text:
Base run generating multiple snapshot images

When I do a base run to generate snapshots, each test is generating 2 snapshots:

base.png
base-big number.png

This creates a lot of churn in our repo because now instead of just having base.png be updated, we have a delete/create of the numbered image:

The number changes every time I run the command to generate base images. I am using the following command to do this:
./node_modules/.bin/cypress run --env type=base --config screenshotsFolder=cypress/snapshots/base,integrationFolder=src,testFiles=\"**/*visual.test.ts\"
Is there a way to run the "base" command and only generate the base.png file for each test?
Thanks!

I think this is the same problem as in #76 . However the PR #35 did not  change it. Up until now @eric-burel's solution in https://github.com/mjhea0/cypress-visual-regression/issues/76#issuecomment-849726637 seems to the only thing that works. It seem that only @mjhea0 can answer what these files with the big number are used for.

Thanks, that definintely looks like the same issue I am seeing. Because that issue is closed (and the solution didn't really solve it), I will leave this issue open. Or should the other one be reopened where it has more history to it?

I would leave yours open. Just meant to link the other issue as reference that this still exists and hasn't been resolved

at the moment I've fixed it (for now) this way for myself:
npm install del-cli
and added these commands in my package.json file
"scripts":
        "base": "npm run create:base && npm run clean:base",
        "create:base": "cypress run --env type=base --config screenshotsFolder=cypress/snapshots/base",
        "clean:base": "del ./cypress/snapshots/base/**/*-base-[0-9]*.png",
        "clean:base:dryrun": "del ./cypress/snapshots/base/**/*-base-[0-9]*.png --dry-run"

which in turn gives me the following situation: I run the npm run base command which generates new base images (including the ones with the timestamp in it) and when that command finishes it will remove all base images which have the timestamp in it

Without  any additional package:
"scripts": {
        "base": "./node_modules/.bin/cypress run --env type=base --config screenshotsFolder=cypress/snapshots/base",
        "postbase": "cd cypress/snapshots/base && rm -rf */*-base-*.png"
}

Should no longer be a problem


text:
mj-include inside mj-include

mjml does not parse another include in an included file.
Is this planned to be supported?
index.mjml
<mj-include path="1.mjml" />

1.mjml
<mj-include path="2.mjml" />

2.mjml
<mj-text>This is a header</mj-text>

This is already supported, how do you compile it ?

On 10 Nov 2019, at 01:05, David Vielhuber notifications@github.com wrote:

does not allow do have another include in the included file.
Is this planned to be supported?
index.mjml

1.mjml

2.mjml
This is a header
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub, or unsubscribe.

Sorry, my fault.
I added mj-include inside a mj-text, which is dump.
Works very well!

source: gharchive/issue

authors: iRyusa vielhuber

repo: mjmlio/mjml

license: MIT

license_type: permissive

license_source: github-api


text:
Error when creating BLEU object with flores200 tokenizer: HTTP 403 Forbidden

Description:
I encountered an HTTP 403 error when attempting to create a BLEU object using the flores200 tokenizer in SacreBLEU.
Steps to Reproduce:

Create a BLEU object with tokenize="flores200".
Run the script.

Error Message:
File "/Users/williamtan/Projects/indonesiaku-benchmarking/benchmark.py", line 33, in __init__
    "bleu": BLEU(tokenize="flores200"),
            ^^^^^^^^^^^^^^^^^^^^^^^^^^
  ...
  File "/Users/williamtan/miniconda3/envs/ai_scientist/lib/python3.11/site-packages/sacrebleu/utils.py", line 430, in download_file
    with urllib.request.urlopen(source_path) as f, open(dest_path, 'wb') as out:
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
urllib.error.HTTPError: HTTP Error 403: Forbidden

Cause:
The error occurs because the flores200 tokenizer URL uses a tinyurl link, which is not accessible via urllib.request.urlopen due to HTTP 403 restrictions.
Proposed Solution:
To resolve this issue, update the flores200 URL in /tokenizers/tokenizer_spm.py:
"flores200": {
    "url": "https://dl.fbaipublicfiles.com/large_objects/nllb/models/spm_200/flores200_sacrebleu_tokenizer_spm.model",
    "signature": "flores200",
}

Thank you for your help!

I checked it now (sacrebleu -tok flores200 example.ref < example.trans) and everything works fine for me: SacreBLEU downloads the spm model automatically via the tinyurl link. In stderr logs, I see
sacreBLEU: Downloading https://tinyurl.com/flores200sacrebleuspm to /home/martin/.sacrebleu/models/flores200sacrebleuspm

I even tried
import urllib.request
with urllib.request.urlopen("https://tinyurl.com/flores200sacrebleuspm") as f, open("flores200sacrebleuspm", 'wb') as out:
    out.write(f.read())

and it works fine.
I confirm it works (and downloads the same file) even if I substitute https://tinyurl.com/flores200sacrebleuspm with https://dl.fbaipublicfiles.com/large_objects/nllb/models/spm_200/flores200_sacrebleu_tokenizer_spm.model.
The question is which URL is more stable. The official Flores200 README uses https://tinyurl.com/flores200sacrebleuspm, so I guess that is meant as the permanent link, while its target may change (and the fbaipublicfiles.com link may not work in future).
I am thus a bit reluctant to change the URL in tokenizers/tokenizer_spm.py. That said, if either

there are more users who cannot use the tinyurl link or
if you provide some evidence that the fbaipublicfiles.com link can be considered permanent

then please make a PR and I will accept it.
(In the case "1", we will have to update the url each time the tinyurl alias changes its target).

@williammtan Can you try downloading https://tinyurl.com/flores200sacrebleuspm once again (both with urllib.request.urlopen and another method e.g. wget/curl)?
Can you try that with another tinyurl link?
Maybe you are behind a firewall which blocks the whole tinyurl.com.
Yet another alternative would be to catch the exception when the download fails and try to use e.g. https://unshorten.it/ to get the target URL and try to download that instead, but I don't like such solution much as it adds code not related to sacrebleu.

authors: martinpopel williammtan

repo: mjpost/sacrebleu


text:
stats.govt.nz

Hi,
This is the Government of New Zealand Statistics site
I believe this is a false positive

Thanks again, yeah definitely a false positive as it's blocked by a regex that blocks domains starting with stats or statistics which mostly blocks domains it should block, but occasionally blocks domains like that


text:
Support for sql stored procedure table typed parameters

Hello
I have a small request as I did not find anything similar in documentation (or did I overlook sth?).
Env

Python: 3.6 x64
pyodbc: 4.0.23
OS: Windows 10
DB: Sql Server 2016 - Compatibility lvl 130
driver: ODBC Driver 13 for SQL Server

Observed behavior:
One to insert many rows to DB's table must use executemany with fast_executemany option and this is quite error prone as does some data converting and includes many round trips to SQL.
Expected behavior:
I would like to use Sql table types as stored procedure parameters in which case whole data set could be potentially passed from Pyton to Sql with one round trip.
Example:
Pyton:
dbAdapter = pyodbc.connect(connectionString).cursor()
dbAdapter.execute("EXEC [dbo].[StoredProcedureName] ?", listOfData)

Sql:
CREATE TYPE [dbo].[StoredProcedureNameParameterType] AS TABLE (
	[C_SomeColumn] [int] NOT NULL,
	[C_SomeColumn2] [nvarchar](max) NOT NULL
);
GO

CREATE PROCEDURE [dbo].[StoredProcedureName]
	@TBL_OfInsertedData [dbo].[StoredProcedureNameParameterType]  READONLY
AS
BEGIN
	BEGIN TRANSACTION
		INSERT INTO [dbo].[TBL_ExistingSqlTaqble] ([C_SomeColumn], [C_SomeColumn2])
		SELECT TBL_OfInsertedData.[C_SomeColumn], TBL_OfInsertedData.[C_SomeColumn2]
		FROM @TBL_OfInsertedData AS TBL_OfInsertedData
	COMMIT TRANSACTION
END
GO

Note:
This can already be done in C# and other languages, so I think there should be an option to code this (Or is it already possible)? This potentially can close all issues regarding executemany with Sql Server. Can similar techniques be used on other DBs engines?

Since this is a duplicate, I'll close this one and #290 should be followed for updates.  Thanks.

authors: WisniowskiPiotr mkleehammer

repo: mkleehammer/pyodbc


text:
feat: support laser pointer

Description
Presentation programs often provide a laser pointer feature, where the operating system cursor disappears and a simulation of laser light is displayed on the slide instead.
This issue tracks the request to add laser pointer support in flutter_deck offering me to work on this issue.
Additional Context
Laser pointer in Microsoft PowerPoint:

Laser pointer in Google Slides:

For my personal use I quickly implemented something functional, it looks like this:
https://github.com/mkobuolys/flutter_deck/assets/9968005/d6ff3cf8-8d55-4db8-93ab-f4cab36b294b

Hey, I have a similar idea on my to-do list - supporting marker. Meaning, you could even draw on top of your slide (pretty neat in some cases). I think the laser pointer could be just another option for that. It's not a priority, but let's keep the issue open so I will remember to cover this as well.

Hey, I have a similar idea on my to-do list - supporting marker. Meaning, you could even draw on top of your slide (pretty neat in some cases). I think the laser pointer could be just another option for that. It's not a priority, but let's keep the issue open so I will remember to cover this as well.

Drawing on the slides is another very good functionality 🤞🏻. If this topic is not yet a priority; Is there a topic I can work on? I am very interested in contributing to this project.

Hey, I have a similar idea on my to-do list - supporting marker. Meaning, you could even draw on top of your slide (pretty neat in some cases). I think the laser pointer could be just another option for that. It's not a priority, but let's keep the issue open so I will remember to cover this as well.

Drawing on the slides is another very good functionality 🤞🏻. If this topic is not yet a priority; Is there a topic I can work on? I am very interested in contributing to this project.

If you have already implemented this, you can create a PR for the laser pointer and we can discuss the details there.

@leonus96 FYI, I have implemented the marker tool recently, you can check it for reference (if you are planning to add a laser pointer): https://github.com/mkobuolys/flutter_deck/pull/36


text:
Show Reply Form at Bottom is Mis-Aligned

The replies are rendered in the submit button's form-group element, rather than a separate container.

Thanks so much Mike. Really appreciate you took care of this :-)

license: mit

license_source: bigquery


text:
"Your computer was restarted because of a problem" after QLoRa on Mistral Nemo fused and (later) quantized checkpoint

My computer keeps getting consistently restarted by a LoRa run against 4-bit float32 quants (via current mlx_lm.convert) of older checkpoints (fused about august, prior to the #1062 PR) that are themselves LoRa fine-tunes of Mistral Nemo.  I'm getting the same problem with freshly quantized Mistral Nemo models (no adapters) of the same datasets on an Apple M1 Max 32GB on macOS Sequoia 15.1
mlx % git rev-parse HEAD
9bd3a7102fc1dccb10e2a93c320e77f4d32c01de

mlx-examples % git rev-parse HEAD
0f799947d0c73ff4901ce17188aceaa933b3c02e

model: "/path/to/Mistral-Nemo/fused-lora-checkpoint/4-bit-float32-quantized"
train: true

data: "[..]"

num_layers: 20
batch_size: 4

learning_rate: 6e-6

adapter_path: "[..]"

seed: 42

eos_token: "[/INST]"

lr_schedule:
  name: "cosine_decay"
  warmup: 5600
  warmup_init: 1e-8
  arguments: [6e-6, 100000, 1e-7]

lora_parameters:
  keys: ["self_attn.q_proj", "self_attn.v_proj", "self_attn.k_proj", "self_attn.o_proj"]
  rank: 32
  dropout: 0.3205
  scale: 20.0

The process gets beyond the first evaluation, with the following validation loss and time:
Iter 1: Val loss 2.366, Val took 8634.032s

Then, at some point much later, the machine restarts with the following error in the GUI:
Your computer was restarted because of a problem
This is the first part of the problem report for macOS:
panic(cpu 0 caller 0xfffffe0022646190): watchdog timeout: no checkins from watchdogd in 92 seconds (3893 total checkins since monitoring last enabled)
Debugger message: panic
Memory ID: 0x1
OS release type: User
OS version: 24B83
Kernel version: Darwin Kernel Version 24.1.0: Thu Oct 10 21:03:15 PDT 2024; root:xnu-11215.41.3~2/RELEASE_ARM64_T6000
Fileset Kernelcache UUID: A22C571B61C24E448B9EFFEEFF5F8CC7
Kernel UUID: 8FF94A3F-7153-35AD-8150-EC096C2596DE
Boot session UUID: 338E844A-A05C-4DB2-9298-502C4744352E
iBoot version: iBoot-11881.41.5
secure boot?: YES
roots installed: 0
Paniclog version: 14
KernelCache slide: 0x0000000019470000
KernelCache base:  0xfffffe0020474000
Kernel slide:      0x0000000019478000
Kernel text base:  0xfffffe002047c000
Kernel text exec slide: 0x000000001ab84000
Kernel text exec base:  0xfffffe0021b88000
mach_absolute_time: 0xda080a41a7

[..snip..]

The earlier checkpoint had the following relevant configuration parameters after quantitation:
    "quantization": {
        "group_size": 64,
        "bits": 4
    },
    "quantization_config": {
        "group_size": 64,
        "bits": 4
    },

It was the result of a larger LoRa run that I wanted to amend with a relatively smaller dataset. The smaller dataset I was using for amendment has 275K records totaling 44M tokens, 434.157 tokens per step, and an average of 162 tokens per record. Two of the records had more than 2048 and were subject to truncation. There was also a validation set of 32K records.
The command-line attempt from above to QLora train the checkpoint on the smaller dataset was:
% mlx_lm.lora --val-batches 2711 \
              --steps-per-report 1032 \
              --steps-per-eval 17210 \
              --save-every 34421 \
              --iters 103264 -c path/to/config.yaml

The full dataset has 945K records, comprising the smaller public datasets and a larger (private) dataset, for a total of 85.6M tokens, at 242 per step, an average of 91 tokens per record, and a validation set of 75K records.
I tried a QLora run using the larger dataset against a newly downloaded quantized Nemo model (no adapters) but still get that hard restart after the initial evaluation and subsequent training/model evaluation:
% mlx_lm.lora --val-batches 6239 \
            --steps-per-report 3543 \
            --steps-per-eval 59051 \
            --save-every 118103 \
            --iters 354309 -c /path/to/config.yaml

In all cases, I have wired my system to 18GB, per the recent mlx_lm generating documentation regarding large models and wiring the memory occupied by the model and cache, since I only had 32GB and Nemo may be large relative to the total RAM available on the machine for mlx (if not for inference, then perhaps for training).
sudo sysctl iogpu.wired_limit_mb=18000

I tried running a LoRa run (no quantization) using the smaller dataset against the older, fused checkpoint and got a few hours before a hard crash

Does it crash if you don't set the syctl limit?

Does it crash if you don't set the syctl limit?

From what I can recall, from when I initially started trying to narrow this down, yes.  But, once this run completes (or fails) or try again w/out the limit

Thanks! So just to be sure:

The QLoRA run crashes but only with the larger dataset?
The regular LoRA (no quantization) runs to completion on the smaller dataset?
What about QLoRA on the smaller dataset and LoRA on the larger? Did you try that?

The QLoRA run crashes on both the larger and smaller datasets.  The regular LoRA was still running earlier today, many hours after the point at which the QLoRA runs were crashing.  So, I'm not sure it will run to completion, but it looks very much like it will so far.
I was planning to try LoRA on the larger one if the smaller one runs to completion to see if it gets beyond the first validation/eval and at least two reportings of loss.  But so far, quantization seems to be the main factor behind when it consistently crashes.

wiring the memory occupied by the model and cache

What do you mean by that?

wiring the memory occupied by the model and cache

What do you mean by that?

I saw the new section on large models and what says about 'wiring' them if "are large relative to the total RAM available on the machine" and wasn't sure, given the size of the model I'm working (12.2B) and the memory I have available on my M1 Max (32GB), if the suggestion was relevant to this situation or if it was only appropriate for memory management during generation.

I'm using sysctl and not mx.metal.set_wired_limit .  I started the smaller QLoRA run without this setting, and it (like the large LoRA attempt) also made it beyond the point where the earlier attempts were crashing.

authors: awni chimezie

repo: ml-explore/mlx-examples


text:
Usage of convert and fuse ?

In the first step, if I didn't use python convert.py -q to generate a quantized model, is that mean it is unnecessay to use -d, --de-quantize parameter to generate a de-quantized model when running the command python fuse.py ?

If you are not using the quant model to do the fine-tuning, you shouldn't de-quantize it during fuse. And if you try to de-quantize a non-quant model, fuse may throw an error.


text:
Not able to convert quantized Mistral 7B to GGUF

Describe the bug
I fine-tuned Mistral 7B, quantized, using Lora. I then tried using llama.cpp to convert the lora_fused_model to gguf format, but receive an error. Seems like the only way to achieve this conversion is to first dequantize, then convert to GGUF in llama.cpp, and then re-quantize. Unfortunately, dequantizing and requantizing seems to lobotomize the model.
To Reproduce

Download quantized base model: python3 convert.py --hf-path mistralai/Mistral-7B-Instruct-v0.2 -q --q-bits 8

Fine tune: python3 lora.py --model ./mlx_model --train --iters 700 --batch-size 1 --lora-layers 8

Fuse Lora layers to the model: python3 fuse.py --model mlx_model \ --adapter-file ./adapters.npz

Switch to Llama.cpp and run: python3 convert.py ./lora_fused_model

You will see the following error message:
 874, in convert     data_type = SAFETENSORS_DATA_TYPES[info['dtype']]                 ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^ KeyError: 'U32'
Expected behavior
Ideally, I would be able to convert the quantized fused model into GGUF format WITHOUT first de-quantizing.
Desktop (please complete the following information):

OS Version: macOS Sonoma
Version 14.4 (23E214)

Additional context
I can't fine tune Mistral 7B on my machine (M2 MacBook Air, 16GB) without quantization, so not being able to convert this to GGUF is a big blocker. Is there any suggested workaround? Is there a framework to run fast inference on the .safetensors thats not specific to apple silicon?

Just curious, why do you want to convert to GGUF?

@awni I use a llama.cpp server for inference, and im under the impressing that I need to use gguf format for that. (please correct me if Im wrong!).
Is there another framework you'd recommend that can run the .safetensors directly?

Do you serve on Mac or on a different machine?
For Apple silicon, yes.. MLX LM can in fact do some of that directly, see the docs on serving
For non-Apple silicon machines, not really, GGUF is a good bet.

Ah yea thats the problem, I will be deploying this to a non apple silicon machine

Makes sense.. good to know, thanks!

dequantizing and requantizing seems to lobotomize the model.

I assume you mean it makes the performance bad? That's one thing we should look into.. it shouldn't be that bad.
As for supporting saving directly to quantized GGUF.. it's a possibility. We haven't decided yet if we will support that in core but it's good to know of your use case!

#I assume you mean it makes the performance bad? That's one thing we should look into.. it shouldn't be that bad.
Correct, as if a lot of my fine tuning got erased in the process.
Is dequantizing mainly just padding on zeros at the end of the weights? And if so, then shouldn't dequantizing back to the original size result in no change in performance (in theory)? Or is some performance degradation inevitable during this process?

@awni Hey I don't think there's an issue with de-quantizing. I noticed that the model starts acting goofy after fusing. I didn't realize this before as I wouldn't test the model until after converting to GGUF. See my comment: https://github.com/ml-explore/mlx-examples/issues/507#issuecomment-2017123532

Right right yea that agrees with my own experience. Fusing the adapters can cause issues if the adapter values are very small compared to the base weights. You can play around with the scale parameter (increase it) to see if that helps get bigger adapters that don't get erased during fusion.

Where is the scale parameter?
Also I notice that server.py doesn't seem to use the adapter file even when passing it in as a parameter. Maybe it's fusing before running?

Where is the scale parameter?

This one

Also I notice that server.py doesn't seem to use the adapter file even when passing it in as a parameter. Maybe it's fusing before running?

Looks to me like it's being used, what make you say that?

Gotcha thanks!
Because running the model and adapter using lora.py results in intended model behavior. But passing in the model and adapter to server.py results in my fine-tuning disappearing from the model.

But passing in the model and adapter to server.py results in my fine-tuning disappearing from the model.

That's very odd 🤔 . The server.py is using the same load and generate_step function so it should be doing more or less the exact same thing. One thing to check would be to make sure you are setting the same arguments (temperature, prompt, etc). It's certainly possible there is a bug somewhere.. they should behave the same way assuming you are giving them the same inputs.

Closing this as a dup of #814. Regarding possible issues with server.py feel free to post here or make a new issue in mlx-examples!

repo: ml-explore/mlx


text:
Better documentation for install django-responsive

Include a little bit of documentation about how install and run django responsive

This should have previously been closed.

source: gharchive/pull-request

authors: luisza mlavin

repo: mlavin/django-responsive


text:
Smudge error when downloading pre-built model binaries

🐛 Bug
Command I run : git clone https://github.com/mlc-ai/binary-mlc-llm-libs.git dist/prebuilt_libs
Here's the error:

Receiving objects: 100% (689/689), 184.05 MiB | 25.71 MiB/s, done.
Resolving deltas: 100% (495/495), done.
Updating files: 100% (197/197), done.
Downloading mlc-chat.apk (124 MB)
Error downloading object: mlc-chat.apk (b7b937c): Smudge error: Error downloading mlc-chat.apk (b7b937c7be3b7e5f8164f0f1ef58c9e1df15fd0f08721fbf7fe16d058ef09c6e): batch response: This repository is over its data quota. Account responsible for LFS bandwidth should purchase more data packs to restore access.

To Reproduce
Steps to reproduce the behavior:
conda create --name mlc-llm python=3.10
conda activate mlc-llm
conda install git git-lfs
git lfs install
git clone https://github.com/mlc-ai/binary-mlc-llm-libs.git dist/prebuilt_libs
Note
I thought it might just be git-lfs error put upon googling I realized it might be that there are limits in terms of the data-storage on GitHub and it needs to be upgraded. Thus sharing it here.

@vin136 Recently added the mlc-chat.apk to LFS because of size issues. Will remove it for now and keep it as a github release instead. Should fix this for now

repo: mlc-ai/mlc-llm


text:
API Functionnal test script

I add a script that call the API to test all the routers in a functional way : the API is tested as a blackbox in an operational way.
To use it:

docker-compose up
cd carbonserver && tox -e with_api_server

Rebase with master. Update to new data in emission.
Ready to merge.

Need to move test script to tests/integration/


text:
Client configuration profiles

This PR adds logic to handle multiple configuration and authentication profiles. It additionally separates the filesystem by server, so that resources are shared for the same server. Lastly, commands for managing profiles are provided, so users can easily create and adjust their settings.
Closes #197.

I made some modifications which I believe make the code more readable and less hacky. Configuration options now are managed through a decorator. Using the merge_args library, it was possible to attach new options to existing commands in a way that typer can handle directly. We no longer need to parse arguments directly, nor format help messages through unconventional means.

repo: mlcommons/medperf


text:
Handle PR Review Dismissals

We want the Slack notify action to notify when new code is committed to a PR that has been reviewed, but when you have it set up to just run on.push without any branches defined, we consistently see the initial failure from any pushes made before the PR was opened.

This change should enable you to maintain the new code has been committed notifications, while preventing the initial push errors by restricting the on.push.branches trigger to your base branch.

on:
  pull_request:
    types: [opened, ready_for_review, synchronize]
  pull_request_review:
    types: [submitted, dismissed]
  push:
    branches:
      - 'staging'

:tada: This PR is included in version 7.8.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


text:
reading feekback and typo fix

Chapter 5. Up to 5.6 alexnet.

Up to 5.7 VGG, now complete. @mli

can you please resolve the conflicts, we can merge it later

working on check

authors: mli zhreshold

repo: mli/gluon-tutorials-zh


text:
Implement Artifact Store functionality in RDBS version

Implemente the common functionality in the RDBS version.

Fixed in #360

repo: mlte-team/mlte


text:
What commands to say

I saw the section about usage however i am still confused as to what commands i can say. When i try anything it says "sorry that is not supported"
Turn the tv off works just fine but can you give me an example of any other command i could try.

Hi,
If you have installed the HomeKit Catalog app you can specify scenes where you set the channel characteristic to a specific channel number or the volume characteristic to increase, decrease or mute the tv. The scenes name is than a phrase siri will understand. Just note that siri only recognizes the exact wording you've chosen for your scene. Your could e.g. create a scene "I would like to watch Channel 4" and set the channel characteristic (second one after on/off toggle) to 4. If you are using iOS 10 I still suggest using the HomeKit Catalog app since the included Home app seems not to allow changing other characteristics beside the on/off one.

authors: Irish-link mmende

repo: mmende/homebridge-samsungtv-control


text:
Fix scrollbar patch limits in epochs plotter

cc @jaeilepp
Closes https://github.com/mne-tools/mne-python/issues/2324
Got stung by it one too many times. In my opinion, the plotting is also nicer this way.

@jaeilepp merge if you're ok

@Eric89GXL any opinion?

Looks reasonable to me. FYI an alternative single-command would be np.clip instead of min(max()), but min(max()) might actually be a little bit faster since they're builtins.

works great
merged by rebase.
thx @jasmainak

authors: Eric89GXL agramfort jasmainak

repo: mne-tools/mne-python


text:
[MRG+1] Add possibility to plot a source space in head coordinates

currently, this is broken:
import mne
path = mne.datasets.sample.data_path()
fwd = mne.read_forward_solution(path + '/MEG/sample/sample_audvis-meg-oct-6-fwd.fif')
fwd['src'].plot(subjects_dir=path + '/subjects')

It is occasionally useful to plot the source space inside a forward operator, to see which vertices may have been discarded due to falling outside the skull. In this case, the source space is in head coordinates, so things don't line up. This PR allows the user to specify a head<->MRI transformation to make the plotting work:
import mne
path = mne.datasets.sample.data_path()
fwd = mne.read_forward_solution(path + '/MEG/sample/sample_audvis-meg-oct-6-fwd.fif')
fwd['src'].plot(subjects_dir=path + '/subjects',
                trans=path + '/MEG/sample/sample_audvis_raw-trans.fif')

LGTM
@larsoner merge if you're happy too

Thanks @wmvanvliet

authors: agramfort larsoner wmvanvliet


text:
Review opencage api changes

https://github.com/OpenCageData/opencagedata-roadmap/blob/master/CHANGES.md

I created issues for all relevant changes added to the api.

repo: moberwasserlechner/jopencage


text:
Fix/chrome scroll bug

Status: Ready for Review
Owner: @ericawright
Reviewers: @stewartyu
Changes

when scrolled on the page before opening pikabu, the viewport would remain at the top of the page.
remove body height style
remove setting viewport to height of inner window

Issue:
https://github.com/mobify/pikabu/issues/66
Todos:

[ ] Engineer +1

Feedback:
none so far
How to Test

grunt serve
go to http://localhost:3000/examples

Hey Erica, do you know why the diff is so large?

authors: ericawright ericmuyser

repo: mobify/pikabu


text:
[Help]: sbas.topo_ra_parallel() taking too long

Processing with 32 cpu / 128 GB RAM / 2 SSD RAID 0 on Jupyter.
3 SS from 151 SLC.
Dem is set to 15m resolution.

sbas.topo_ra_parallel() running very slowly. It has been about 2 hours and only 15%.

Notebook becomes stuck at 15%. Error in NotebookApp:

The logged error is not related to PyGMTSAR, see
https://github.com/tornadoweb/tornado/issues/2271
https://github.com/python/cpython/issues/85269
To resolve it, try to upgrade all your python libraries (especially tornado). Also, do you use chunk size 1024 (instead of default 512) and dask distributed LocalCluster with tcp and connect timeouts 60s? For the reference, an example configuration for 2 stitched scenes 15m for pygmtsar-large Docker image available on GitHub: https://github.com/mobigroup/YamchiDam/tree/main/notebooks

Yes, I am using chunk size 1024:

It took about 12 hours.

Not only does sbas.topo_ra_parallel() take very long, it is called a second time in sbas.geocode_parallel(). Is this really necessary? It would only make sense on the condition that sbas.get_topo_ra() is empty.
`class SBAS_geocode(SBAS_sbas):
def geocode_parallel(self, pairs=None):
    # find any one interferogram to build the geocoding matrices
    if pairs is None:
        pairs = self.find_pairs()
    # build trans_dat and topo_ra grids
    self.topo_ra_parallel()
    # define the target interferogram grid
    intf_grid = self.open_grids(pairs, 'phasefilt').min('pair').astype(bool)
    # build geographic coordinates transformation matrix for landmask and other grids
    self.intf_ll2ra_matrix_parallel(intf_grid)
    # build radar coordinates transformation matrix for the interferograms grid stack
    self.intf_ra2ll_matrix_parallel(intf_grid)`

geocode_parallel() should be called after merge_parallel() when all the subswaths merged together and so it builds the topography matrix for the merged grid. That's possible to enhance it combining single subswath matrices but for now merge_parallel result is unpredictable sometime (GMTSAR binary is used to do it).
Timeouts can be tuned by this code (see the large Docker image or the same notebooks on GitHub):
import dask, dask.distributed
# increase timeouts to work using default chunk size (512) even on large areas
dask.config.set({'distributed.comm.timeouts.tcp': '60s'})
#print (dask.config.get("distributed.comm.timeouts.tcp"))
dask.config.set({'distributed.comm.timeouts.connect': '60s'})
#print (dask.config.get("distributed.comm.timeouts.connect"))

from dask.distributed import Client, LocalCluster
cluster = LocalCluster(n_workers=1)
client = Client(cluster)
client

I think sbas.topo_ra_parallel() requires about 1 hour on 8 core Apple Air laptop for a single scene topography processing using 15m resolution. So for your case it would be about 15 minutes in case you use all the cores (check your "client" variable output). "LocalCluster(n_workers=1)" can be not optimal for your hardware (I use it to limit the used RAM as possible because 2GB RAM per core is not enough for 2 stitched scenes processing by common way and the trick is required), try just "LocalCluster()".

Using larger cluster seems to make this faster.

authors: SteffanDavies mobigroup

repo: mobigroup/gmtsar


text:
[Feature Request] Ability to query Maestro runtime information (e.g current test)

Is your feature request related to a problem? Please describe.
We are investigating ways through which we can record and play back network interactions during a Maestro test. One requirement that we've run up against is the ability to know which test is running so that we can match request/response pairs to the correct test.
We're aware that you can check whether your app is running in a Maestro environment, but we'd also like to be able to query what test is running.
Describe the solution you'd like
We imagine being able to hit a "Maestro API" on a loopback address, something like:
// some_interceptor.dart
Future<void> onRequest(req, handler) async {
  if (isRunningInMaestro()) {
    final testName = await _maestroApi.fetchTestName();
    final session = await _requestDataStore.fetch(testName);
    final response = session[req];
    if (response != null) {
      handler.resolve(response);
    } else {
      handler.next(request);
    }
  } else {
    handler.next(request)
}

Describe alternatives you've considered
Alternatives are hard here (though we're very open to them!): Since Maestro is running in a black-box, and we don't want to re-build our app between test runs, there's no way to inject this information into the application other than at runtime via Maestro (as far as we can tell...).

Hey, thank you for this issue. This sounds like a duplicate of #1616 to me (yes I know it was created later, but I triaged it in a reverse order, sorry bout that!). Going to close it, but please feel free to comment if I'm wrong!

authors: bartekpacia btrautmann

repo: mobile-dev-inc/maestro


text:
[Maestro v1.33.0] pressKey command hangs and fails eventually

Describe the bug
Using pressKey  command makes Maestro hang and test fails eventually. It happens if there's a constantly updating element on the screen like a timer.
To Reproduce

Start the simulator
Run maestro test ...
The Flow fails at ...

Expected behavior
Command shouldn't hang.
Environment information (please complete the following information):

Maestro version: v1.33.0
Platform: Android TV
Framework: React Native
Device model and OS version: Any Android OS & Model
Simulator, emulator or physical device: All
Host: M1 Mac

Workspace (if applicable)
Will share a simple reproduction apk soon.

I've investigated this problem a bit and it's related to this code piece https://github.com/mobile-dev-inc/maestro/blob/main/maestro-client/src/main/java/maestro/Maestro.kt#L389-L391.
UI never settles in the case I described above and test hangs. waitForAppToSettle can be exposed to the user as a flag under pressKey command but I don't know if it would be something you folks want to do. I can fix this issue but I feel like a brief prior discussion is required before diving into the implementation.


text:
Error:Failed to resolve: com.robert.autoplayvideo:0.1.2:

Please can you help me ?

Sorry for my late. What are you having trouble?

Can't use your gallery Sir

Failed to resolve: com.robert.autoplayvideo:0.1.2: error occur please help

authors: DucHM algorr anonym2

repo: mobileappsvn/AutoPlayVideoRecyclerView


text:
Getting unknown error from FirebaseData class

I wanted to make cleaner code for main class so I made another one and I am getting "unknown error" from instance of FirebaseData class.
`
class fireBase{
public:
FirebaseData fbdo;
FirebaseAuth auth;
FirebaseConfig config;
fireBase(){
    config.api_key = API_KEY;
    config.database_url = DATABASE_URL;
    auth.user.email = GMAIL;
    auth.user.password = GMAIL_PASSWORD;
}

void begin(bool reconnectBase=false){
    Firebase.begin(&config, &auth);
    config.token_status_callback = tokenStatusCallback;
    if(reconnectBase) Firebase.reconnectWiFi(true);
}

bool write(String path, String value){
    bool state = false;
    fbdo.pauseFirebase(false);
    if(Firebase.RTDB.setString(&fbdo, path, value)) state=true;
    else Serial.println("REASON: " + fbdo.errorReason()); //<<From here
    fbdo.pauseFirebase(true);
    return state;
}

bool write(String path, bool value){
    bool state = false;
    fbdo.pauseFirebase(false);
    if(Firebase.RTDB.setBool(&fbdo, path, value)) state=true;
    else Serial.println("REASON: " + fbdo.errorReason()); //<<From here
    fbdo.pauseFirebase(true);
    return state;
}

};
`

Problem begins when trying to unpause firebase. I am using ps4 controller in project and wifi and bluetooth can't work simultaneously, with paused wifi firebaseData ps4 controller can connect, although I am not sure why it works from start with only wifi library and webpage.
fbdo.pauseFirebase(false);

Unknown error means no error.
Call fbdo.errorReason() from the last operation that returns true will give unknow error as no error.
The issue occurred when you call pauseFirebase during no network or server connection and the internal pause status will not change after all.
I will fix this soon.

The update v4.3.8 is available, please download.

Thank you, everything works as intended.

authors: mobizt simzdev

repo: mobizt/Firebase-ESP-Client


text:
Downgrading to mobx-4 for ie11 support

I'm currently building an app with mobx, I was using: "mobx": "5.*", mobx-react-lite: "^2.0.6" when I realised that mobx 5 isn't supported in ie11, so I downgraded to the latest mobx 4 package: "mobx": "4.15.0" as recommended in the Readme.
That stopped the errors and lets the page load, however (and I'll note, this problem only exists on ie11, if i run the mobx 4 version of my app in chrome, it works just fine), that the observers are no longer working and my components don't re-render?
Is there another step in order to downgrade mobx for ie11 support? I noticed a console warning/info to add import 'mobx-react-lite/batchingForReactDom', I tried with and without this and it didn't make a difference

MobX 4 certainly has some limitations in what works for observability due to the different underlying mechanisms. Sadly, there is no overview page of such differences afaik. You need to look at your specific case in the docs.
Also, note that MobX 6 is in the works that will unify this and will be still compatible with IE11. If there is no rush for you to get IE11 compatibility right now, you might be better off with just waiting.
@mweststrate can probably tell more about this.

I'm going to close this as it turned out the virtual box environment was causing me some issues which were affecting other packages and not mobx, as far as I can tell things seem to be working okay now!
Much appreciate your help @FredyC !

repo: mobxjs/mobx-react


text:
mocha watching fails under npm

Hi,
I have a very simple Koa application:
var app = module.exports = require("koa")();

app.use(function *(){
	this.body = "Koa says Hi!";
});

var port = process.env.PORT || (process.argv[2] || 3000);
port = (typeof port === "number") ? port : 3000;

app.listen(port);
console.log("Application started. Listening on port:" + port);

that I test with mocha and supertest like this;
var app = require("../");
var request = require("supertest").agent(app.listen());

describe("Our amazing site", function () {

	it("has a nice welcoming message", function (done) {
		request
			.get("/")
			.expect("Koa says Hi!")
			.end(done);
	});
});

I want to watch my files for changes and use the -w flag like this
mocha -u bdd -R min -w

That works fine. I change a file, the test is reexcuted and all is well.
Now I move that command into my package.json file as a script, like this:
"scripts": {
    "watch:test": "mocha -u bdd -R min -w"
  },

The first time I run the command it works, when I make a change that is picked up but now the test fails with:
1)  Uncaught error outside test suite:
     Uncaught Error: listen EADDRINUSE :::3000
      at Object.exports._errnoException (util.js:837:11)
      at exports._exceptionWithHostPort (util.js:860:20)
      at Server._listen2 (net.js:1231:14)
      at listen (net.js:1267:10)
      at Server.listen (net.js:1363:5)
      at Application.app.listen (node_modules/koa/lib/application.js:70:24)
      at Object.<anonymous> (index.js:10:5)
      at Object.<anonymous> (test/site.spec.js:1:73)
      at Array.forEach (native)
      at StatWatcher._handle.onchange (fs.js:1285:10)

That error will not go away until I stop mocha and then restart it.
Why does it behave differently when run via npm?
What can I do to fix this?

EADDRINUSE  means that port is already in use. In you case, your server was not shutdown after the first test run. You should have a teardown hook (after) to shut down the server, stop listening to the port.

Aaah - that would do it. Night is falling here now. I'll check in on how to stop listening to a koa server tomorrow. Keep you posted

Ha - could of course not sleep after that. yes, your are correct. But I had to jump through some Koa-hoops to get there.
I now expose the server returned by app.listen() from the application and use that to close the server in my test.
Server:
var app = require("koa")();

app.use(function *(){
	this.body = "Koa says Hi!";
});

var port = process.env.PORT || (process.argv[2] || 3000);
port = (typeof port === "number") ? port : 3000;

var server = app.listen(port);
console.log("Application started. Listening on port:" + port);

module.exports = {
	server : server,
	app : app
};

Test:
var app = require("../").app;
var server = require("../").server;
var request = require("supertest").agent(server);

describe("Our amazing site", function () {

	after(function (done) {
		server.close();
		done();
	});

	it("has a nice welcoming message", function (done) {
		request
			.get("/")
			.expect("Koa says Hi!")
			.end(done);
	});
});

Thanks a bunch! Recording a screen cast for PluralSight and this stopped me in my tracks

No problemo!
And thanks much for posting back the solution! I tried finding the way to close the server to paste it back here and couldn't find it in less than 5min. I was left curious. :smile:

I wrote the whole thing down in a blog post, should anyone want to know more.
What I still fail to grasp is why this only failed when run as a script in npm. Running the same mocha command from the prompt worked fine

Why are error messages being suppressed? I can't figure out what I'm seeing this error at all.

repo: mochajs/mocha


text:
.only not working in 3.0.2

We run mocha tests using grunt with a simple config:
mochaTest: {
            functional: {
                options: {
                    reporter: 'dot',
                    timeout: '10000',
                    recursive: true
                },
                src: ['tests/functional/**/test*.js']
            },
            unit: {
                options: {
                    reporter: 'dot',
                    timeout: '10000',
                    recursive: true
                },
                src: ['tests/unit/**/test*.js']
            }
        },

However when we upgraded to mocha 3.0.2, the .only feature does not work anymore. It runs all tests all the time. It works fine with mocha 2.5.3.
I tested it using mocha directly using:
mocha tests/functional/**/test*.js

and .only still not working.
Any help appreciated.

Hey @richardlay! 🙂
I have tried to reproduce this with a fresh install and failed. 😶
Could you please take a quick look and maybe spot what’s different in my scenario from yours, and maybe you can come up with a small subset of your scenario that proves the misbehavior. 🤓

Hi @gurdiga
After doing some simple tests, I could not reproduce it either using the mocha command line.
Actually I don't think my mocha command I posted before is valid... don't think you can specify a regex path like that.
However, grunt-mocha-test accepts a regex path, and it looks like it binds each file to mocha.
grunt-mocha-test MochaWrapper.js snippet:
  params.files.forEach(function(file) {
    file.src.forEach(mocha.addFile.bind(mocha));
  });

Could that be the issue?

Not sure what grunt-mocha-test is up to.  They may need to change something for 3.x; I'd suggest opening an issue there, if you haven't already.  The programmatic API isn't considered "public", so I'm not surprised things are breaking.

@richardlay Maybe you can prepare a repo with the smallest setup that reproduces the issue. I’m open to digging into it some more to find what’s wrong. 🤓
What do you think? 🤔

@boneskull I'm currently working on getting ember-cli-mocha updated to Mocha 3. Everything seems to be working fine except for this issue here. I'll try to extract a small reproduction case.

nevermind, it seems that our issue is most likely related to https://github.com/teddyzeenny/ember-mocha-adapter/blob/master/adapter.js#L169-L172 and not a bug in Mocha.

@gurdiga Hi, sorry taken a while to get back to you. Here's a setup that reproduces the issue. Just run "npm test" (assuming you have grunt installed). Many thanks.
https://github.com/richardlay/grunt-mocha-302

I'm picking this up and know the cause in grunt-mocha-test - unfortunately in order to handle asynchronous errors correctly within grunt I have to replicate the procedure in mocha.run, split it in 2 and wrap the call to runner.run in a domain. This procedure has changed and I just need to update my implementation (copy).
As an aside, if this were split into 2 stages within the mocha API it would make my life easier :) (Or if  it were promise based, which makes catching asynchronous errors much simpler)

This is now fixed in version 0.13.0 of grunt-mocha-test. I'm also working on a pull request for mocha that will hopefully prevent breaking changes when mocha is updated

Didn't need a pull request - mocha seems to have stopped leaking unhandled exceptions asynchronously :) As such I have removed my workaround and now use the API as documented

authors: Turbo87 boneskull gurdiga pghalliday richardlay


text:
most query strategies return either identical or very near identical std for all instances

when I use the following query strategy, I get very similar std values for all of the instances.
def GP_regression_std(regressor, X_pool):
    _, std = regressor.predict(X_pool, return_std=True)
    query_idx = np.argmax(std)
    print(max(std))
    print(min(std))
    print(query_idx)
    return query_idx, X_pool[query_idx]

and the following code spinet is where I train my active leaner regressor and then apply active learning to it
# In this section a Gausian process regressor is used with the ActiveLearner
kernel = RBF(length_scale=1.0, length_scale_bounds=(1e-2, 1e3)) \
         + WhiteKernel(noise_level=1, noise_level_bounds=(1e-10, 1e+1))

regressor = ActiveLearner(
    estimator=GaussianProcessRegressor(kernel=kernel),
    query_strategy=GP_regression_std,
    X_training=X_train, y_training=y_train
)

y_pred = regressor.predict(X_test)
print(mean_squared_error(y_test, y_pred))
print()

n_queries = 10
for idx in range(n_queries):
    query_idx, query_instance = regressor.query(X_pool)
    query_instance = query_instance.reshape(1,-1)
    query_label = y_pool[query_idx].reshape(1,-1)
    regressor.teach(query_instance, query_label)
    X_pool = np.delete(X_pool, query_idx, 0)

y_pred_final = regressor.predict(X_test)
print()
print(mean_squared_error(y_test, y_pred_final))

the output is as follows. the first number being the mean_squared_error before active learning, the second number is the biggest std, the third number is the smalles std and the fourth number is the index of the instance with highest std and then then these numbers are repeated for each query. the very last number is the mean_squared_error after active learning is applied: the situation is the same when I use a Baysian opmtimizer with max_EI, max_PI. the only one seem to be working correctly is max_UCB.
30.651265099894882

3.3166247903554003
3.168658599624672
24666
3.3166242910960957
3.1686585997638748
26558
3.3166235180359047
3.1686564613769344
23131
3.3164740861077475
3.1686562479450835
28997
3.3163078069240384
3.1686388344283087
15744
3.3160924267142
3.1685967954943877
11120
3.3157385357717892
3.1685844957953995
23908
3.315239650363367
3.1685215847608976
13548
3.314345077461044
3.1685123324148354
18970
3.312167480544017
3.1685007990178864
7307

30.671384281234605

the data set i used is taken from UCI and can be found here. its a regression problem with 9 features, all of them numerical. I use about 500 of them for the initial training and use about 30000 of them as the unlabeled pool.

Hi!
I am pretty sure these are algorithmic problems, not implementation ones. The almost identical std happens very frequently with Gaussian processes, this can be improved with proper kernel choice. Unfortunately, I am not an expert about that :)

Thanks for the response. I kind of came to the conclusion that it has got to do with the kernel

repo: modAL-python/modAL


text:
[1.3] Backport https://issues.redhat.com/browse/MODCLUSTER-714 and clean.

Backport https://issues.redhat.com/browse/MODCLUSTER-714.
And clean warnings/errors when using --enable-maintainer-mode

@jfclere Can you pick a reviewer please, so we have 2nd pair of eyes on this :-) thanks!

Cool, thanks

@gzaronikas please also resolve the issues in Jira upon merge. Thanks! (Already done for this one)

authors: jfclere rhusar


text:
Add disk space output to debug occasional test failures

Despite freeing up disk space early on, we saw occasional failures like https://github.com/model-checking/kani/actions/runs/7030685174/job/19130721957 that look like running out of disk space.
This change should be reverted once we have diagnosed the problem.
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 and MIT licenses.

The CI run here suggests that we do have 35 GB of free disk space, so should be fine. Given that we have these sporadic failures, I'd now ask for reviews to get this merged so that we have more diagnostics upon the next failure that we see.

repo: model-checking/kani


text:
Create RMC compiler driver

Requested feature: We should be able to configure the compiler without having to modify its code.
Use case: Provide a robust and clean compilation module for RMC.
Link to relevant documentation (Rust reference, Nomicon, RFC):
Is this a breaking change? No
Success criteria: We replace rmc-rustc by a rust application call. I.e., this issue only covers the creation of the RMC compiler driver on the top of rustc. Follow up issues will track moving more logic out of our python scripts into an RMC application.

We still have rmc-rustc wrapper, but it's mostly needed to overcome a limitation of cargo rmc. I'll close this issue since it has captured the most important issue which is the dependency on a modified rustc and its bootstrap script.

repo: model-checking/rmc


text:
请问如何在推理时加入System Prompt

请问如何在这个教程页面里的代码下面加入系统的提示词：https://swift.readthedocs.io/zh-cn/latest/LLM/VLLM推理加速与部署.html
即使用openai的请求命令时的'role': 'system'参数

template = get_template(template_type, llm_engine.hf_tokenizer, default_system="your system")

or
request_list = [{'system': 'your system', 'query': '你好!'}]

repo: modelscope/ms-swift


text:
🛑 Prowlarr is down

In dc64388, Prowlarr ($PROWLARR_URL) was down:

HTTP code: 523
Response time: 451 ms

Resolved: Prowlarr is back up in fa74bbd.


text:
build(builder): export compiled/* and package.json

PR Details

Description

Related Issue

Motivation and Context

How Has This Been Tested

Types of changes

[ ] Docs change / refactoring / dependency upgrade
[ ] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to change)

Checklist

[ ] My code follows the code style of this project.
[ ] I have updated changeset
[ ] My change requires a change to the documentation.
[ ] I have updated the documentation accordingly.
[ ] I have read the CONTRIBUTING document.
[ ] I have added tests to cover my changes.
[ ] All new and existing tests passed.

如果使用通配符导出 compiled 的话，后续就没法区分出哪些包被外部使用了，感觉显式声明导出的路径会更好

如果使用通配符导出 compiled 的话，后续就没法区分出哪些包被外部使用了，感觉显式声明导出的路径会更好

我改了下，就先导出 package.json 好了


text:
Add a new class DictProvider to handle a dictionary of values.

MR adds a new class DictProvider to the codebase, which allows for handling dictionary values and resolving them asynchronously or synchronously.
Issue: https://github.com/modern-python/that-depends/issues/29

@lesnik512  could you take a look, please? If it's okay I'll add the tests and docs as well.

@lesnik512  I've added some docs. Also, I planned to add tests, but it seems the containers don't have any tests.

@Denis-Frunza thank you! I merged it and wrote simple test. And released it https://github.com/modern-python/that-depends/releases/tag/1.12.0

repo: modern-python/that-depends


text:
refactor: Update Gradle wrapper

Use this link to re-run the recipe: https://app.moderne.io/recipes/org.openrewrite.gradle.UpdateGradleWrapper?organizationId=TW9kZXJuZQ%3D%3D

Would you want me to move that parser to the root? It's become an essential part of this project but started out experimental.

This was done by running the UpdateGradleWrapper recipe -- should the behavior of that recipe change?

This was done by running the UpdateGradleWrapper recipe -- should the behavior of that recipe change?

This project is odd, but perhaps not unusual; did you use Add if missing in your run? I only see a link to the recipe and org, not to any variables used.
Ideally yes we fix the recipe to tolerate finding Gradle wrappers in different locations, although I'd hope not to encounter that too often.

And I'll fix this project here.

did you use Add if missing in your run?

No, I didn't use Add if missing

authors: kmccarp timtebeek

repo: moderneinc/jenkins-ingest


text:
Unpin mindsdb_sql as soon as dfsql fixed own deps on mindsdb_sql

Revert changes, included by this #3248

Did we open an issue on dfsql?

They are currently working on it.
https://github.com/mindsdb/dfsql/pull/19

authors: YarShev devin-petersohn prutskov

repo: modin-project/modin


text:
Describe fails on modin for certain dtypes and doesn't support certain parameter values

System information
ray 1.9.2
modin 0.12.0
python 3.9.7
Describe the problem
modin_df = modin_pd.DataFrame(
    {
        'a': modin_pd.date_range('1/1/2000', periods=4, freq='D'),
        'b': [10.0, np.nan, 9.0, 13.0],
        'c': [50, 60, 40, 100],
        'd': list('abcd')
    }
)

modin_df.describe(include=[np.number])

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Input In [11], in <module>
----> 1 modin_df.describe(include=[np.number])

File conda/anaconda/lib/python3.8/site-packages/modin/pandas/base.py:1081, in BasePandasDataset.describe(self, percentiles, include, exclude, datetime_is_numeric)
   1074         include = [include]
   1075     include = [
   1076         np.dtype(i)
   1077         if not (isinstance(i, type) and i.__module__ == "numpy")
   1078         else i
   1079         for i in include
   1080     ]
-> 1081     if not any(
   1082         (isinstance(inc, np.dtype) and inc == d)
   1083         or (
   1084             not isinstance(inc, np.dtype)
   1085             and inc.__subclasscheck__(getattr(np, d.__str__()))
   1086         )
   1087         for d in self._get_dtypes()
   1088         for inc in include
   1089     ):
   1090         # This is the error that pandas throws.
   1091         raise ValueError("No objects to concatenate")
   1092 if exclude is not None:

File conda/anaconda/lib/python3.8/site-packages/modin/pandas/base.py:1085, in <genexpr>(.0)
   1074         include = [include]
   1075     include = [
   1076         np.dtype(i)
   1077         if not (isinstance(i, type) and i.__module__ == "numpy")
   1078         else i
   1079         for i in include
   1080     ]
   1081     if not any(
   1082         (isinstance(inc, np.dtype) and inc == d)
   1083         or (
   1084             not isinstance(inc, np.dtype)
-> 1085             and inc.__subclasscheck__(getattr(np, d.__str__()))
   1086         )
   1087         for d in self._get_dtypes()
   1088         for inc in include
   1089     ):
   1090         # This is the error that pandas throws.
   1091         raise ValueError("No objects to concatenate")
   1092 if exclude is not None:

File conda/anaconda/lib/python3.8/site-packages/numpy/__init__.py:315, in __getattr__(attr)
    312     from .testing import Tester
    313     return Tester
--> 315 raise AttributeError("module {!r} has no attribute "
    316                      "{!r}".format(__name__, attr))

AttributeError: module 'numpy' has no attribute 'datetime64[ns]'

Values category and number not supported for exclude parameter
modin_df.describe(exclude=["category"], datetime_is_numeric=True)

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Input In [48], in <module>
----> 1 modin_df.describe(exclude=["category"], datetime_is_numeric=True)

File conda/anaconda/lib/python3.8/site-packages/modin/pandas/base.py:1095, in BasePandasDataset.describe(self, percentiles, include, exclude, datetime_is_numeric)
   1093 if not is_list_like(exclude):
   1094     exclude = [exclude]
-> 1095 exclude = [np.dtype(e) for e in exclude]
   1096 if all(
   1097     (isinstance(exc, np.dtype) and exc == d)
   1098     or (
   (...)
   1104 ):
   1105     # This is the error that pandas throws.
   1106     raise ValueError("No objects to concatenate")

File conda/anaconda/lib/python3.8/site-packages/modin/pandas/base.py:1095, in <listcomp>(.0)
   1093 if not is_list_like(exclude):
   1094     exclude = [exclude]
-> 1095 exclude = [np.dtype(e) for e in exclude]
   1096 if all(
   1097     (isinstance(exc, np.dtype) and exc == d)
   1098     or (
   (...)
   1104 ):
   1105     # This is the error that pandas throws.
   1106     raise ValueError("No objects to concatenate")

TypeError: data type 'category' not understood

modin_df.describe(exclude=["number"], datetime_is_numeric=True)

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Input In [49], in <module>
----> 1 modin_df.describe(exclude=["number"], datetime_is_numeric=True)

File conda/anaconda/lib/python3.8/site-packages/modin/pandas/base.py:1095, in BasePandasDataset.describe(self, percentiles, include, exclude, datetime_is_numeric)
   1093 if not is_list_like(exclude):
   1094     exclude = [exclude]
-> 1095 exclude = [np.dtype(e) for e in exclude]
   1096 if all(
   1097     (isinstance(exc, np.dtype) and exc == d)
   1098     or (
   (...)
   1104 ):
   1105     # This is the error that pandas throws.
   1106     raise ValueError("No objects to concatenate")

File conda/anaconda/lib/python3.8/site-packages/modin/pandas/base.py:1095, in <listcomp>(.0)
   1093 if not is_list_like(exclude):
   1094     exclude = [exclude]
-> 1095 exclude = [np.dtype(e) for e in exclude]
   1096 if all(
   1097     (isinstance(exc, np.dtype) and exc == d)
   1098     or (
   (...)
   1104 ):
   1105     # This is the error that pandas throws.
   1106     raise ValueError("No objects to concatenate")

TypeError: data type 'number' not understood

All these work on Pandas

@c3-cjazra this is fixed in modin 0.23.0. The release should be available today.


text:
corr and cov is slower in Modin

System information

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): MacOSX
Modin version (modin.__version__): 0.15.0
Python version: Python 3.9.9
Code we can use to reproduce:

Timing code: cov_corr.ipynb.zip
Data: synthetic_100_31622.parquet.gz

Describe the problem
corr and cov take longer in pandas. When I run scalability experiments where the number of rows (up to 1M) is varied, the Modin runtime increases at a faster rate as we increase the number of rows.

Source code / logs

@dorisjlee thanks for reporting this issue. I get similar results on my mac. corr on the whole dataframe from your file takes 112 sec on Modin and 16.1 sec on pandas. Here's a self-contained reproducer where the corr takes 78 sec in modin and 12 sec in pandas.
import modin.pandas as pd
import numpy as np
from modin.config import BenchmarkMode
import pandas
import time

BenchmarkMode.put(True)

np.random.seed(0)
pdf = pandas.DataFrame(np.random.randint(0, 100, size=(2**19, 100)))
start = time.time()
pdf.corr()
end = time.time()
print(f'pandas corr took {end - start}')
df = pd.DataFrame(pdf)
start = time.time()
df.corr()
end = time.time()
print(f'modin corr took {end - start}')

cov is similar: 5.2 sec on modin and 1.6 sec on pandas.
I dug into the performance with ray timeline (corr and cov timelines for the reproducer attached here). It looks like Modin is slow because the distributed full-axis tasks are way too slow, e.g. 76 sec for each of the 3 larger (32 column as opposed to 4 column) column partitions for corr. That function for both cov and corr is here.
@YarShev I see that you implemented the initial version of that function in #2130. Did you do any performance testing then? How could we speed up the remote tasks? Is there any way to use the pandas corr and cov implementation?
ray timelines
System Specs

macOSMonterey 12.2.1
MacBook Pro (16-inch, 2019)
2.3 GHz 8-Core Intel Core i9
16 GB 2667 MHz DDR4

This is a duplicate of #2399. The initial version of the corr/cov was implemented in #2130. We didn't benchmark it well then but IIRC, the performance was near the same as in pandas by using some big dataset, but I am not sure of the exact shape. Still, yes, we definitely need to improve the corr/cov operations. There was an attempt for this as part of #2400 where we introduced a new Modin dataframe's operator but decided not to add it because of its doubtful performance. There is a number of ways we can go with but probably not limited to.

Sharpen the new operator introduced in #2400 to see if it is beneficial for all/most cases.
Try to transpose self in the remote tasks.
2 + broadcast right/other dataframe to the left row partitions in order to transform it to a numpy array in the remote tasks instead of doing this in the main thread.

@mvashishtha, would you be willing to tackle this? If any question arises, feel free to ask me.

@YarShev thank you, that's very helpful. I'll mark #2399 as a duplicate of this issue because this issue has so many details now.

@mvashishtha, would you be willing to tackle this? If any question arises, feel free to ask me.

Unfortunately, I can't take this on for now.

#6193 only fixed the perf for .corr() method. Here's a separate issue for .cov(): #6248

authors: YarShev dchigarev dorisjlee mvashishtha


text:
PERF-#367: Using numpy to alter values of service buffer

What do these changes do?

In _allocate_shared_memory(self): function we are setting -1 to the service buffer because 0 is a valid value. This operation is a time consuming operation. Changing this to use numpy to speed up the step.

[ ] first commit message and PR title follow format outlined here

NOTE:  If you edit the PR title to match this format, you need to add another commit (even if it's empty) or amend your last commit for the CI job that checks the PR title to pick up the new PR title.

[ ] passes flake8 .
[ ] passes black .
[x] signed commit with git commit -s
[ ] Resolves #367
[ ] tests added and passing
[ ] module layout described at docs/developer/architecture.rst is up-to-date

Please also rename the PR title and exclude the file unidist/core/backends/mpi/core/memory/_memory.cpp (it is auto-generated by cython) out of this PR.

Some perf measurements would also be helpful.

repo: modin-project/unidist


text:
WIP display spawnpoints

TODO List:

[X] add spawnpoint markers to the map
[X] add a popup with information about spawns on that point
[ ] nice formating of the popup
[ ] nice image for the spawnpoints
[ ] clustering! so it does not kill the browser
[ ] add options for customization to the config

Screenshot of WIP

I like it! Should I do the code review, or should I wait with it until you're happy with its shape?

@modrzew todo list is on 2/6 - and some of the code will be touched with clustering. Guess I will have done most tomorrow evening

Oh boy, I'm very excited for this!
Do you see any way to include an aggregate of spawn numbers per Pokemon, without cluttering the thing too much? So from the example of your screenshot it could display something like

Hornliu: 3 (50%)
Rattfratz: 2 (33,3%)
Zubat: 1 (16,6%)

Yes that is the goal in the long run. Also a classification may be included (blue dots for points that get classified as water)
But one step after the other

I am currently working on a classifcation algorithm which could be integrated with pokeminer (see https://www.reddit.com/r/pokemongodev/comments/4xfw9r/biomes_debunked/)
I am currently rewriting my matlab code prototype to python, which is now almost done, so this might be possible to do in the not so distant future

@FFroehlich that post was the reason I started this! When you are ready to show something I would be happy to review it.

@modrzew code quality has gone down in the last commits but I will not have much time to code the rest of the week; so I released what I had. Top post has my thoughts on what could be improved.
Also one note: if you use this with python 2.7 there are ascii errors again which I ignored since the project is going 3.5

okay couldn't sleep, so added clustering and its amazing! performance has gone way up!

I just try it and it's very nice!
I was using it with python 2.7 and as expected, i got an ascii error. With python 3, no problem.
Simple suggestion, it would be nice to not display the filtered pokemon (those in the TRASH_IDS) array as they add a lot of unnecessary data.

@fxbt I really intended something different. It is intended to show all data - this way you can see if there was a skipped spawn or not.
Also what if you have a spawn that only spawned trash? Would this point not be displayed? This way you kind of loose information.

authors: Aiyubi FFroehlich Innenseide fxbt modrzew

repo: modrzew/pokeminer


text:
Mod-CSS not working with SvelteKit due to hydration

I tried using Mod-CSS with SvelteKit but the style only applies for a couple milliseconds and disappears. I tried debugging it with GPT-4 and it says it's likely due to the server-side rendering nature of SvelteKit.

Hello Heedong,
Thanks for your feedback.
Let me see what can I do about that.
See you soon  ;-)

authors: dev-geos heedongcho-xyz


text:
Feat/avoid extract same zip

Avoid files deletion and archive extraction on native federation if the remote archive didn't change

@ilteoood Can you keep the prefix format of your mr title? In this way, we can ensure the uniform format of github release note we generate

authors: ilteoood zhoushaw

repo: module-federation/core


text:
🛑 STATUS.MOFE.IO is down

In a5200dc, STATUS.MOFE.IO (https://status.mofe.io) was down:

HTTP code: 0
Response time: 0 ms

Resolved: STATUS.MOFE.IO is back up in ace5af3.

repo: mofelee/upptime


text:
Configure the period of time betweek token checks

The following PR will address and hopefully solve #5
It is basically adding another parameter that will configure a Cookie; when this is expired, the user info endpoint will be called again to make sure the token is still valid.
I put 60 (seconds) as default as I think is a good value. Who's more obsessed about the security can definitely set this to 0 or 1, according to the Max-Age parameter.
I'd like to test these things, I still have to come out with a way to spin up a fake oauth2 server, though.
@mogui ^

yep I don't have a clue too, on how to fake the oauth flow for a test :P

This -> https://github.com/patientsknowbest/fake-oauth2-server

Looking forward for the new release

authors: XVincentX mogui

repo: mogui/kong-external-oauth


text:
Password visible in the 'bash history'

would change the  parser.add_argument('--password', '-P', required=True, type=str)
into  parser.add_argument('--password', '-P', required=False, type=str)
adding "from getpass import getpass" in the import section
adding :
"
if not args.password:
args.password=getpass()
"
just after the "args = parser.parse_args()"
same could apply to some other fields :) (when you want to run it manually it help to reduce the leak of the password in some logs )

Hi Secufred,
yes you are right. I adjusted most of the scripts to use getpass instead of the direct input.
I think this is the more appropriate way to do.
Thanks again for your support.
Martin

authors: mohlcyber secufred


text:
fix broken link

Type of PR

[ ] BUG
[ ] FEAT
[ ] MAINT
[x] DOC

Is your Pull Request linked to an existing Issue or Pull Request?

Give a brief description for the solution you have provided

PR Checklist

[ ] Added documentation for changes
[ ] Added feature to example notebooks or tutorial (if appropriate)
[ ] Added tests (if appropriate)
[ ] Updated CHANGELOG.md (if appropriate)
[x] Made changes based off the latest version of Splink
[ ] Run the linter
[ ] Run the spellchecker (if appropriate)

Thank you! I might be misunderstanding something but I think you possibly made this change on quite an old versino of splink, hence the weird diff.  Could you make the change in https://github.com/moj-analytical-services/splink/pull/2238/commits/93f22e1344d2ff8aad400be87cc3dd8a45ac31a9 on the latest master so the diff/merge is simpler?

Thanks. Closing in favour of https://github.com/moj-analytical-services/splink/pull/2240

authors: RobinL dkaufman-rc

repo: moj-analytical-services/splink


text:
reserved keywords for native DOM elements, everything else is a component

Enables stuff like this:
<template name="blarg">

    </template>

    <!-- this doesn't work now, but it will in the future -->
    <blarg />

Already kind of doable with the current implementation. Wontfix for now since it's not a feature request.


text:
demo / docs page appears broken

What used to be contained in the left-hand window (api docs) is now at the bottom of the page, and the slide mechanism appears broken. Anyone else seeing this?

Excuse the late reply, but I am not seeing this. I'd be happy to correct it, if you could more explicitly tell me what you are experiencing?

The documentation will be rewritten. Thank you!

authors: braxtonfair newswim

repo: mojotech/jeet


text:
Latest alpha seems to stretch Portrait images.

In this first image you can see two pictures taken with the camera in iOS, one portrait one landscape. This was done using the stable version.

In this second image the photos were taken after updating to latest alpha, again portrait and landscape but as you can see the image is stretched.

Only thing that changed was updating to the latest alpha.
Thanks!

Actually I think this is a diff plugin. Sorry.

repo: molinch/FFImageLoading


text:
ATAC5 not found

Hello, I found that there is no ATAC5 in the folder of 'exe' after compiling, leading to the failure when trying to deal with 5-vertex motifs. Can you kindly recheck the files? Thanks.

Hi, the ATAC5 module is currently in the process of being developed and is not yet accessible. However, it is expected to become available in the near future. We appreciate your enthusiasm for the project.

repo: momatinaj/MOSER


text:
endOf('day') fails on days that don't start at midnight

Consider:
moment("2016-10-16").endOf('day').format("YYYY-MM-DD HH:mm:ss")

In most time zones, this will return "2016-10-16 23:59:59".   However, in Brazil, this will return "2016-10-17 00:59:59".  This is incorrect, because only the hour from 00:00 to 00:59 on 2016-10-16 is missing.  The end of 2016-10-16 is still 23:59:59 on the same date.
This is also reproducible with moment-timezone:
moment.tz("2016-10-16","America/Sao_Paulo").endOf('day').format("YYYY-MM-DD HH:mm:ss")

The problem is in the endOf method.  To compute the end of the day, we take the start of the day, add one day, then subtract one millisecond.  That logic is flawed when the day doesn't start at midnight.  Instead of adding one day, we need to add the exact duration length of the particular day.

This was originally reported as moment/moment-timezone#327.
#2749 is related, but slightly different.

As opposed to computing the exact length of time of the day, can't you just do:
moment('2016-10-16').startOf('day').add(1, 'day').startOf('day').subtract(1, 'millisecond').format()
"2016-10-16T23:59:59-02:00"

Works fine on the 15th when pushed into the 16th as well:
moment('2016-10-15').startOf('day').add(1, 'day').startOf('day').subtract(1, 'millisecond').format()
"2016-10-15T23:59:59-03:00"

Is there an edge case that I"m not thinking of?
I suppose there might be a performance benefit to doing it differently, but heck, you can read it!

Hmmmm, something else screwy here:
moment.tz("2016-10-16","America/Sao_Paulo").startOf('day').add(1,'day').startOf('day').subtract(1,'ms').format()
// "2016-10-16T23:59:59-02:00"  (ok)

moment.tz("2016-10-15","America/Sao_Paulo").startOf('day').add(1,'day').startOf('day').subtract(1,'ms').format()
// "2016-10-14T23:59:59-03:00"  (wrong date)

moment.tz("2016-10-15","America/Sao_Paulo").startOf('day').add(1,'day').format()
// "2016-10-15T23:00:00-03:00"  should have skipped forward to "2016-10-16T01:00:00-02:00"

Are we just dealing with the whole ambiguous browser behavior here? Or is there something more to it?

In chrome with the windows timezone of Brasillia:
moment("2016-10-15").startOf('day').format()
"2016-10-15T00:00:00-03:00"
moment("2016-10-15").startOf('day').add(1, 'day').format()
"2016-10-16T01:00:00-02:00"

In chrome with my timezone using Moment Timezone:
moment.tz("2016-10-15","America/Sao_Paulo").startOf('day').format()
"2016-10-15T00:00:00-03:00"
moment.tz("2016-10-15","America/Sao_Paulo").add(1, 'day').format()
"2016-10-15T23:00:00-03:00"

COOL!
Something up with moment timezone? I don't really know that code so it's hard to say.

I think that this is a result of the fact that moment timezone will always push an invalid date back, if it has been 'added' into that date. Whether by design or on accident I am not sure.
//setting moves forward
moment.tz("2016-10-16T00:00:00","America/Sao_Paulo").format()
"2016-10-16T01:00:00-02:00"
//adding moves backward
moment.tz("2016-10-15T00:00:00","America/Sao_Paulo").add(1, 'day').format()
"2016-10-15T23:00:00-03:00"

//setting moves forward
moment.tz("2016-03-13T02:00:00","America/Chicago").format()
"2016-03-13T03:00:00-05:00"
//adding moves backward
moment.tz("2016-03-12T02:00:00","America/Chicago").add(1, 'day').format()
"2016-03-13T01:00:00-06:00"

//one more time for funzies
moment.tz("2016-03-27T01:00:00","Europe/London").format()
"2016-03-27T02:00:00+01:00"

moment.tz("2016-03-26T01:00:00","Europe/London").add(1, 'day').format()
"2016-03-27T00:00:00Z"

I think this has something to do with trying to use the keepTime setting when you can't keep the time. I don't know this code well enough to tell you why the code is the way it is, but I know for sure that if the keepTime call in this code were 0 instead of 1, everything would go forward as expected. It's because keep time is on that it's pushed back. And keep time should be on, it just is funky with this edge case.
	moment.updateOffset = function (mom, keepTime) {
		var zone = moment.defaultZone,
			offset;

		if (mom._z === undefined) {
			if (zone && needsOffset(mom) && !mom._isUTC) {
				mom._d = moment.utc(mom._a)._d;
				mom.utc().add(zone.parse(mom), 'minutes');
			}
			mom._z = zone;
		}
		if (mom._z) {
			offset = mom._z.offset(mom);
			if (Math.abs(offset) < 16) {
				offset = offset / 60;
			}
			if (mom.utcOffset !== undefined) {
				mom.utcOffset(-offset, keepTime);
			} else {
				mom.zone(offset, keepTime);
			}
		}
	};

I don't know enough about moment-timezone to be helpful here, but perhaps the ticket on why keepTime is used will be helpful to anyone investigating: https://github.com/moment/moment-timezone/issues/28

https://github.com/moment/moment/pull/1564
This is the last big change in handling zones in moment. Not sure if its related to this issue, but it should help.
@maggiepint can you explain a bit the

will always push an invalid date back

part. I mean -- do we have an example that exposes a problem with moment-timezone, or we just need some smart code in moment to detect DST at the start/end of the day and handle it appropriately. The second is medium-to-easy. If we have to refactor again the zone passing between the moment-tz and moment, then its hell -- I'd rather wait for 3.0 and hope the new interface won't have this issue.

@ichernev the way the code stands today, we have two issues in this one issue. One is the issue that @mj1856 originally raised, which is that days that don't start at midnight end up with a funky end of day value. This is a moment issue.
The other is that moment timezone, when presented with an invalid date, goes forward if that invalid date is used in the constructor, but it goes backward if it is 'added' into that date. This is, as it stands, an issue with moment timezone and not moment. I'm not sure how the timezone interface changes that - I would have to think about it a bit.

@maggiepint thank you for the clear explanation.
So to fix the moment problem : endOf('day') being inaccurate -- just "aim" for the end of the day, go there, if its 00:00, finish, otherwise aim again, if the second aim reaches 00:00 we're done otherwise use the first shot. The second aim will help if we jump across DST and are "distorted" by an hour. If the end of day is an invalid time because of DST, the second aim won't hurt.
We should use this algo for all endOf, maybe even startOf, but that is harder to reason with the set-to-zero we currently do.

Hi guys, I am also being affected by this issue on the current version of moment (2.14.1).

I have #3716 submitted to fix this, but am currently seeing issues with Travis CI for transpile reasons. Will be looking into it more soon.

This one is also related (default Brazilian locale).
Operation results in the same date:
moment(("2017-10-16T00:59:59.999").subtract(1,'day').endOf('day')
=> "2017-10-16T00:59:59.999"

Hey - I just submitted #4164 which fixes this for startOf as well as endOf. Would love to get feedback there so we can hopefully finally move this forward.

@mj1856 , I closed my PR because the problem with endOf in DST edge seems to be fixed. Could this be fixed too?

@Seldaek is working for startOf. endOf has the problem yet.
October 20th is the last day without DST. October 21th is the first day of DST.
Ruby does the right thing:

Moment doesn't:

This looks like be fixed on #4164.

authors: Joqus Seldaek darakeon icambron ichernev keithwillcode lourenci m0nzderr maggiepint mj1856

repo: moment/moment


text:
1 test failed. relative time:custom rounding (2721.3)

Client info
Date String   : Tue Mar 14 2017 01:23:36 GMT-0400 (EDT)
Locale String : 3/14/2017, 1:23:36 AM
Offset        : 240
User Agent    : Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3013.3 Safari/537.36
Moment Version: 2.17.1

====
relative time:custom rounding (2721.3)
Round down towards the nearest day
// Expected in 30 days
// Actual   in a month
"in a month" === "in 30 days"

Closing as a dupe of #3801

authors: icambron verzil


text:
[bugfix-ts3.1]moment.d.ts add isoWeeksInISOWeekYear

Summary

Test plan
ts3.1-typing-tests/moment-tests.ts and typing-tests/moment-tests.ts

Coverage remained the same at 88.48% when pulling 8309115180bf941a7176de2299f2763a2001cf52 on Alanscut:ts_bug into 2259e43cfefe3a4a306ef25f4db37e0824d32d43 on moment:develop.

authors: Alanscut coveralls


text:
website of uku.js always shown as “loadig”

I've already opened VPN

Hi Bloom， could you check your network again？Ukulele.js official website is running on the github.io server, it works well for me.

Well, it works well at the moment.


text:
fix refresh_tokens

Не работала смена токена. так как в методе присутствует 2 ошибочки
1 после requests.get нет преобразования в text как это реализовано в остальных методах
2 опечатка в названии переменной должно быть  self.access_token, а не self.auth_token

Спасибо!

authors: MSITETOP momoru-kun

repo: momoru-kun/PyBitrix


text:
Doesn't works on Android?

I found a issue when trying to open the .html in android
I have opened the file on 2 android devices to test and on both devices I get a white screen when opening said .html with a native browser of the phone and with an external android browser when opening the .html file, it simply never connects even if they are connected to the same wifi

The native browser sucks, don't use it.
When using a separate device, you need to find your laptop's IP and either
a) host a little web server on the laptop
b) make neopixel.js point towards the laptop's IP

repo: mon/spice-drs-pad


text:
Set lower version constraint on satysfi-base

List.split-at is available at satysfi-base 1.4.0 and later.
This PR backports https://github.com/na4zagin3/satyrographos-repo/pull/450

Thank you!

repo: monaqa/satysfi-azmath


text:
[Obsolete] MONDO_0005569 'cartilage disease'

Mondo term (ID and Label)
MONDO_0005569 'cartilage disease'
Reason for deprecation
Uncertain if this grouping class is needed, the children can be classified elsewhere.
Discussed on call with @ahamosh and @pnrobinson (and @sabrinatoro)
Suggested term to consider
MONDO_0003816 'articular cartilage disease' or 'disease or disorder'

part of #3155

authors: nicolevasilevsky sabrinatoro

repo: monarch-initiative/mondo


text:
Draft 1: Update confirmed subclass of evidence in Mondo

This PR

Adds a workflow for updating confirmed subclass of evidence
Updates mondo-edit.obo accordingly

Issues of dispute
Against our previous agreement, the current version of the "confirmed" subclassOf axioms covers "Case 2 (SCR is direct in source, but indirect Mondo)". So, in other words, we include subclassOf axioms that are implied by Mondo (not asserted in the edit file!) and confirmed by an external source.
Example:
[Term]
id: MONDO:0000266
name: pulmonary aspergilloma
def: "A aspergillosis that involves the lung." [MONDO:patterns/location]
...
intersection_of: MONDO:0005657 ! aspergillosis
intersection_of: disease_has_location UBERON:0002048 ! lung

results in this:
[Term]
id: MONDO:0000266
name: pulmonary aspergilloma
def: "A aspergillosis that involves the lung." [MONDO:patterns/location]
...
is_a: MONDO:0005657 {source="DOID:0050153"} ! aspergillosis
intersection_of: MONDO:0005657 ! aspergillosis
intersection_of: disease_has_location UBERON:0002048 ! lung

https://docs.google.com/document/d/1H8fJKiKD-L1tfS-2LJu8t0_2YXJ1PQJ_7Zkoj7Vf7xA/edit#heading=h.9hixairfgxa1
Chris would probably be very against this, and I must say, I am also against it, but weakly. Indeed, I am like 55% against it, and 45% think this could be a good idea. The advantage is that we see all the evidence as Mondo curators - every positive subsumption. When we make classification decisions in the future, we can see them all in the edit file (not just the non-redundant ones). Note - all of these are implied, so they are all correct. Today.
The clear disadvantage is though that changing our logical definitions / patterns (equivalent class statements) will no longer be sufficient to change classification - if you really want to get rid of some subsumption moving forward, you must physically delete both the equivalence class axioms and the asserted subclass axiom. Here is a particularly bad scenario: We decide a pattern no longer works and change it, which leads to changes in classification. The old classification will not be removed, as the subclass of axioms have now been baked into the class hierarchy. I dont know though how much of a problem this is in reality.
I would suggest you

Consult Chris on slack about his opinion on this. Its a big, PI-level, change.
If he says "no", we need to change the source for the "confirmed subclass pipeline" to "mondo-edit". Its not a huge deal, but may require some thinking.
If he says "yes", we still need to determine if there is a bug in this PR or not - I spot-checked 10 random examples and they are all correct (correct in the sense, mondo entails the subclass axiom).

I don't mind the redundancy. In fact, I think it is helpful as it adds a level of confidence to the term classification (which is always good since Mondo integrates multiple sources).
We could consider removing this redundancy in the released version of the ontology (actually we might already do it), but I personally would keep it.

thx @twhetzel, i will wait for your approval to merge!

authors: matentzn sabrinatoro


text:
Add ext ref to LIRICAL phenopackets

The PMID is not showing up in the export file -- adjust the script
Probably we want a warning from PPKtStore

done

repo: monarch-initiative/phenopacket-store


text:
Merchant cleanup

Hi,
can we get rootbox.host removed as a merchant? Trusting the fact they are added as a merchant in the official docs I purchased a server with them.
Result:

My moneroj are gone
No server or anything
Nobody responding to any of the repeated attempts of communication.

So regardless of if the initial intentions were good or not, at this point it's just a scam or, at best, a black hole to throw your Moneroj in and should be removed.

Nobody responding to any of the repeated attempts of communication.

How did you try to contact them? The only contact email I could find anywhere was kevin@rootbox.host

I tried via the email (kevin@rootbox.host) , the  internal ticketing system and through reddit. So far no response at all.
It looks like this was a single person project and it was abandoned without notice, but the infrastructure for making the payments is still up. I will let you know if I get any feedback, but the last reddit post from Rootbox was 4 months ago, so I don't expect much.

Trusting the fact they are added as a merchant in the official docs

Anyone can add a PR to the site and add information. We can't always verify the honesty of merchants. It being listed is not an endorsement by "Monero" (there's not organization just a group of people that decide to contribute).
I think we should consider removing them as long as long as nobody else says they're legitimate.
@RootBox-Kevin We're considering de-listing your site. If you'd like to comment, please do so in this issue.

Hi,
I finally got a response, so I it seems there has been some issues with the service, so, in the end, it does look legitimate. I'll be closing the issue, if it's OK with you all.

Hi everyone. Just a quick update here:
jmg87, I now see your email in my inbox at kevin@rootbox.host on the 25th at 12:41 PM. Unfortunately I did not see this email in time. I apologize for this delay. However I noticed at 15:23 on the 25th you created ticket ID#84160. To clarify I did respond at 7:09 on the 26th. We do try our absolute best to respond to every ticket sent into support@rootbox.host within 24 hours. I apologize about the hassle here! Moving forward I will try to keep a closer eye on my personal email as well. Rest assured we are legitimate :)

repo: monero-project/monero-site


text:
ラジオボタンのdisabled時の振る舞いを修正する

概要
ラジオボタンのdisabled時の振る舞いを修正します。

disabled時はテキストカラーを #999 にする
disabled時はカーソル操作不可であることを示す。cursor-pointer: not-allowed

左から chrome, Firefox, Safari

対応内容
CSSセレクタを活用して、checkedやdisabledの状態を管理します。
そのためにHTMLとCSSのリファクタリングを行っています。
リファクタリング内容

構造を整理して不要なスタイルとHTMLを削除
radioボタンの表示をsvgからdiv要素に変更(CSSで描画)
Propsは ComponentPropsWithRef<'input'> を使い一般的なInputの属性をカバーする

レビュー箇所

disabledの振る舞いが実現できているか

すみませんですが、disabledの時、まだcheckedしているそうですが、その修正は別のPRで対応しますか。

@xistz
なるほど、このグレーの輪はdisabledの意図した見た目じゃないのですね！
(勘違いしてました)
修正しまっす！

ありがとうございました！

利用プロダクトで検証したいので、少しステイです

検証問題なさそうなのでマージします、レビュあざました！

と思ったけど、もっかいapproveが必要そうだ！！

@xistz @kimromi
すません、approveの魔法が切れちゃってたのでもう一度approveお願いします！
実装は変更してません！

あじゃます！ 前と実装変わらないので1LGTMでマージします！

authors: m-yoshiro xistz

repo: moneyforward/cloud-react-ui


text:
Faulty Money comparisons for negative values

Calculator defines an interface to compare numbers:
    /**
     * Compare a to b.
     *
     * @param string $a
     * @param string $b
     *
     * @return int
     */
    public function compare($a, $b);

Since nothing is documented concerning the meaning of the returnvalue, I would expect that it returns a negative number when $a < $b, zero when $a = $b and a positive number when $a > $b. This expectation conforms to e.g. http://php.net/manual/en/function.usort.php or the <=> operator of PHP7.
Looking at Money.php, you will find several operations where the result of compare() is compared to either +1 or -1, which is subtly different from above assumption. For GMP, check this example:
$a = gmp_init('-100');
$b = gmp_init('100');
$res = gmp_cmp($a, $b);
var_dump($res);

On my machine, the output is -2, which then breaks Money when comparing negative amounts.
I'm in the process of preparing a patch with the following features:

No more comparisons with +1 or -1 are left in Money.
Tests for comparisons of negative numbers exist.
Tests (CalculatorTestCase.php) don't assume a specific negative or positive value either.

Here's the promised patch:
0001-Fix-numeric-comparison-for-negative-numbers.patch.txt

@UlrichEckhardt thanks a lot for bringing this issue up. Would you mind opening a pull request with the proposed changes? That would provide a better way to review and discuss the changes.

Okay, the first PR had a failure in a test (the test itself seems to have failed, not the tested code), but now it should be ready. Any questions left, @sagikazarmark ?

Fixed in #505

authors: UlrichEckhardt sagikazarmark

repo: moneyphp/money


text:
CLOUDP-185801: ServerlessMetricThreshold normalization

Adjusting ServerlessMetricThreshold object to not recognize types. We are missing some details in the discriminator and the API which fails in response parsing.

FYI @SanyaLuc

Looks like it: https://github.com/search?q=repo%3Amongodb%2Fatlas-sdk-go GetMetricThreshold&type=code

repo: mongodb/atlas-sdk-go


text:
CLOUDP-70032: mongocli atlas integration(s) create|update NEW_RELIC

Proposed changes

Jira ticket: CLOUDP-70032

Checklist

[x] I have signed the MongoDB CLA
[x] I have added tests that prove my fix is effective or that my feature works
[x] I have added any necessary documentation (if appropriate)
[x] I have run make fmt and formatted my code

Further comments

./bin/mongocli atlas integrations create NEW_RELIC --accountId 2857403 --licenceKey XXXXXXXXXXXX --readToken NRIQ-XXXXXXXXX --writeToken NRII-zpwCnhrDyUojdSJOk2LXXXXXXXXX -o json
{
  "links": [
    {
      "rel": "self",
      "href": "https://cloud-dev.mongodb.com/api/atlas/v1.0/groups/5e4e593f70dfbf1010295836/integrations/NEW_RELIC?pageNum=1\u0026itemsPerPage=100"
    }
  ],
  "results": [
    {
      "type": "NEW_RELIC",
      "licenseKey": "eu01xx5f87268ff5028e69a6XXXXXXXXX",
      "accountId": "2857403",
      "writeToken": "NRII-zpwCnhrDyUojdSJOk2LDvtTXXXXXXX",
      "readToken": "NRIQ-MHCu7bPq2xvrrpVvybXXXXXXXX"
    }
  ],
  "totalCount": 1
}

./bin/mongocli atlas integrations create NEW_RELIC --accountId 2857403 --licenceKey eu01xx5f87268ff5028e69aXXXXXX --readToken NRIQ-MHCu7bPq2xvrrpVvybtXXXXXXX --writeToken NRII-zpwCnhrDyUojdSJOk2LDXXXXXXXXXX
New Relic integration created.

@gssbzn ready for review

repo: mongodb/mongocli


text:
MongoDB Morphia elemMatch API

Hi,
I posted the question on stackoverflow, but I'm pasting the question here also:
http://stackoverflow.com/questions/30978668/mongodb-morphia-elemmatch-api/30982707?noredirect=1#comment49997944_30982707
I'm trying to put this into morphia query :
db.woot.find({
"bar.tables": {
$elemMatch: {
"tableId": {
$in: [3,
4]
},
"tab": {
$gte: 20000
}
}
}
})
So I have :
Query q
q.field("bar.table").hasThisElement()
And after this I don't know how to finish the query and still using FieldEnd which supports in(), gte() methods without writing whole query myself with BasicDBObjects.
Please help me transform above query to the nicest possible Morphia equivalent.
bar.tables is an array so matching must be done with elemMatch or else it can match first condition from some element and the second condition from the other element, but only elements matching both conditions are valid.

My next few days are hectic but I'll try to put something together.  I'll answer on SO, though, as the issue tracker here really isn't meant for support questions.

authors: Steinkauz evanchooly

repo: mongodb/morphia


text:
Travis CI builds not running anymore (needs switch to travis-ci.com?)

I've just submitted PR #239 and it seems that Travis CI integrations is broken. The Travis CI link:
https://travis-ci.org/github/mongoid/mongoid-rspec/requests
has a warning saying  Since June 15th, 2021, the building on travis-ci.org is ceased. Please use travis-ci.com from now on.. Seems like the repo should be switched over to travis-ci.com.

I've tried to migrate this repo to .com like I did for other repos but failed. The travis ui keeps telling me to sign up for some kind of beta (I did), all the repos to migrate are greyed out, etc.
I suggest doing the work to move to GHA and calling it a day. I can help review PRs.

Push a badge CR maybe that changes the badge location to .com, let's see if it picks up?

@dblock thanks for hopping onto this quickly. Almost there, the PR #241 was picked up by Travis CI, but the build failed with " Could not authorize build request for mongoid/mongoid-rspec. "

Where do you see that error? Push again? https://app.travis-ci.com/github/mongoid/mongoid-rspec looks ok to me, but it didn't run anything new.

I've just force-pushed again #241 but it doesn't seem to be triggering Travis CI. I can see the same error again here: https://app.travis-ci.com/github/mongoid/mongoid-rspec/requests

authors: dblock knovoselic

repo: mongoid/mongoid-rspec


text:
The Great Big Spec Refactor

All specs need to be brought up to date to the documented pattern.

All instance variable declarations should be removed in favor of let and let!.
Make sure there is only a single assertion for each example block.
Replace all specific instantiation of the class under test to described_class.
Ensure proper locations of tests to the class under test in spec/functional.
Ensure exactly 1 unit and functional test for each class/module in the framework.
Ensure no order dependency when running the entire suite (depends on connection pool)
Change all instances of should == obj to should eq(obj) to get rid of the ruby -d warnings.

This will need to follow when all pull requests are in not to screw people on conflicts.

:%s/\(should == \)\(.*\)/should eq(\2)/g

repo: mongoid/mongoid


text:
#remove_attribute doesn't remove attribute

If I #remove_attribute, I expect that attribute to be gone. Its value should not be nil; rather, the key should be removed. What I am seeing is that the value is simply set to nil, rather than the key being removed.
In particular, this issue relates to models with a #field for that particular key. Rather, the key is set, get, or removed via #read_attribute, #write_attribute, and #remove_attribute.
Here is a failing spec that illustrates the issue.

I also have a use case where I want to unset seven fields at once on one model.  Sounds like I'd currently have to go down to the driver level to do that or make seven round trips to the DB.
But it sounds like this is a pain to fix without support in ActiveModel::Dirty.  I added my +1 to rails-3137.

@canavese, just for reference:
my_model_instance.class.collection.update(
  { "_id" => my_model_instance.id },
  { "$unset" => { "field1" => true, "field2" => true, "field3" => true } }
)

Yep, I know how to do it with the driver, but it's obviously less than ideal.  And then you'd have to reload the model from the DB if you want it to be consistent.

Nice!

authors: canavese yfeldblum


text:
Which is the latest version of mongo compatible with mongo_mapper?

Hi, I have an old app using mongo_mapper and now I want to move DB host ... which is the latest version supported by mongo_mapper ?
Thank you for your answers

Mongo 3.0. Mongo 3.2 is not, as it doesn't support the Ruby 1.x driver. Note that for Mongo 3, you need the Ruby Mongo 1.2.x driver, which has some set-up requirements with MongoMapper. The email list had some discussion on this.

authors: jamieorc solisoft

repo: mongomapper/mongomapper


text:
SCOPE_MODE and EMIT_MODE

What is the difference between SCOPE_MODE and EMIT_MODE ? When I need to use it ?
I see my unit test failing on .apply telling me object is undefined. Maybe it's link to that ?

Can you please provide more detailed code samples?

repo: mongoosejs/mongoose-async-hooks


text:
alternative test scenario

This adds another test scenario with alternative settings and cleans up default scenario.
Default scenario runs role with variables set to values as close as possible to ones from defaults/main.yml.
Alternative scenario should overwrite as many variables as possible.
This is a continuation of work started in #49 and mentioned in #46.

lgtm

authors: mongrelion paulfantom

repo: mongrelion/ansible-role-docker


text:
Add ability to customize ObjC bindings names via attributes or xml

An initial stab was taken here:
https://github.com/mono/Embeddinator-4000/pull/366

let's make an RFC and consider all platforms and languages

Agreed. I was just closing the ancient PR and made the issue to not forget the work.

#481 is an older duplicate

authors: chamons spouliot


text:
[objc] Use SourceWriter from *Helper classes

Mostly remove tabulations from Write[Line] calls.

Build and tests passed.

authors: monojenkins spouliot


text:
Config changes to reflect the default branch from master to main. Please merge to complete the default branch renaming job.

Auto branch renaming content.

The build was broken prior to this commit, so I will merge it since we want the CI to continue to work!

repo: mono/SkiaSharp-API-docs