
The script flattens internal s into single

Pull Request Checklist

[x] Ask the contributors if a similar effort is already in process or has been solved.
[x] Review the contribution guidelines.
[x] Use staging as your pull request's base branch. (All PRs using production as its base branch will be declined).
[x] Ensure all gulp scripts successfully compile.
[ ] Update, remove, or extend all affected documentation.
[ ] Ensure no private Dialpad links or info are in the code or pull request description (Dialtone is a public repo!).

Obligatory GIF (super important!)

Lowered the resolution so the script takes only like 5 seconds, later will need to compare the icons until we find the right "resolution-performance" balance.


How to use scrcpy to see the device from STF

[x] I have checked that a similar feature request does not already exist.

Is your feature request related to a problem? Please describe.
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
Describe the solution you'd like
A clear and concise description of what you want to happen.
I have a stf server which have lots of android device. The android device is plugin to a machine and port adb server to the STF server. so all the device will have the same IP with different port.

adb connect <IP_ADDRESS>:7451
scrcpy -Vdebug

2020-10-27 20:33:27.219 scrcpy[12148:436467] DEBUG: Using server: /usr/local/Cellar/scrcpy/1.14_1/share/scrcpy/scrcpy-server
/usr/local/Cellar/scrcpy/1.14_1/share/scrcpy/scrcpy-server: 1 file pushed. 0.7 MB/s (33142 bytes in 0.045s)
[server] INFO: Device: samsung SM-G9650 (Android 9)
[server] DEBUG: Screen streaming stopped
[server] DEBUG: Controller stopped
Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
Additional context
Add any other context or screenshots about the feature request here.

Check the output of adb logcat to get more info.

1.txt

Add logcat file
1.txt

Does the same device work directly (without STF as a "proxy")?

Yes. if i plugin with usb or wireless. it works

OK so it's probably related to how STF "proxifies" connections. I don't know how it works.
Maybe try scrcpy --force-adb-forward.

Nice, works. Thanks.


vault: 1.16.1 -> 1.16.2

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://github.com/hashicorp/vault/releases.
meta.description for vault is: A tool for managing secrets
meta.homepage for vault is: https://www.vaultproject.io/
meta.changelog for vault is: https://github.com/hashicorp/vault/blob/v1.16.2/CHANGELOG.md
Updates performed

Golang update

To inspect upstream changes

Release on GitHub

Compare changes on GitHub

Impact
Checks done

built on NixOS
Warning: a test defined in passthru.tests did not pass
found 1.16.2 with grep in /nix/store/xqndai482ixj2mv14jw1lk16qkfk5pk4-vault-1.16.2
found 1.16.2 in filename of file in /nix/store/xqndai482ixj2mv14jw1lk16qkfk5pk4-vault-1.16.2

Rebuild report (if merged into master) (click to expand)

3 total rebuild path(s)

3 package rebuild(s)

First fifty rebuilds by attrpath

kubernetes-helmPlugins.helm-secrets
vault

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/xqndai482ixj2mv14jw1lk16qkfk5pk4-vault-1.16.2 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A vault https://github.com/r-ryantm/nixpkgs/archive/533d7e7968c0029bdc65e318d4e8bf648fb6f558.tar.gz

Or:
nix build github:r-ryantm/nixpkgs/533d7e7968c0029bdc65e318d4e8bf648fb6f558#vault

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/xqndai482ixj2mv14jw1lk16qkfk5pk4-vault-1.16.2
ls -la /nix/store/xqndai482ixj2mv14jw1lk16qkfk5pk4-vault-1.16.2/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
Result of nixpkgs-review --extra-nixpkgs-config '{ allowInsecurePredicate = x: true; }' run on x86_64-linux 1

2 packages built:

kubernetes-helmPlugins.helm-secrets
vault

Maintainer pings
cc @rushmorem @LnL7 @offlinehacker @pradeepchhetri @Chili-Man @techknowlogick for testing.

@ofborg eval


feat: Flutter v3 compatibility - Remove operand of null-aware operation

Hello @FilledStacks,
I fixed all errors when launching the project after migrations to Flutter v3.
Let me know if this helps and how to improve if needed.
Have a nice day!
Gerfaut

Maybe this should not be fixed as is, but with support for 3.0 and earlier version, using the _ambiguate solution provided by the Flutter team: https://docs.flutter.dev/development/tools/sdk/release-notes/release-notes-3.0.0#your-code.
What do you think?

@Gerfaut thanks! I'm checking out the fix and your code now.

@Gerfaut I like the ambiguate solution. Please use that one and add the link to those docs in a comment. This way we'll know to remove it once everything is moved over to Flutter 3.

Hey @FilledStacks,
Thanks for feedback! I just pushed the changes and I hope it fit your expectations 🙏
Let me know if it isn't the case!
Have a nice day 🌞
Gerfaut

It's gonna be published today

@FilledStacks This warning still appears in version 0.3.8+1 of the stacked_themes package. Is there anyway you can update that package?


Update voice activity detection

update: this is the PR that is connected with natalieyhw:master, whereas #1 is connected with natalieyhw:patch-2, so I am going to merge this one since it incorporates my own changes (8a46008)


feat(theme)!: remove theme auto-load

Replace theme auto-load with --theme option and .meta.theme resume field.
Although a nice feature, theme auto-load added a lot of complexity to the project (~30% of the code). Removing it also removes half the dependencies, and facilitates a future migration to ESM.

Codecov Report
Base: 100.00% // Head: 100.00% // No change to project coverage :thumbsup:

Coverage data is based on head (a27fe04) compared to base (ec96392).
Patch coverage: 100.00% of modified lines in pull request are covered.

Additional details and impacted files
@@            Coverage Diff            @@
##            master        #4   +/-   ##
=========================================
  Coverage   100.00%   100.00%
=========================================
  Files            6         5    -1
  Lines           75        55   -20
  Branches        10         6    -4
=========================================
- Hits            75        55   -20

Impacted Files
Coverage Δ

src/index.ts
100.00% <ø> (ø)

src/cli.ts
100.00% <100.00%> (ø)

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testrun script divides by zero

Original issue: https://charm.cs.illinois.edu/redmine/issues/1022

../../../bin/testrun  ./hello +p8 +restart log  ++local
expr: division by zero

https://charm.cs.illinois.edu/autobuild/cur/netlrts-darwin-x86_64.txt
Tests don't seem to be failing because of this, but it's certainly ugly.

Original date: 2016-03-31 20:30:32

~~https://charm.cs.illinois.edu/gerrit/#/c/1123/~~ https://github.com/UIUC-PPL/charm/commit/d7528dd6d5cd1179550fb69fe9c144572e224acf


Type equality inconsistency for generic functions.

When we generate a Type object for a generic function, dart2js normalizes dynamic bounds to be the same as Object bounds, and the VM doesn't even consider structurally equal types to be equal Type objects.
Example:
Type type<T>() => T;
main() {
  var t0 = type<void Function<X extends Object>(X) Function()>();
  var t1 = type<void Function<X extends Object>(X) Function()>();
  var t2 = type<void Function<X extends dynamic>(X) Function()>();
  var t3 = (<D>() => type<void Function<X extends D>(X) Function()>())<dynamic>();
  print(t0 == t1);  // false in VM, true in dart2js, even though it is *exactly* the same type.
  print(t1 == t2);  // false in VM, true in dart2js
  print(t2 == t3);  // false in VM, true in dart2js
  print(t1 == t3);  // false in VM, true in dart2js
  print(t1); // () => <T1>(T1) => void
  print(t2); // () => <T1>(T1) => void
  print(t3); // () => <T1 extends dynamic>(T1) => void in VM, () => <T1>(T1) => void in dart2js.
}

The VM is definitely wrong about equality of the structurally same type.
As to considering dynamic and Object as the same bound, I guess that's reasonable, even though a little inconsistent (a bound of void is not equal).

Note the overlap with #32782 / #32783, which is associated with the test language_2/type_alias_equality. That test uses type aliases as well, but the bug is actually in the treatment of the underlying type, which includes generic function types and also has a case with differently named type variables.

@lrhn is this a language bug to clarify the spec?

The spec was updated in https://github.com/dart-lang/sdk/issues/34447 to say that Type.== must evaluate to true iff the arguments are subtypes of each other. So the spec already requires the equalities t0 == t1, t2 == t3.
For the bounds of type parameters of generic function types, the spec relies on renaming (generic function types are explicitly considered to be the same type if they only differ by choice of names), and this is not sufficient to establish a subtype relationship like Function<X extends Object>() <: Function<X extends dynamic>(). We might consider that to be an unintended distinction (it seems inconsistent to me), and we could then change the subtype rules to say that also bounds must just be mutual subtypes.

Even if we change the specifiction to be "Type objects are == equal if they are the the same type" (which might be a good idea since that's almost what everybody implmenets), then "the same type" for structural types like function types still means that void Function<T>(T) Function() is the same type every time you write it. There is only one function type with that structure.
So, this is a VM bug.
Hardly a high priority one, though.

PS: Unless we change the subtype rules, it is also a dart2js bug.


[refactor] - aggregated middleware.

"You can also load a series of middleware functions together, which creates a sub-stack of the middleware system at a mount point." - ExpressJS documentation ( http://expressjs.com/en/guide/using-middleware.html ).

Thank you for the PR @TyreseW, but I am going have to politely decline as I don't see much improvement with these changes in my opinion.


Missing operationId doesn't provide context as to where it's missing from

Currently, leaving out an operationId logs [ERROR] Error: Missing operationId before halting codegen.
Without any context (JSON Path, parameters, even just logging the surrounding block) these kinds of issues can be hard to fix.
Lowest hanging fruit is to simply log the Operation along with the error.

+1 -- This was super annoying to try and figure out!


Fix Fanart resolution and icon.png (again)

Check if this PR fulfills these requirements:

[X] My changes respect the Kodi add-on development rules
[X] I have read the CONTRIBUTING document.
[X] I made sure there wasn't another one Pull Requests opened for the same update/change
[X] I have successfully tested my changes locally

Types of changes

[ ] New feature (non-breaking change which adds functionality)
[ ] Feature change (non-breaking change which change behaviour of an existing functionality)
[X] Improvement (non-breaking change which improve functionality)
[ ] Bug fix (non-breaking change which fixes an issue)
[ ] Breaking change (fix or feature that would cause existing functionality to change)

Description
Finally fix Fanart and Icon regarding kodi-addon-checker results.

Sorry about the previous wrong commit. Now pass tests.


Toast build for orsay not working

I create an application for smart tvs with TOAST project. During the development I test everything with tizen emulator and tizen studio and everything was fine.
After finishing development I tried to run the application on both orsay TV and orsay emulator and unfortunatly there was a lots of issue in that platform. I fixed some issues in design but I can't fix the main issue.
When I run the application, There is a line in console that say : deviceready has not fired after 5 seconds. And I can't use any of the TOAST api functionalities.
I create an empty project and do exactly what this page say: https://github.com/Samsung/cordova-plugin-toast#prepare-to-start
But again I got the same error. Please help me.
Here is the log:

cordova/platform: orsay bootstrap BEGIN            cordova.js:1365
adding proxy for NetworkStatus            cordova.js:887
adding proxy for Console            cordova.js:887
adding proxy for Device            cordova.js:887
adding proxy for Globalization            cordova.js:887
cordova/platform: orsay bootstrap END            cordova.js:1460
adding proxy for toast.inputdevice            cordova.js:1880
return Window             cordova.js:1880
adding proxy for toast.tvwindow            cordova.js:1880
return Window             cordova.js:1880
adding proxy for toast.tvchannel            cordova.js:1880
adding proxy for toast.tvaudiocontrol            cordova.js:1880
adding proxy for toast.drminfo            cordova.js:1880
adding proxy for toast.application            cordova.js:1880
adding proxy for toast.Media            cordova.js:1880
Failed to load resource: fail to read a resource form decryptied file            file:///home/smarttv/Apps/xThreeApp/cordova_plugins.js
deviceready has not fired after 5 seconds.            cordova.js:1880
Channel not fired: onNativeReady            cordova.js:1880
Channel not fired: onCordovaReady            cordova.js:1880
Channel not fired: onCordovaConnectionReady            cordova.js:1880
Channel not fired: onCordovaInfoReady            cordova.js:1880

Ok I just find out two things:

when I run the application on the emulator with Debug As/Samsung Smart Tv Emulator the devicereaday won't fired but if I close the app in the emulator and and open it again from the app page in emulator, the deviceready event will work perfect

Even with the above trick, when I navigate to the second page, deviceready again won't fire! (Even I tried to navigate to the current page but second attamp will fail to fire the deviceready event)

I tried lots of method to navigating to the second page but all have the same result. (I use methods like window.location.href = url; and window.location.replace(url); and ...)

There was a problem in cordova.js and you find the answer here :
https://github.com/Samsung/cordova-plugin-toast/issues/53


Have you considered to make a PR to Xamarin.Forms project?

A while ago I just tried your library and it's working really great, and I think I am gonna use it to my own project, have you considered to make a PR to Xamarin.Forms project?
BTW, thank you for making this library 😄

Sorry, what is PR?

PR = Pull Requests

Ah, am think Xamarin will not approve this :)