text:
ElementProxy is missing in the docs

The ElementProxy class does have a doc string but is missing in the API documentation.
You can find just the sourcecode.
https://python-docx.readthedocs.io/en/latest/_modules/docx/shared.html?highlight=elementproxy

Hmm, yes, so it is. I assume I did that because it's subclassed by so many objects and its couple of methods should show through on them. What was interesting about it from your perspective? Like why did you want to know more about it? It's strictly a base class.
I'm happy to consider giving it a more prominent position, but it's not really intended to be used directly, so I expect that's the main reason I didn't include it directly. In fact I expect I had to explicitly exclude it.

authors: buhtz scanny

repo: python-openxml/python-docx


text:
Accessing adjacent properties of different types in Document object

The situation I am at right now is that I want to locate a table which the content should be instructed by a paragraph right above it. In another word I should be given a string that appears in a paragraph and is expected to get a reference of the table right below it. In the docs both tables and paragraphs are block items but Document objects don't have a "blocks" property, and we don't have a "BlockItem" interface. Is there any way to work around?

I think I am in the same page and don't know how to work it out. My objective is to be able to read "line by line" and interact with it, it being a paragraph or a table. This is so because they are directly related and being able to read both, one after each other is key.
I can iterate through the Doc with say, for loops, on tables or on paragraphs but they are incompatible with each other meaning the for loop will ignore the counterpart.
Anyone has any idea on that?
W

Search this issues list on iter_block_items.
Especially this one: #40.

source: gharchive/issue

authors: injune16 scanny willem-tee

license: mit

license_type: permissive

license_source: bigquery


text:
add environment.yml

add conda-env sphinx, Closes #17

Looks great, I'll leave it open for a while, so the rest of people can have a look, understand it, add comments or whatever.
Thanks for this!

Thanks @dujm

source: gharchive/pull-request

authors: datapythonista dujm

repo: python-sprints/pandas-mentoring

license_source: github-api


text:
Allow parallel run of commands

all execute methods can be started in parallel
if required - use lock attribute

Change execute_async signature and use typed NamedTuple.
Types are exported for typing purposes only.

Pull Request Test Coverage Report for Build 230

46 of 48 (95.83%)  changed or added relevant lines in 4 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage decreased (-0.2%) to 99.397%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

exec_helpers/_ssh_client_base.py
20
21
95.24%

exec_helpers/subprocess_runner.py
17
18
94.44%

Totals

Change from base Build 229:
-0.2%

Covered Lines:
989

Relevant Lines:
995

💛  - Coveralls

authors: coveralls penguinolog

repo: python-useful-helpers/exec-helpers


text:
Script freezes on await coroutine cancelled by wait_for if this coroutine contains any await inside it's CancelledError handling

import asyncio

async def some_func():
    try:
        await asyncio.sleep(2)
    except asyncio.CancelledError:
        # await asyncio.sleep(1)
        print('cancelled')

async def main():
    coro = some_func()
    try:
        await asyncio.wait_for(coro, timeout=1)
    except asyncio.TimeoutError:
        await coro
        print('timeout')

if __name__ == "__main__":
    loop = asyncio.get_event_loop()
    loop.run_until_complete(main())

Output as expected:
cancelled
timeout

But if you uncomment line inside some_func script will freeze (without printing). It can be avoided if we will use task instead of coroutine. But behavior with coroutine seems to be unclear: why everything works if line is commented and just freezes (without any error) if line is uncommented? If coroutine can't be awaited in this case shouldn't we get exception if we try to awaite it?
Windows 10, Python 3.5.0

I'm looking into this. I suspect it's something deep inside Task._step()... Not sure how easy it'll be to track it down.

So here's the problem (as you already indicated). The call await_for(coro, timeout=1) constructs a Task to wrap coro. But two lines below, when the wait_for() has timed out, the code uses await coro. I still have to dig deeper, but it appears that somehow the Task created by await_for() gets woken up when some_func() awaits the second sleep() call (the one commented out in the working version). IOW some_func() does catch the CancelledError but then await instantly gets cancelled again.
At this point my brain hurts and I still haven't quite figured out the complete sequence of events, nor an idea of how to fix it (if we can even fix it). I've got the feeling it's similar to the scenario warned against in the docstring for run_until_complete() -- two tasks wrapping the same coroutine.
Anyway, congrats on discovering this!

I think I know what's going on here:
import asyncio

async def some_func():
    try:
        await asyncio.sleep(2)
    except asyncio.CancelledError:
        await asyncio.sleep(1)
        print('cancelled')

async def main():
    coro = some_func()
    try:
        await asyncio.wait_for(coro, timeout=1)
    except asyncio.TimeoutError:
        await coro
        print('timeout')

if __name__ == "__main__":
    loop = asyncio.get_event_loop()
    loop.run_until_complete(main())

wait_for, creates a Task (T1) for coro.

coro, creates asyncio.sleep(2) coroutine, which creates a Future (F1) and waits on it (in F1.__iter__'s yield self)

wait_for, after 1 second, timeouts and cancels T1.

T1, in its cancel method, cancels F1, which schedules T1._wakeup with a CancelledError.

wait_for raises TimeoutError, which is caught by main().

main() awaits on coro, which causes Python eval loop to call coro.__iter__().__next__()

None is pushed to coro, which really pushes None to F1!

F1.__iter__ generator, calls F1.result(), which raises CancelledError (important: keep in mind step # 4!!!)

CancelledError propagates in coro (instance of some_func), and advances the coroutine to execute await asyncio.sleep(1) (F2).

asyncio event loop runs again, and T1._wakeup scheduled in step # 4 actually happens. And cancels the wrong future.

coro is now in an inconsistent state -- it will never be waken up by F2.

Now, what should we do?  One option, would be to enhance CoroWrapper (wraps all coroutines in debug mode) to prohibit awaiting on a coroutine more than one time.  Thoughts?

I've updated my previous comment with a bit more accurate description of what's going on.

Thanks! Async code never ceases to amaze. I think your analysis matches my own observations. A crucial step seems to be (7), which is fundamental to how yield from (and now await) works, but also hard to grok.
Regarding your proposed solution, I don't disagree, but how can you tell that a coroutine object is being awaited? I guess you're thinking of just instrumenting the calls to CoroWrapper? Given that we don't want to add overhead to the CPython interpreter that's the only thing we can do.
Let's not try to fix this for 3.5.1 though. It's pretty uncommon and the workaround is easy (just wrap the offending coroutine in a Task, or don't use this pattern -- I'm guessing it occurs most likely in code written by new asyncio users who are still trying to figure out how things fit together).

Regarding your proposed solution, I don't disagree, but how can you tell that a coroutine object is being awaited? I guess you're thinking of just instrumenting the calls to CoroWrapper?

Yes, we can use the newly added coroutine.cr_await for this purpose. See PR #293.

Given that we don't want to add overhead to the CPython interpreter that's the only thing we can do.

Actually, we can add this check to the CPython directly. gen_yf is a fairly fast call, and YIELD_FROM opcode is easy to modify to check if the coroutine is being awaited already (we can target specifically coroutines, and leave generators as is).

Let's not try to fix this for 3.5.1 though.

Up to you. The PR is fairly small, and shouldn't affect anything.

That wouldn't do anything for Python 3.3 or 3.4. But maybe that's okay.
Let's see that PR...
On Wed, Nov 18, 2015 at 9:19 AM, Yury Selivanov notifications@github.com
wrote:

Regarding your proposed solution, I don't disagree, but how can you tell
that a coroutine object is being awaited? I guess you're thinking of just
instrumenting the calls to CoroWrapper?
Yes, we can use the newly added coroutine.cr_await for this purpose. See
PR #293 https://github.com/python/asyncio/pull/293.
Given that we don't want to add overhead to the CPython interpreter that's
the only thing we can do.
Actually, we can add this check to the CPython directly. gen_yf is a
fairly fast call, and YIELD_FROM opcode is easy to modify to check if the
coroutine is being awaited already (we can target specifically coroutines,
and leave generators as is).
Let's not try to fix this for 3.5.1 though.
Up to you. The PR is fairly small, and shouldn't affect anything.
—
Reply to this email directly or view it on GitHub
https://github.com/python/asyncio/issues/288#issuecomment-157785010.

--
--Guido van Rossum (python.org/~guido)

That wouldn't do anything for Python 3.3 or 3.4. But maybe that's okay.

That wouldn't do anything for Python 3.3 or 3.4. But maybe that's okay.

Yes.  We can probably hack something in CoroWrapper for 3.3 and 3.4, but even if that's possible, it would be fragile.

@germn PR #293 has been merged. Starting with 3.5.1, in debug mode, your code would crash instead of freezing.

authors: 1st1 germn gvanrossum

repo: python/asyncio


text:
Allow triggering unstable buildbots with the !buildbot PR comment

this came up several times recently around testing the NoGIL build on PRs - it's currently not possible to do that using the !buildbot nogil comment (example attempt) because the nogil builders are marked as unstable.
considering the NoGIL build is "experimental", keeping these builders as "unstable" is probably a good idea, but then we need some way to be able to request these builders on PRs.
after chatting with @ambv, I propose that we extend the !buildbot command to support unstable builders.
the mechanics can be discussed in this issue. here are the options I am considering:

easy but changes existing behavior: include unstable buildbots by default
also easy but kinda hacky: include unstable buildbots if they have a certain tag (e.g. "trigger-on-pr-command")
introduce new spelling for explicitly allowing unstable builders (e.g. !buildbot_with_unstable ... or !buildbot[unstable] or !buildbot ... #with_unstable - bikeshedding welcome)

An alternative is to promote the buildbot to stable.

https://buildbot.python.org/all/#/builders/1241 : multiple builds succeeded in a row, I would be ok to mark it as STABLE. We can downgrade it to UNSTABLE if it becomes unstable again.
https://buildbot.python.org/all/#/builders/1225 most builds are success, same.

Do you want to propose a PR to make them STABLE?

I'm fine with changing these to STABLE, and happy to send a PR to make that change!
I was under the impression that marking a builder as STABLE has broader implications that are not appropriate for an experimental and optional build mode (not sure what my impression was based on, other than my own interpretation of the word "stable" :) )

You're correct, Itamar. Stable buildbots are special for release managers, so at least until the PEP is officially approved, I'd wait with marking nogil BBs as stable.
I believe that the limitation to only allow running stable buildbots with "!buildbot" is unnecessary.

Oh wait, I was confused about the definition of "stable" here.
For me, unstable means "is known to fail", and stable "is known to be reliable. Don't we have tiers to decide if a builder blocks a released or not? For example, Tier 3 failures do not block a release: https://peps.python.org/pep-0011/#tier-3

I read the Working with buildbots devguide page again, and it mentions stability in two places:

In this section it mentions only stable buildbots will post a message to PRs that break them (makes sense, I wouldn't want to extend this to unstable buildbots)
In the section conveniently named "Stability" it mentions stable buildbots are the ones taken into account when making releases

I agree with @vstinner that the semantics of stability vs tiers is confusing. If I combine the devguide with PEP-11, then only TIER_1 and TIER_2 builders can be STABLE, but in practice I see many TIER_3 and NO_TIER builders that are also considered STABLE.
Maybe further clarification is needed. In the meantime, I propose gh-420 to add the unstable builders only to those that can be manually triggered on PRs (@ambv's suggestion above).

Thanks @vstinner! Should we do gh-420 too? or change to NoGIL builders to stable?

with GH-436 the triggering is finally working correctly. we're still not getting the status from unstable builders reported to GitHub Status thingie - this should be fixed with GH-437 (and get this issue resolved finally :) )

looks good on test PR https://github.com/python/cpython/pull/111583 !
correct builders were triggered and their status is visible on GitHub checks

authors: ambv itamaro vstinner

repo: python/buildmaster-config

license: MIT


text:
[BugFix] Allowing for auto-nested tensordict

Description
Blocked self nested behaviour during repr or any other recursive calls.
Motivation and Context
Why is this change required? What problem does it solve?
If it fixes an open issue, please link to the issue here.
[BUG] Auto-nested tensordict bugs #106
Types of changes
What types of changes does your code introduce? Remove all that do not apply:
Bug fix (non-breaking change which fixes an issue)
Checklist
Go over all the following points, and put an x in all the boxes that apply.
If you are unsure about any of these, don't hesitate to ask. We are here to help!

[x] I have read the CONTRIBUTION guide (required)
[ ] My change requires a change to the documentation.
[x] I have updated the tests accordingly (required for a bug fix or a new feature).
[ ] I have updated the documentation accordingly.

This is looking good, thanks for working on it!
I've left a few comments inline.
The other main thing that we should add are some tests. We can add a couple of tests for specific functionality such as checking for the presence of "Auto-nested" in the repr, but as @vmoens suggested in #106 it would be nice to run all tests on a tensordict with autonesting and check that we haven't inadvertently broken something.
Check this class that gets used in the tests, you can add a method for auto_nested_td or similar, and then add it to the tests here. In principle it should work for anything that nested_td works for, but in any case it will be interesting to see what breaks!

I added "Auto-nested" as you recommended, but because of nature. of auto-nesting I think we can't test it using existing test cases. For instance we have this test:
 def test_items_values_keys(self, td_name, device):
        torch.manual_seed(1)
        td = getattr(self, td_name)(device)
        keys = list(td.keys())
        values = list(td.values())
        items = list(td.items())

        # Test td.items()
        constructed_td1 = TensorDict({}, batch_size=td.shape)
        for key, value in items:
            constructed_td1.set(key, value)

>       assert (td == constructed_td1).all()

if we use this td:
 def auto_nested_td(self, device):
        tensordict = TensorDict({
            "a": torch.randn(4, 3, 2, 1, 5),
            "b": torch.randn(4, 3, 2, 1, 10),
            },
            batch_size=[4, 3, 2, 1],
            device=device,)
        tensordict["self"] = tensordict
        return tensordict

when we construct constructed_td1 properly, because out self property contains our "main" td. and when we copy it to  constructed_td1.self property it's not the same as we put constructed_td1['self'] = constructed_td1. More over when we try to compare them, out eq function will try to do deep comparation. It mean we are not able to compare td with self nested key.
I don't know what to do in this case we can discuss it or omit it in this iteration because we need to have a strategy about working with auto(or self) nesting.

After https://github.com/pytorch-labs/tensordict/pull/121, It became easier to solve this auto-nesting bug. I updated pull request. But it still has a problem to add tests which I mentioned here https://github.com/pytorch-labs/tensordict/pull/119#issuecomment-1362954669

Regarding the tests, I'm happy with tests being independent of the others although I wonder if the fact that a call to __eq__ is prohibited should not be addressed by this PR. TBH I did not quite get what the issue was. Can you elaborate a bit more? You can also code it and push the code with the tests breaking, that would give me some visibility on what's happening.

This issue was about infinite recursion during print, flatten_keys, and list(keys()). Issue # https://github.com/pytorch-labs/tensordict/issues/106. This is example of code how to verify this PR:

Code
tensordict = TensorDict({
     "key 1": torch.ones(3, 4, 5),
     "key 2": torch.zeros(3, 4, 5, dtype=torch.bool),
}, batch_size=[3, 4])

tensordict2 = TensorDict({
    "super key 1": torch.ones(3, 4, 6),
    "super key 2": torch.zeros(3, 4, 7, dtype=torch.bool),
}, batch_size=[3, 4])

tensordict["innerTD"] = tensordict2
tensordict2["self 2"] = tensordict2
tensordict["self"] = tensordict
tensordict["key 3"] = torch.zeros(3, 4, 7, dtype=torch.bool)

f_keys = tensordict.flatten_keys()  # Ok
print(f_keys)
td_list = list(tensordict.keys(include_nested=True))  # Ok
print(td_list)
print(tensordict)  # Ok

Thanks
If you could write some tests it would be easier to comment by using the fit review process

@vmoens I've added tests for keys() and repr(). Unfortunately, I didn't handle to add tests for flatten_keys in current test_flatten_keys for several reasons. 1) We can't just add
@pytest.mark.parametrize(
    "td_name",
    [...,
    auto_nested_td,
    ]
)

because there are many other tests which will be broken.
2) I tried to add test_flatten_keys(self, td_name, device, inplace, separator) with auto nested td only, but faced with infinite recursive unlocking of self nested tensordict which doesn't related to flatten_keys problem https://github.com/pytorch-labs/tensordict/blob/455b64adc16833567f45d917d40e4abf3b0a898c/test/test_tensordict.py#L1716

We can broke the tests, I'd rather have that and solve the bug. Otherwise it's hard to see what the problem is.

We can break the tests, I'd rather have that and solve the bug. Otherwise it's hard to see what the problem is.

I've added auto_nested_td into tests

Some benchmarking first:
On this branch, common_ops:
TensorDict({}, [3, 4]) 0.054020772999999966
TensorDict({'a': a, 'b': b}, [3, 4]) 0.10693320900000014
TensorDict({'a': a, ('b', 'b1'): b}, [3, 4]) 0.26566142599999987
TensorDict({'a': a, 'b': {'b1': b}}, [3, 4]) 0.19251463799999957
tdc = td.clone() 0.23632501300000008
tdc = td.clone();tdc['c'] = c 0.2863006590000001
tdc = td.clone();tdc.set('c', c) 0.2764215059999984
tdc = td.clone();tdc.share_memory_() 1.781234584
tdc = td.clone();tdc.update(td2) 0.41446814300000057
tdc = td.clone();tdc.update(td2) 0.6884915679999999
tdc = td.clone();tdc['b', 'b1'] = b 0.3841283730000029
tdc = td.clone();tdc['c', 'c', 'c'] = c 0.6221515459999978

On main
TensorDict({}, [3, 4]) 0.06562997599999987
TensorDict({'a': a, 'b': b}, [3, 4]) 0.1289677100000004
TensorDict({'a': a, ('b', 'b1'): b}, [3, 4]) 0.29692919799999995
TensorDict({'a': a, 'b': {'b1': b}}, [3, 4]) 0.24163629199999992
tdc = td.clone() 0.26948069800000063
tdc = td.clone();tdc['c'] = c 0.3178999400000002
tdc = td.clone();tdc.set('c', c) 0.3091379649999997
tdc = td.clone();tdc.share_memory_() 1.806307208999998
tdc = td.clone();tdc.update(td2) 0.42458679399999966
tdc = td.clone();tdc.update(td2) 0.6898641609999991
tdc = td.clone();tdc['b', 'b1'] = b 0.4234232099999993
tdc = td.clone();tdc['c', 'c', 'c'] = c 0.6865369579999978

So we're good on that side.
Functional:
instantiation, functorch: 2.3080958469999997
instantiation, tensordict: 1.3075678029999995
exec, functorch: 4.814458004
exec, tensordict: 5.19893972

Other benchmarks seem to be roughly similar.

@Zooll I'm on it. Thanks for your hard work!
I tried to solve the to_tensordict() but it's a hard one. I need to sleep on this because all the solutions I can think of are either completely wrong or way to complex.
I'll keep you posted!

Closing as this has been addressed in #201

authors: Zooll vmoens

repo: pytorch-labs/tensordict


text:
Clean up FP6-LLM

Remove original FP6 quantization code (qtorch and C++ bit-packing)
Replace FP32<->FP6 dtype conversion with @vkuzo's implementation for MX dtypes

I also migrate some of my FP32->FP6 rounding test cases to MX custom cast test.

Replace FP32<->FP6 dtype conversion with @vkuzo's implementation for MX dtypes

I have two questions:

Just curious, have you benchmarked the performance of this change?  I have not optimized the mx types for performance yet.
I think it's not ideal to depend on code in prototype folder, if other people need custom_cast.py it might be good to move it to a common place outside of the prototype folder.

@vkuzo

I did benchmarking. IIRC, your implementation is faster than mine for both CPU and GPU (w/ torch.compile). Will benchmark it again and update the result in this comment. (I also did correctness comparison. Your implementation and mine are bit-identical for all FP16 bit patterns - can't test all FP32 bit patterns because it would take too long)
Yea I want to discuss with you about this also. It will be good to move it to a separate file for low bit-width floating point conversion. The FP6-LLM author added support for FP5 E2M2, so I want to support FP5 also (mx doesn't have FP5).

A question for @msaroufim. Is there a guideline when we should or should not decorate a function with @torch.compile? These functions rely on torch.compile to be fast, but there are cold-start (first time is slow) and dynamic shape (can we avoid re-compile on different shapes, in a guaranteed way?) problems. (haven't looked into the problems too much yet, maybe it is not that significant).

So for Windows the main issue is torch.compile() codegenerates triton kernels which hasn't prioritized Windows support. I think for inductor cpu backend this should be less of an issue, I suspect there might be an overly aggressive assert somewhere though.
I would say overall everything should be compilable, the cold start problems is indeed annoying and is actively being worked, there are some broader plans that have been shared though https://dev-discuss.pytorch.org/t/how-to-bring-compile-time-down-to-zero-our-plans-and-direction-may-14th-edition/2089
Regarding dynamic shapes the way I iterate through things is first eliminate graph breaks then recompilations, this has been my goto guide https://github.com/pytorch/pytorch/blob/main/docs/source/torch.compiler_troubleshooting.rst
Also just FYI we removed the requirement to have branches up to date before merge, there was a breaking change in PyTorch that was just reverted so please rebase your changes to get rid of CI flakes

authors: gau-nernst msaroufim vkuzo

repo: pytorch/ao


text:
Distributed dataparallel implementation of WaveRNN training

Some speed up over the original WaveRNN training example.
Here is a working version on gist.
On a 8 GPU machine, it should be 10 times faster with batch size 256.

Thanks for the proposal! I think another refactoring direction is using PyTorch Lightning template besides the DistributedDataParallel  dataloader. We can put the two refactor way into one PR.

One thing for this gist that I would like to add is that there are some command line arguments that are not well set.
For example, here and here, the default is True and using the argument also sets the variable to True, which is weird and should be fixed during the refactoring.

authors: nateanl yangarbiter

repo: pytorch/audio


text:
Added ability to save tensors

Ported the code from here to save tensors! Should also close #2, let me know if any feedback

Thanks for the feedback @apaszke, made a few changes if you could review again!


text:
A checkpoint should always be triggered when stopping criteria triger

🚀 Feature Request
Currently, when stopping criteria trigger (e.g. --max-updates) a checkpoint is not triggered. This is generally fine, but somewhat surprising if, say, at some point in between two save points, early stopping criteria are triggered. The last point in training should be given a chance at validation and saving.
This can be a dedicated model_last.pt file, for example. Written only when training has decided to end.
Motivation
Allow debugging or continuing training from the actual end point of training.
Pitch
Two possibilities:

Right before terminating training, force an evaluation of the current model as a potential checkpoint candidate.
Always, right before terminating training, save the current model in a dedicated checkpoint file. E.g. model_last.pt.

Alternatives
Not sure.
Additional context
N/A

what makes you think this is the case?
    # Stopping conditions
    max_update = args.max_update or math.inf
    should_stop = (
        should_stop_early(args, valid_losses[0])
        or trainer.get_num_updates() >= max_update
        or (
            args.stop_time_hours > 0
            and trainer.cumulative_training_time() / (60 * 60) > args.stop_time_hours
        )
    )

    # Save checkpoint
    if do_save or should_stop:
        logger.info("begin save checkpoint")
        checkpoint_utils.save_checkpoint(args, trainer, epoch_itr, valid_losses[0])

authors: alexeib narfanar

repo: pytorch/fairseq


text:
misleading definition of mask

Not a bug, but in the torchtune the mask = True to avoid calculating loss on it (see https://github.com/pytorch/torchtune/blob/main/torchtune/datasets/_instruct.py#L102C9-L102C91).
This is quite different from the standard notion of mask in a lot of the popular NLP repos (e.g. Llama, fairseq, hf) where mask = False means not training on that token. It can be extremely misleading to whoever using it.

Thanks for the feedback @jxmsML and thanks for taking a look at the code!
My personal experience has been that the way mask is used in different libraries (and even within different components within the same library) is not very standard. I've seen folks use both mask and ~mask to decide whether a component is 0-ed or not. That said, there are a few places we need to do better:

Document the meaning of mask for every module
Aim to be consistent about how torchtune uses mask across the library

We'll start to address both of these in our upcoming PRs. including the PR @joecummings has on batch inference.

All docstrings related to masks were made more clear in #875. Please re-open this issue if there's still any remaining confusion!

authors: RdoubleA jxmsML kartikayk

repo: pytorch/torchtune


text:
save_image behavior

https://github.com/pytorch/vision/blob/master/torchvision/utils.py#L52
The .mul(0.5).add(0.5) in this line seems to be assuming that the input values are in [-1,1]? Isn't the Torch convention to use [0,1] for images?

Personally, I vote for having a default behavior that assumes a range [0, 1] and doesn't normalize the image.
Doing otherwise would result in issues like the mentioned #41 and potentially introduce bugs difficult to spot (as the normalization is "silent").

This is fixed in master by removing the offset, but definitely having a range parameter would be quite useful!

authors: rtqichen soumith stepelu

repo: pytorch/vision


text:
Improve transforms

Hi there!
At this moment, torchvision is so poor; in particular, transforms. It really restricts our ability for data augmentation. However, people have already done a few nice libraries for it. For instance:
https://github.com/mdbloice/Augmentor (already has compatibility with PyTorch)
https://github.com/aleju/imgaug
What about contact with authors and merged these great jobs to torchvision.transforms?

@fmassa, okay, thanks, it will cool :) Actually, I strongly recommend to look at this libraries instead of write new code, but, of course, you know better :)
By the way, don't forget about segmentation!

Don't worry, I won't forget about instance segmentation :-)

@fmassa sorry for offtop: I would like to notice that first provided library uses excellent way to transform two or more images. All transforms take list of images rather than just one image like transform in torchvision. For example:
def perform_operation(self, images):
#init random values
for image in images:
    augmented_images.append(do(image))
return augmented_images

I suppose it's great idea ^^

It's indeed much simpler in some cases, but also more restrictive in more general setups.
For the record, this is something that has been bugging me for a long time, see https://github.com/pytorch/vision/issues/9 and https://github.com/pytorch/vision/issues/230 for some context.
In many cases, you don't want to pass all transforms to all data (no color augmentation for segmentation masks for example), and the approach you mentioned doesn't easily allows that (without making the API overly complex).

The codes of imaug  is somehow far more complicated.

@nnop yes, I saw imaug and agree that it is very complex. I would rather have a simpler API, even if it requires having to write a bit more code.

authors: Oktai15 fmassa nnop


text:
add headings to weights table.

Related to #6126 and #6131
Here is my attempt.

This creates the following error in the doc build:
Warning, treated as error:
/home/circleci/project/docs/source/models.rst:263:Title level inconsistent:

Table of all available quantized classification weights
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
make: *** [Makefile:42: html] Error 2

I think now the error is gone. Here are the generated tables -

classification
Quantized Classification
Detection
Instance Segmentation
detection keypoint
segmentation
Video

Thanks for the PR @abhi-glitchhg but I think the current solution adds titles below the tables: https://output.circle-artifacts.com/output/job/7b9d5b75-850e-4421-acd7-d4f7b6fa314f/artifacts/0/docs/models.html#classification-weights-table

Thanks @NicolasHug !
I have added the titles at the top; generated tables:-

Classification
Quantized Classification
Detection
Instance Segmentation
Detection Keypoint
segmentation
Video Classification

Also note that i have edited table_name parameter for 2 tables to make titles little more descriptive.
Please have a look and let me know.
Thanks.

I think the problem is just reversed now, the title is above the table but we still have duplicated titles which is redundant:

Any chance we can tell the table to use the first title as its title in the search?

I think I can do that.

I would prefer not to change the current heading levels and keep what we currently have in https://pytorch.org/vision/main/models.html

@NicolasHug True but is this possible? Aka if you add headings aren't those going to automatically be appeared to the heading levels?

Yes, which is why ideally we would find a way to tell the table to just use its section title as title https://github.com/pytorch/vision/pull/6139#issuecomment-1153848536
This way we don't have to add another heading level.

I would prefer not to change the current heading levels and keep what we currently have in https://pytorch.org/vision/main/models.html

Thanks! Then I think I am done, please check the docs and let me know.

@abhi-glitchhg Push!!! :)

@abhi-glitchhg I am very sorry that none of our team got back to you. Many of us had our annual leaves this period and your PR fell through the cracks. :( Let me ping Nicolas tomorrow internally and try to get you some feedback.

No problem at all. I know how busy you all must be and it's very much
possible that somethings might get unnoticed.
I appreciate your support!
Thanks 🙏.
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period and your PR fell through the cracks. :( Let me ping Nicolas tomorrow
internally and try to get you some feedback.
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@abhi-glitchhg  Thanks for getting me involved. I just went through the PR, and it seems the current problem is that we prefer table context/titles coded in .rst files rather than conf.py. (I agree this as well. Furthermore, it seems strange to me that we call this generate_weights_table method to create tables in conf.py since this file should only contains configurations.)
I think a better idea might be register a new sphinx domain to do this in setup() or create a sphinx extension to parsing the tables? These shall be doable in conf.py without touching theme package. Later we can apply the new domain in .rst files. (The same process as autosummary)
In current architecture, it's a python method rather than a sphinx domain, which forces it to be called in conf.py.

I think a better idea might be to register a new sphinx domain to parse tables in setup()? It shall be doable in conf.py without touching theme package. Later we can apply the new domain in .rst files and pass content-related arguments there. (The same process as autosummary)

Thanks for your insights @ain-soph . I'm happy to refactor our implementation to something more standard / canonical, as long as it's not too complex or overkill. Out of curiosity, do you believe this would solve our "table title in search rendering issue" ?

@NicolasHug
Here is how to set the table title (very simple): https://stackoverflow.com/questions/53191945/how-can-i-add-a-caption-to-a-restructuredtext-table
And for the  shown in the search page, that’s actually because section name of the generated rat page is not set. (Not related to the table directive)
@abhi-glitchhg has already solved that correctly by setting the section name of the generated page.
<section name>
—————————————————————

Ok ill give this one more try!
Thanks a lot, @ain-soph  for the directions!

@abhi-glitchhg  Nah, I think adding the table title won’t help anything. You have already solved the search results in your previous commits.
I think the current issue from maintainers is that: those content-related texts are put into conf.py, which violates the initial purpose of this file.
My suggestion is to implement a new small plugin which contains a new sphinx directive and register it in conf.py. The plug-in will be highly similar to autosummary that preprocess your auto rst files and generate the real table rst files.

oh I misunderstood your previous message. Thanks for pointing it out.

My suggestion is to implement a new small plugin which contains a new sphinx directive and register it in conf.py. The plug-in will be highly similar to autosummary that preprocess your auto rst files and generate the real table rst files.

I do not have much knowledge of implementing this, So closing this pr [I promise wont open this pr again :hand_over_mouth: ]
If anyone wants to resolve this, feel free to supersede me. Thanks.

I shall be available to work on this after finishing the issue at https://github.com/pytorch/vision/issues/6224
Maybe 1 month later?

authors: NicolasHug abhi-glitchhg ain-soph datumbox


text:
Taskbar and UIA MenuWrapper small refactorings

taskbar: fix issue #294 - get the non-English notification area toolbar
TaskbarTestCases: verify type_keys in _toggle_notification_area_icons
UIA: refactor MenuWrapper
MenuWrapperNotepadTests: remove extensive traces

Codecov Report

Merging #308 into master will decrease coverage by -0.03%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master     #308      +/-   ##
==========================================
- Coverage   94.46%   94.44%   -0.03%
==========================================
  Files          49       49
  Lines       19520    19521       +1
==========================================
- Hits        18440    18437       -3
- Misses       1080     1084       +4

Continue to review full report at Codecov.

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authors: airelil codecov-io

repo: pywinauto/pywinauto


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text:
zafira jenkins integration should use fqdn root_url

we have to reuse actual fqdn jenkins root_url to integrate it with jenkins otherwise client browser->jenkins reruns/build now etc don't work

https://github.com/qaprosoft/qps-infra/commit/e21e03d2b1757d1bb5c29b45071d3712bf7a96a0
in .env.oriinal updated definition of root url from:
ROOT_URL=http://${INFRA_HOST}/jenkins
to:
ROOT_URL=http://demo.qaprosoft.com/jenkins
as result after setup.sh it should substituted by actual fqdn or ip address

repo: qaprosoft/qps-infra


text:
播放歌曲无法暂停

尽量每个 issue 只提一个 bug 或新功能
提新 issue 前请确认 👉

没人提过这个 issue（这里看所有 issue）
项目的 Todo 里没有与你 issue 相关的内容（这里看 Todo）

反馈 bug 需要的信息

用的是网页版还是客户端
浏览器名称或电脑操作系统
控制台 Console 页面的截图（按 F12 可打开控制台）

請重設 App。
要重設 App，請在 Console 輸入 resetApp() 然後 Enter。


text:
ENH: API Docstrings

WORK IN PROGRESS. @ebolyen & @nbokulich, feel free to push docstrings to this branch.

This can be reviewed whenever - I have been building the development builds of the dev-docs against this PR, btw.


text:
集群连接

操作系统OS
Mac
应用版本
1.2.1
问题描述
请问如何连接redis集群，单节点环境下可以连接

暂不支持

能提到开发计划中么。。
集群连接相比于单节点，有什么技术难点么？

底层连接组件不支持，需要手动开发redirect逻辑 :crying_cat_face: 改动较大
后续看看有没有直接支持集群的底层组件，有的话直接换上

底层redis连接组件用的什么?
不太熟悉vue代码，熟java，有没有什么我能帮得上忙的。
mac下好用的redis客户端工具确实很难得呀。

哈哈，谢谢支持
底层用的node_redis，再底层是hiredis

@dale19900108  试了试另一个支持cluster的组件，感觉最终效果并没有啥区别
1、由于cluster无法遍历所有key，所以左侧key list显示的还是当前node的所有key
2、不过cli console里面执行命令可以跨node执行命令，get set功能正常
所以你的需求点是什么，如果目前实现的cluster功能是上面的1\2，能够满足常规需求

遇到的问题是这样，
1、set了一个key之后，因为是集群环境，可能key落到了其他节点，无法在左侧列表显示。
2、同上，模糊查询的时候，因为无法显示全部的key

由于2的限制，左侧列表只能同时显示一个node的所有key，并不能展示集群的所有key，包括模糊匹配的时候。
而大部分需要集群支持的呼声中可能都是想要key列表是全集群key，所以即使实现集群功能，也不能很好的支持左侧列表

对的 ，根据模糊查询get全部的key，这个是最主要的场景了。
而且，在使用过程中，对于key存在哪个节点上，应该关心的人不多吧？
公司集群有6个节点，查询一个key，要去点6次，就有点麻烦了。
对于2的限制，感觉很奇怪哦 ，支持cluster集群连接，为什么还只能显示当前node的key呢？

你可以认为底层存储了n个真实node的链接，当节点返回redirect跳转的时候，他会自动找到目标链接重新查询。所以本质上还是链接到一个node，也只能查询当前node的所有key
一个笨方法是找到所有节点链接，依次遍历获取后再合并，搜索时同理，但这样性能太差，这也是一般redis客户端也不支持显示集群所有key的原因

Redis官网上说，ioredis是支持集群的，刚才到github上看了下ioredis的介绍，，试试这个？
我感觉，redirect这种情况，应该是由组件封装好的才对。

我试的就是ioredis
直接get是没问题的啊，所以上面我说cli里get能够跨节点取到数据，但是获取所有key还是单节点，这个不能获取集群全部key

repo: qishibo/AnotherRedisDesktopManager


text:
Fermi-Hubbard Model block/interleaved inconsistency

Environment

Qiskit Nature version: 343d2901
Python version: 3.9.16
Operating system: RHEL 8.8

What is happening?
Since the introduction of InterleavedQubitMapper (#1046) the FermiHubbardModel class doesn't behave consistently with this feature, producing an interleaved-encoded hamiltonian when used together with JordanWignerMapper, and a block-encoded hamiltonian when used together with InterleavedQubitMapper.
How can we reproduce the issue?

>>> from qiskit_nature import settings
>>> from qiskit_nature.second_q.hamiltonians import FermiHubbardModel
>>> from qiskit_nature.second_q.hamiltonians.lattices import LineLattice
>>> from qiskit_nature.second_q.mappers import JordanWignerMapper, InterleavedQubitMapper
>>> settings.use_pauli_sum_op = False

>>> lattice = LineLattice(2)
>>> model = FermiHubbardModel(
    lattice.uniform_parameters(
        uniform_interaction=-1.,
        uniform_onsite_potential=0.
    ),
    onsite_interaction=1.
)
>>> hamiltonian = model.second_q_op().simplify()
>>> print(hamiltonian)

FermionicOp({'+_0 -_2': (-1+0j), '-_0 +_2': (1+0j), '+_1 -_3': (-1+0j), '-_1 +_3': (1+0j), '+_0 -_0 +_1 -_1': (1+0j), '+_2 -_2 +_3 -_3': (1+0j)}, num_spin_orbitals=4, )

>>> mapper = JordanWignerMapper()
>>> print(mapper.map(hamiltonian)) # Block encoding

SparsePauliOp(['IYZY', 'IXZX', 'YZYI', 'XZXI', 'IIII', 'IIZI', 'IIIZ', 'IIZZ', 'ZIII', 'IZII', 'ZZII'],
              coeffs=[-0.5 +0.j, -0.5 +0.j, -0.5 +0.j, -0.5 +0.j,  0.5 +0.j, -0.25+0.j,
 -0.25+0.j,  0.25+0.j, -0.25+0.j, -0.25+0.j,  0.25+0.j])

>>> interleaved_mapper = InterleavedQubitMapper(mapper)
>>> print(interleaved_mapper.map(hamiltonian)) # Interleaved encoding

SparsePauliOp(['IIYY', 'IIXX', 'YYII', 'XXII', 'IIII', 'IZII', 'IIIZ', 'IZIZ', 'ZIII', 'IIZI', 'ZIZI'],
              coeffs=[-0.5 +0.j, -0.5 +0.j, -0.5 +0.j, -0.5 +0.j,  0.5 +0.j, -0.25+0.j,
 -0.25+0.j,  0.25+0.j, -0.25+0.j, -0.25+0.j,  0.25+0.j])

What should happen?
For consistency with the other uses of JordanWignerMapper and InterleavedQubitMapper, the outcomes of the prints should be:
>>> hamiltonian = model.second_q_op().simplify()
>>> print(hamiltonian)

FermionicOp({'+_0 -_1': (-1+0j), '-_0 +_1': (1+0j), '+_2 -_3': (-1+0j), '-_2 +_3': (1+0j), '+_0 -_0 +_2 -_2': (1+0j), '+_1 -_1 +_3 -_3': (1+0j)}, num_spin_orbitals=4, )

>>> mapper = JordanWignerMapper()
>>> print(mapper.map(hamiltonian)) # Block encoding

SparsePauliOp(['IIYY', 'IIXX', 'YYII', 'XXII', 'IIII', 'IZII', 'IIIZ', 'IZIZ', 'ZIII', 'IIZI', 'ZIZI'],
              coeffs=[-0.5 +0.j, -0.5 +0.j, -0.5 +0.j, -0.5 +0.j,  0.5 +0.j, -0.25+0.j,
 -0.25+0.j,  0.25+0.j, -0.25+0.j, -0.25+0.j,  0.25+0.j])

>>> interleaved_mapper = InterleavedQubitMapper(mapper)
>>> print(interleaved_mapper.map(hamiltonian)) # Interleaved encoding

SparsePauliOp(['IYZY', 'IXZX', 'YZYI', 'XZXI', 'IIII', 'IIZI', 'IIIZ', 'IIZZ', 'ZIII', 'IZII', 'ZZII'],
              coeffs=[-0.5 +0.j, -0.5 +0.j, -0.5 +0.j, -0.5 +0.j,  0.5 +0.j, -0.25+0.j,
 -0.25+0.j,  0.25+0.j, -0.25+0.j, -0.25+0.j,  0.25+0.j])

Any suggestions?
In qiskit_nature/second_q/hamiltonians/fermi_hubbard_model.py, change the "index" variables everywhere from index = 2 * node + spin to index = node + spin * num_nodes. I am happy to open a PR with this change!

I think unifying the behavior of the FermiHubbardModel with the block-ordering of the ElectronicEnergy class is a good idea! Please go ahead and open a PR as you had suggested :slightly_smiling_face:

authors: ialsina mrossinek

repo: qiskit-community/qiskit-nature


text:
Test Issue - fljuw

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repo: qlikqaa/dummyrepo


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text:
More control over boot script injection

If you've built for variants or deal with certain broken browsers, you want to control how (or which) script is injected into the template boot/index.html.
Currently there's no way to i.e. load the script via boot.js?42 to trick a broken caching mechanism. Or even load a variant boot-webkit.js instead. Where the variant type is detected via JS on load time.

@johnspackman Does this still hold true? If yes, @cajus, is it still a relevant problem for you or one that can be addressed later?

This is solved in that the source/boot/index.html can be used to provide a custom index.html; that .html file could (for example) inject it's own <script> tag to load boot.js, and so can add boot.js?1234 or perform any other kind of dynamic changes.

authors: cajus cboulanger johnspackman

repo: qooxdoo/qooxdoo-compiler


text:
allow data driven portals to have custom particles [suggestion]

immersive nether portals have those portal particles around them obviously, but personally i think this means that data driven portals should also be able to have their own particles specified in json. thanks for listening to my TED™ talk.

It's being considered

authors: qouteall wouu

repo: qouteall/ImmersivePortalsMod


text:
Consider adding support for Android content:// URIs

First of all, I'd like to commend your work on an incredibly useful plugin. It really has helped address some drastic shortcomings of capacitor file system.
Would you consider supporting content URIs though?
The Filesystem.readfile() method in capacitor is capable of doing so but obviously without the advantage of being able to read in chunks and thus hitting memory limitations.
Our use case is uploading video and with your plugin we were able to create an elegant solution on iOS. Because we are using @capawesome/capacitor-file-picker however, on android we receive content URLs which I believe need resolving first.
If this isn't something you'd consider then is there any other approach you could suggest?

Hello,
Sorry for the late reply, somehow it got lost. Well, it should work as I also use it when receiving shared files on Android. I don't know this plugin. Have you tried converting the path? In the file manager you have this function:
  public async getPath(tPath: string, tDirectory: Directory): Promise<string> {     try {       // CREATE EMPTY FILE       const tResult = await this.mFilesystem.getUri({         path: tPath,         directory: tDirectory,       });       if (tResult.uri) {         return tResult.uri.replace('file://', '');       } else {         return '';       }     } catch (e) {       return '';     }   }
Thanks,

the plugin simply calls this function on Android. I assume you have the correct permissions, and to be safe, please remove all special characters and spaces from the filename just to be sure.
////////////////////////////////////////////////////////////////
// START SERVER
@PluginMethod
public void readFileChunk(PluginCall call) {
    String tPath = call.getString("path");
    Integer tOffset = call.getInt("offset", 0);
    Integer tLength = call.getInt("length", 0);
    JSObject tResponse = new JSObject();

    byte[] tBuffer = new byte[tLength];
    try (RandomAccessFile tRandomAccessFile = new RandomAccessFile(tPath, "r")) {
        tRandomAccessFile.seek(tOffset); // MOVE TO OFFSET
        tRandomAccessFile.read(tBuffer, 0, tLength);
        tResponse.put("data",android.util.Base64.encodeToString(tBuffer, android.util.Base64.NO_WRAP));
        call.resolve(tResponse);
    } catch (IOException e) {
        tResponse.put("data", "");
        call.resolve(tResponse);
    }

}

S

Oddly, what I would do to try to fix the bug would be to play with the Android code part and debug there. You can just edit the plugin code in Android Studio to find the problem and the solution. Depending on that, you may then need a permanent solution. If it's my plugin, I can update the code or you can create your own plugin and you can use mine as a base if you wish.

Hello,
Sorry for the late reply, I've lost track. As soon as I have a little more time, I will check and apply the corrections.
Thanks a lot!

I could also really use the ability to read content: streams under Android. Any update on merging in this enhancement?

authors: Yermo calvin-william-smith qrclip

repo: qrclip/capacitor-file-chunk


text:
🛑 otakusan is down

In 9651ae3, otakusan (https://otakusan.net/LightNovel) was down:

HTTP code: 0
Response time: 0 ms

Resolved: otakusan is back up in 99f440e after 6 minutes.


text:
🛑 otakusan is down

In 3b6c2c0, otakusan (https://otakusan.net/LightNovel) was down:

HTTP code: 0
Response time: 0 ms

Resolved: otakusan is back up in f9ccaf4.


text:
🛑 Xemphim club is down

In 3aa8f77, Xemphim club (https://xemphim.club/) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Xemphim club is back up in d62acef.


text:
🛑 kokocon is down

In a438ec2, kokocon (http://kokocon.net/) was down:

HTTP code: 500
Response time: 119 ms

Resolved: kokocon is back up in 56d1240 after 7 minutes.


text:
🛑 kokocon is down

In 4cbe97a, kokocon (http://kokocon.net/) was down:

HTTP code: 500
Response time: 75 ms

Resolved: kokocon is back up in e54f08a after 8 minutes.


text:
initialized frames are a bit off

is MAXDIM the culprit?  the frames are often too big and I feel they should be smaller

notice the synthetic demo, some of the frames are completely off by at least one border row/col

repo: quantombone/exemplarsvm


text:
MAINT: set FixedBasisPointsSlippage as default

set FixedBasisPointsSlippage as default slippage model

changed the default setting to be in blotter.py, and added params to make equity and future slippage models configurable

@vikram-narayan changes here look good to me, but I think you've still got some real test failures from updating the slippage model.

@ssanderson made the slippage model return None, None if the number of shares to fill is 0. Appveyor is passing, still seeing the weird issue with travis builds

Coverage increased (+0.002%) to 87.547% when pulling c1b731683544dc6ff4d4c375bd7e849bd402d3a4 on change-default-slippage-model into 52826bfa3f02b66b67600c929ce140881e58eb33 on master.

authors: coveralls ssanderson vikram-narayan

repo: quantopian/zipline


text:
Remove SimulationStep/SimulationResult

This would be a big breaking change, so perfectly happy to let it go.
All the simulators use TActOnArgs internally, and now SimulationStepResult/SimulationTrialResult are just wrappers around that object. Those classes served a purpose back when all the simulators were implemented independently, but now they feel like unnecessary layers that obfuscate the code. They're also pretty delicate in that we've gone through great lengths to make sure none of the functions accidentally merge separated states yet retain backwards compatibility.
Instead we could yield/return TActOnArgs (after renaming to TSimulatorState or something more reasonable) directly, and that would allow us to ditch the extra layers. Obviously this would be a huge breaking change. But I figure it's now or never so felt like it should be posted here.
@MichaelBroughton cc @95-martin-orion

From cirq sync:
Discussion: This is a very breaking change. Also, we should gate this on renaming TActOnArgs to something more meaningful.
Conclusion: We probably don't really have time to do this. Maybe reopen some time before 2.0.

authors: daxfohl viathor

repo: quantumlib/Cirq


text:
Dependabot spams git log

Given that Cirq's commit messages are based on PR descriptions, Dependabot's commit messages contain a lot of unnecessary information. See https://github.com/quantumlib/Cirq/commit/8ac690d97c453ca2f1f736fd8956583c9aefd7f8 for example.
This issue will be closed once we find a way to configure Dependabot to trim down it's PR descriptions or automatically do it ourselves.

This appears to be resolved, message sizes got small as of #6209 commit da866e3889a097b08a1800549ec72285d6786bd1.
$ git log --log-size --author=dependabot | egrep -o "(log size.*|.*#[0-9]+[)])"

log size 734
    Bump tar from 6.1.11 to 6.2.1 in /cirq-web/cirq_ts (#6559)
log size 755
    Bump express from 4.18.1 to 4.19.2 in /cirq-web/cirq_ts (#6533)
log size 197
    Bump webpack-dev-middleware from 5.3.3 to 5.3.4 in /cirq-web/cirq_ts (#6524)
log size 753
    Bump follow-redirects from 1.15.4 to 1.15.6 in /cirq-web/cirq_ts (#6501)
log size 735
    Bump black from 23.3.0 to 24.3.0 in /dev_tools/requirements/deps (#6512)
log size 584
    Bump ip from 1.1.5 to 1.1.9 in /cirq-web/cirq_ts (#6470)
log size 753
    Bump follow-redirects from 1.15.2 to 1.15.4 in /cirq-web/cirq_ts (#6407)
log size 192
    Bump @babel/traverse from 7.14.5 to 7.23.2 in /cirq-web/cirq_ts (#6318)
log size 184
    Bump word-wrap from 1.2.3 to 1.2.4 in /cirq-web/cirq_ts (#6209)
log size 10080
    Bump requests from 2.24.0 to 2.31.0 in /dev_tools/pr_monitor (#6104)
log size 11112
    Bump webpack from 5.40.0 to 5.76.0 in /cirq-web/cirq_ts (#6035)
...

authors: pavoljuhas vtomole


text:
s/v1/v2 for metrics proto.

Updated package for metrics.proto from v1 to v2 and re-ran proto compiler on the directory, which updated some of the generated code for other protos as well.

Note: we now have https://github.com/quantumlib/Cirq/blob/master/dev_tools/build-protos.sh for generating protobuf code. That script uses the version of protoc defined in the dev dependencies in the repo, so doesn't depend on protoc being installed on the user's machine, and also updates the mypy stubs. We should probably add a CI check that runs the build script and checks that there are no diffs.

Created #1801 for this

authors: dabacon maffoo wcourtney


text:
Add link to GitHub repository automatically on each extension doc

👆

There's already an indirect version of this capability. If you know to click the 'edit this page' link, you can get to the github repo – but that's obviously dependent on people knowing the trick. :)
This also raises some interesting questions about how much overlap we want between the various sites, such as code.quarkus.io, docs.quarkiverse.io, and extensions.quarkus.io. For example, https://github.com/quarkusio/extensions/issues/251 covers putting part of the docs on the main panel on extensions.quarkus.io, so it's sort of the opposite of this issue; if we did both, the two sites would become very similar.
From an implementation point of view, the overlap is slightly irritating, because it means duplicated code. From a user perspective, however, I can't think of any downside. Well, no downside as long as the 'extra' content doesn't add so much clutter that interferes with the core function of the site. For example, we'd want to carefully limit the amount of information on code.quarkus.io, because otherwise it becomes hard to use for app creation. The other thing we want to be cautious of is having so much overlap that users get confused about why we have several sites and what they should do on each one.
However, I think we will see more convergence between the three/four sites as time goes on.
(And the TLDR of that comment for this request is that I agree we should do it. :) )

I was about to open the same issue, because right now I am using the 'edit this page' link for that and then manually edit the location in the address bar or click on the project name to go back to the github home of the project.
Often I click on the 🏠 icon in the bar (because I am thinking let's go to the github home), and then I regret my click.

--> if there is an option in Antora to hide this button you should do it, since you already have the logo at the top left corner to go to the "Quarkiverse documentation" page.

For me a button (with the github logo or whatever) would be perfect:

And then, maybe it is out-of-scope for this issue, but I think you should make sure (or encourage the maintainer to configure it) that each quarkiverse project that has a guide also sets its guide as github project's website. This way you would have a standard link to the guide:

And then, maybe it is out-of-scope for this issue, but I think you should make sure (or encourage the maintainer to configure it) that each quarkiverse project that has a guide also sets its guide as github project's website. This way you would have a standard link to the guide:

That would definitely be a different issue. @gastaldi, could the terraform scripts and the registry cooperate in some way to do that? I'm thinking get the extension list from the registry, for anything with an scm-url that points to the quarkiverse, update the repo description to include the guide link as the last line?

Thanks, @gastaldi. Could we automate it? So it wasn't done manually? I guess that's probably more effort than it's worth.

Probably once (and if) we automate the creation of the Terraform scripts someday :)

authors: gastaldi holly-cummins ia3andy jmini

repo: quarkiverse/quarkiverse-docs


text:
Update project.yml

Release with support for the new DEV UI.

it is an update to 0.27.3

repo: quarkiverse/quarkus-dashbuilder


text:
NPE with websocket / converstation handling

2024-03-25 08:45:36,336 ERROR [io.und.web.request] (vert.x-eventloop-thread-2) UT026013: Unhandled error in annotated endpoint com.redhat.ChatBotWebSocket@c823ecd: java.lang.NullPointerException: Cannot invoke "java.util.Map.remove(Object)" because "this.chatMemories" is null
        at io.quarkiverse.langchain4j.runtime.aiservice.QuarkusAiServiceContext.removeChatMemoryIds(QuarkusAiServiceContext.java:48)
        at com.redhat.Bot$$QuarkusImpl.remove(Unknown Source)
        at io.quarkiverse.langchain4j.ChatMemoryRemover.remove(ChatMemoryRemover.java:28)
        at com.redhat.ChatBotWebSocket.onClose(ChatBotWebSocket.java:36)
        at java.base/jdk.internal.reflect.DirectMethodHandleAccessor.invoke(DirectMethodHandleAccessor.java:103)
        at java.base/java.lang.reflect.Method.invoke(Method.java:580)
        at io.undertow.websockets.annotated.BoundMethod.invoke(BoundMethod.java:87)

Is this with the current latest release or main?
Asking because I recall fixing something similar.

I hope to get a new release out tomorrow or Wednesday

I have just released 0.10.0. When you have some time, please give it a try and let me know if the issue has been fixed

Nope, still there:
redhat.ChatBotWebSocket@26599c5f: java.lang.NullPointerException: Cannot invoke "java.util.Map.remove(Object)" because "this.chatMemories" is null
        at io.quarkiverse.langchain4j.runtime.aiservice.QuarkusAiServiceContext.removeChatMemoryIds(QuarkusAiServiceContext.java:50)
        at com.redhat.Bot$$QuarkusImpl.remove(Unknown Source)
        at io.quarkiverse.langchain4j.ChatMemoryRemover.remove(ChatMemoryRemover.java:28)
        at com.redhat.ChatBotWebSocket.onClose(ChatBotWebSocket.java:36)
        at java.base/jdk.internal.reflect.DirectMethodHandleAccessor.invoke(DirectMethodHandleAccessor.java:103)
        at java.base/java.lang.reflect.Method.invoke(Method.java:580)
        at io.undertow.websockets.annotated.BoundMethod.invoke(BoundMethod.java:87)
        at io.undertow.websockets.annotated.AnnotatedEndpoint$4.run(AnnotatedEndpoint.java:199)

Happens in dev mode when the websocket is cut during the hot reload.

Interesting, I'll make it more defensive

https://github.com/quarkiverse/quarkus-langchain4j/pull/408

authors: cescoffier geoand


text:
Update copyright to 2023

Update the copyright to 2023

Hi,To improve the usability/readability of the git blame, can you also add the commit to a.git-blame-ignore-revs file? https://docs.github.com/en/repositories/working-with-files/using-files/viewing-a-file#ignore-commits-in-the-blame-viewThanks! Le 20 juin 2023 09:47, Riccardo Mori @.***> a écrit :Update the copyright to 2023
You can view, comment on, or merge this pull request online at:
  https://github.com/quarkslab/quokka/pull/14
Commit Summary
7270339  Update license to 2023
File Changes  (66 files)
M
bindings/python/quokka/__init__.py
(2)

M
bindings/python/quokka/addresser.py
(2)

M
bindings/python/quokka/analysis/__init__.py
(2)

M
bindings/python/quokka/analysis/arch.py
(2)

M
bindings/python/quokka/analysis/calling_convention.py
(2)

M
bindings/python/quokka/analysis/env.py
(2)

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bindings/python/quokka/analysis/replacer.py
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bindings/python/quokka/analysis/utils.py
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bindings/python/quokka/backends/__init__.py
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bindings/python/quokka/backends/capstone.py
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bindings/python/quokka/backends/pypcode.py
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bindings/python/quokka/block.py
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bindings/python/quokka/data.py
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bindings/python/quokka/exc.py
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bindings/python/quokka/executable.py
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bindings/python/quokka/function.py
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bindings/python/quokka/instruction.py
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bindings/python/quokka/program.py
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bindings/python/quokka/reference.py
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bindings/python/quokka/segment.py
(2)

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bindings/python/quokka/structure.py
(2)

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bindings/python/quokka/types.py
(2)

M
bindings/python/quokka/utils.py
(2)

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bindings/python/quokka/version.py
(2)

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docs/tutorials/bionic/code/script.py
(2)

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docs/tutorials/features/code/script.py
(2)

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include/quokka/Block.h
(2)

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include/quokka/Comment.h
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include/quokka/Compatibility.h
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include/quokka/Data.h
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include/quokka/FileMetadata.h
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include/quokka/Function.h
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include/quokka/Imports.h
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include/quokka/Instruction.h
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include/quokka/Layout.h
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include/quokka/Localization.h
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include/quokka/Logger.h
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include/quokka/ProtoHelper.h
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include/quokka/ProtoWrapper.h
(2)

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include/quokka/Quokka.h
(2)

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include/quokka/Reference.h
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include/quokka/Segment.h
(2)

M
include/quokka/Settings.h
(2)

M
include/quokka/Util.h
(2)

M
include/quokka/Version.h
(2)

M
include/quokka/Windows.h
(2)

M
include/quokka/Writer.h
(2)

M
setup.py
(2)

M
src/Block.cpp
(2)

M
src/Comment.cpp
(2)

M
src/Compatibility.cpp
(2)

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src/Data.cpp
(2)

M
src/FileMetadata.cpp
(2)

M
src/Function.cpp
(2)

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src/Imports.cpp
(2)

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src/Instruction.cpp
(2)

M
src/Layout.cpp
(2)

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src/Quokka.cpp
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src/Reference.cpp
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src/Segment.cpp
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src/Util.cpp
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src/Version.cpp.in
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src/Writer.cpp
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tests/python/tests/conftest.py
(2)

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tests/python/tests/test_data.py
(2)

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tests/python/tests/test_executable.py
(2)

Patch Links:
https://github.com/quarkslab/quokka/pull/14.patchhttps://github.com/quarkslab/quokka/pull/14.diff
—Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you are subscribed to this thread.Message ID: @.***>

Yes, I can do that :+1:

authors: DarkaMaul patacca

repo: quarkslab/quokka


text:
Setting background color leaves artifact

Describe the bug
Setting the background color leaves an artifact when selecting a side that is not top.
To Reproduce
Steps to reproduce the behavior:

Configure side trailing (also tested with leading & bottom, same issue)
Set backgroundColor to something not clear

Expected behavior
All of the tooltip's background is set to backgroundColor.
Screenshots

Desktop (please complete the following information):

OS: iOS 15.2
Version 1.1.2

I think the offsets are wrong at https://github.com/quassum/SwiftUI-Tooltip/blob/main/Sources/SwiftUITooltip/TooltipModifier.swift#L167

I think the offsets are wrong at https://github.com/quassum/SwiftUI-Tooltip/blob/main/Sources/SwiftUITooltip/TooltipModifier.swift#L167

Uff, yeah. I'll try to fix it this week. Or feel free to send a PR ;)

@bring-shrubbery Any update since that week?

@b95505017 Nope, literally didn't have a single free hour since then. Will try to take a look at it this weekend though :)

Hey @Eckelf, @b95505017! I fixed this issue. The solution is not perfect - you can still see one transparent pixel where the arrow connects, but it's the best I could do with the time that I have. I encourage you to send a pull request to make it better - just need to add a small rectangle and position it correctly, so that the arrow looks nice on all the side: parameter settings.

authors: Eckelf b95505017 bring-shrubbery

repo: quassum/SwiftUI-Tooltip


text:
The examples doesn't work.

@sinchb I test examples in examples folder and test.py in the tests folder today,but these didn't work.I open my local  addr 192.168.0.112 in brower. I run in ubuntu(desktop14.4.2).PS: I am new hand in ONVIF.so I am sorry for this stupid issues.
Traceback (most recent call last):
File "continuous_move.py", line 83, in
continuous_move()
File "continuous_move.py", line 43, in continuous_move
mycam = ONVIFCamera('192.168.0.112', 80, 'admin', '12345')
File "/usr/local/lib/python2.7/dist-packages/onvif-0.1.2-py2.7.egg/onvif/client.py", line 216, in init
self.update_xaddrs()
File "/usr/local/lib/python2.7/dist-packages/onvif-0.1.2-py2.7.egg/onvif/client.py", line 226, in update_xaddrs
services = self.devicemgmt.GetServices({'IncludeCapability': False})
File "/usr/local/lib/python2.7/dist-packages/onvif-0.1.2-py2.7.egg/onvif/client.py", line 28, in wrapped
raise ONVIFError(err)
onvif.exceptions.ONVIFError: Unknown error:urlopen error time out

@sinchb @taiyangc I run it in virturalbox, can the discover protocol nomal work ?

continuous_move.py is just an EXAMPLE. It works well ONLY with MY CAMERA. you should use onvif-cli or ONVFIService of this lib to test your camera. Before your testing, you should know the IP, Port, username, password of your camera.

@flyingpang Anything else?

@sinchb I install dual system in my computer,I use nmap scan the inter addr,find the cam ip is 192.168.0.116,port is 81,I modify them in continuous_move.py,but it still doesn't work,Maybe my ipcam dosen't support the ONVIF?
Traceback (most recent call last):
File "continuous_move.py", line 83, in
continuous_move()
File "continuous_move.py", line 43, in continuous_move
mycam = ONVIFCamera('192.168.0.116', 81, 'admin', '888888')
File "/usr/local/lib/python2.7/dist-packages/onvif-0.1.2-py2.7.egg/onvif/client.py", line 216, in init
self.update_xaddrs()
File "/usr/local/lib/python2.7/dist-packages/onvif-0.1.2-py2.7.egg/onvif/client.py", line 222, in update_xaddrs
self.devicemgmt  = self.create_devicemgmt_service()
File "/usr/local/lib/python2.7/dist-packages/onvif-0.1.2-py2.7.egg/onvif/client.py", line 331, in create_devicemgmt_service
return self.create_onvif_service('devicemgmt', from_template)
File "/usr/local/lib/python2.7/dist-packages/onvif-0.1.2-py2.7.egg/onvif/client.py", line 319, in create_onvif_service
self.daemon)
File "/usr/local/lib/python2.7/dist-packages/onvif-0.1.2-py2.7.egg/onvif/client.py", line 28, in wrapped
raise ONVIFError(err)
onvif.exceptions.ONVIFError: Unknown error: <urlopen error [Errno -2] Name or service not known>

Please read my comment writen 4 days ago. You can  NOT use continuous_move.py to test your camera.

@sinchb  Sorry,I misunderstand your meaning,at first thought if I just modify ip,port in continuous_move(),The cam will work.Thx

Ok, I will close this issue

continuous_move.py is just an EXAMPLE. It works well ONLY with MY CAMERA. you should use onvif-cli or ONVFIService of this lib to test your camera.

Might i suggest adding those file names to a .gitignore so that we (the public) do not get your private test scripts or as a much better alternative set up a generic framework that can be setup for a broader spectrum of ONVIF compatible devices.
Traceback (most recent call last):
  File "./probe.py", line 89, in <module>
    mycam = ONVIFCamera('192.168.0.22', 80, 'admin', 'admin', '/etc/onvif/wsdl/')
  File "/usr/local/lib/python2.7/dist-packages/onvif/client.py", line 227, in __init__
    self.update_xaddrs()
  File "/usr/local/lib/python2.7/dist-packages/onvif/client.py", line 237, in update_xaddrs
    services = self.devicemgmt.GetServices({'IncludeCapability': False})
  File "/usr/local/lib/python2.7/dist-packages/onvif/client.py", line 31, in wrapped
    raise ONVIFError(err)
onvif.exceptions.ONVIFError: Unknown error: <urlopen error timed out>

as it stands im not sure if this is a problem with my python programming or if this is a problem with the library. My OS is Kali (Debian based 4.9.0-kali4-amd64 #1 SMP Debian 4.9.30-1kali1 (2017-06-06) x86_64 GNU/Linux) after running the install using pip install onvif I fired up the python console and imported the library. however once running the Example on the README.md provided with the project it failed telling me that several WSDL documents were in fact missing. I found them all in the repository under wsdl and copied them to etc. now it seems to load up an instance fine however i still cannot interface with the camera. I have over 150 cameras that i would like to manage all were purchased at the same time from the same manufacture (Zhejiang Dahua Technology Co., Ltd.) I'm running Zoneminder for CCTV recording and picks up ONVIF compatible devices i would rather not have to walk through every camera with the zoneminder install wizard. Providing i can communicate with the camera using this library i should be able to obtain all of the needed information and build the Zoneminder database with Python. Once the MySQL database has been built with the camera information i also have to change Static IP Address assignments from the Camera Web-Interface as well as System Clock settings and administrative logon. Asking to do this manually on that number of devices is a big task i would like to solve this using a python application to automate the mind numbing task.

authors: Morketh flyingpang sinchb

repo: quatanium/python-onvif


text:
Unable to get proper results for imbalanced dataset

I am currently working on the multi-class segmentation of Agricultural aerial images. I have about 7 classes which are highly imbalanced both by image and no.of.pixels that each class has.
I have tried following steps to overcome this class imbalance:
1.I have calculated the class weights based on the procedure mentioned here https://github.com/qubvel/segmentation_models/issues/137#issuecomment-515774767
And obtained my class weights as [  1.52601775  27.67985103 126.29271733 402.83724388  72.80682642  86.53852883   6.85154221  ]
since  class weights are recommended to be [0-1]. I converted the above weights to decimal [0.0037 0.068 0.3141 1.002  0.1811 0.2152 0.017 ]
2. And I tried with combined focal and dice loss with and without class weights.
3. Also,I tried with both encoder_freeze = True and encoder_freeze = False
4.I have also checked that my masks are in the range[0-1]
I am using UNET with resnet-50 backbone.
But the val_loss does not decrease,and it continues to fluctuate above 93% and also I am not able to get good IOU score.
Please give me some inputs to overcome the above issue and also i need to know how to print the class wise metrics
Thanks in advance

@Indhujamari just throwing out extra things for you to try, but have you tried:

using the class_weight parameter in model.fit() instead of using with the loss function(s)? Don't rescale from [0, 1] with this one;
undersampling majority/over sampling minority classes? For example, if every image has class A, but only a few images have class B - G, then remove all images that only contain class A.
using categorical_cross_entropy + jaccard
using one of the efficientnet as the encoder, w/ imagenet or nosy-student weights?

@JordanMakesMaps Thank you for your inputs. Let me try it out.

I also have the same issue with multi class segmentation where my dataset contains about 8 classes (6 classes + 1 background + 1 ignore) which are highly imbalanced.But how to manually assign class weights to this imbalanced dataset... Please help me to solve this issue. Thanks in advance!

@JordanMakesMaps  Thank you for your solution! I'll definitely try it.

@nivetha1234, did you do something in particular to update the model? E.g which models, loss and metrics did you use?
Thank you.

authors: Indhujamari JordanMakesMaps murdav nivetha1234


text:
Normalize error messages

The error message given by the Display representation of an error type should be lowercase without trailing punctuation and typically concise.

Examples of error messages
"unexpected end of file"
"provided string was not true or false"
"invalid IP address syntax"
"second time provided was later than self"
"invalid UTF-8 sequence of {} bytes from index {}"
"environment variable was not valid unicode: {:?}"

As per Rust API Guidelines, this will reduce noise during code reviews.

We should update our code style doc with that too.

authors: fmassot guilload

repo: quickwit-oss/quickwit


text:
Include CQS pattern in list awesome

CATEGORY/PROJECT_NAME - PROJECT_LINK
PROJECT_DESCRIPTION
// Please, fill in this PR template. It will help maintainers to do the review.
// Also, please read our Contribution guidelines.
// Please, create 1 pull request per 1 link.

@bernardo-bruning can you please fix the PR before we look at it? Thanks.
https://github.com/quozd/awesome-dotnet/blob/master/CONTRIBUTING.md

authors: bernardo-bruning pleb

repo: quozd/awesome-dotnet


text:
🛑 Adguard Home DoT is down

In f439070, Adguard Home DoT ($AG_DOT) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Adguard Home DoT is back up in 47790ec after 30 minutes.

repo: quyleanh/upptime


text:
🛑 Adguard Home DoT is down

In db771d9, Adguard Home DoT ($AG_DOT) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Adguard Home DoT is back up in 5c2dc03.


text:
🛑 Adguard Home DoT is down

In d463eb3, Adguard Home DoT ($AG_DOT) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Adguard Home DoT is back up in 129e181.


text:
🛑 Adguard Home DoT is down

In bdaf177, Adguard Home DoT ($AG_DOT) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Adguard Home DoT is back up in b3957b1.


text:
🛑 Adguard Home DoT is down

In 690f504, Adguard Home DoT ($AG_DOT) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Adguard Home DoT is back up in 2eb94b6 after 8 minutes.


text:
Great deskclock, timer!! Missing connection to file manager for selection of alarm sound

Hi your deskclock / timer is excellent. I have installed it on my android from f-droid.
It is a petty that is quite hard to find your app even within f-droid.
I have thousands of songs on my mobile. Thus a very important function I am really missing is to be able easily to select a song for alarm by first selecting an existing file manager and than selecting the song file via the file manager.
This feature would make it much much easier than running through the existing selection for finding the needed song for alarm.
It would be great if you can implement this feature.
Best Regards!

It can already be done.  There are two ways to do this. First method in settings select sounds and then default alarm sound and choose ringtone from file manager.  Second method open the application click on the alarm ringtone, then at the top in personal sounds click on add new and the file manager opens

According to f-droid I am using version 1.2.1. - German translation.
In settings --> Timer --> timer sound --> I can add a sound. There only opens a list of all sounds but I wouldn't call it a file manager, because it is very rudimentary and very difficult to find the needed song file.
My approach would be that you can select first a professional file manager installed. Within the prof. file manager you easily can select what you need.

https://user-images.githubusercontent.com/59417474/135064847-61b6a07f-d151-4158-9b6e-e8651207d257.MOV
As you can see from this screen record you can open the file manager and then search in the file manager, then once in the file manager you have to select the desired ringtone.  It is pretty much the same thing that happens in google clock.

Thanks for your answer. Actually I figured out now, that I hadn't activated "show extended devices" in settings of your file manager. This I was looking for. Maybe you should activate it by standard and make this setting more obvious instead of hided. Or maybe easier you take out these settings complety and have shown SD-Card and internal memory including size always by default.
Something else, if I click on your file manager on "Audio", "recent" or "downlaods" than the search function for a file is not available anymore. It is only visible within SD-Card and internal memory. It should be seen on all views, isn't it?

The file manager is the default and pre-installed on android, my clock app has nothing to do with the file manager, they are two different apps, the clock app opens a link with the default file manager.  More like a problem with the file manager

I see! Thanks!


text:
🛑 Bitwarden is down

In 17eb214, Bitwarden (https://pass.qwq2333.top) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Bitwarden is back up in 320daba.


text:
🛑 Blog is down

In 8fe4f33, Blog (https://qwq2333.top) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Blog is back up in 5fd3f88.


text:
added basic stats page

extracted shared function
Could someone with a little more knowledge of browser compatibility confirm that the type="module" will work here so we can share that function? I haven't written js without babel in a long time...
Once i18n.js is back in a can merge that and add in i18n strings

It's okay to assume es2015+ and modern browser.  The rest of the site already does and most of traffic is mobile.

authors: awong-dev nburt

repo: r-pop/findthemasks


text:
Config directory is not being created on run.

Hi. I'm using version 2 and wallhaven doesn't run and it's complaining config directory doesn't exist. I think it should create it by itself.

I don't think this was an issue in version 1.0.6.
Thanks.

Fixed.


text:
AMQP 1.0 Support

The plugin for AMQP 1.0 is archived. Does that mean support for AMQP 1.0 is not existing any more? Since it is still in the supported protocol section.

No it is still supported we just moved all plugins we support into the
server project itself: https://github.com/rabbitmq/rabbitmq-server
Cheers
Karl
On Tue, 11 Jan 2022 at 15:48, Jens Willmer @.***> wrote:

The plugin for AMQP 1.0
https://github.com/rabbitmq/rabbitmq-amqp1.0/blob/v3.7.x/README.md is
archived. Does that mean support for AMQP 1.0 is not existing any more?
Since it is still in the supported protocol section
https://www.rabbitmq.com/protocols.html#amqp-10.
—
Reply to this email directly, view it on GitHub
https://github.com/rabbitmq/rabbitmq-website/issues/1323, or unsubscribe
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.
Triage notifications on the go with GitHub Mobile for iOS
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or Android
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You are receiving this because you are subscribed to this thread.Message
ID: @.***>

--
Karl Nilsson

authors: jwillmer kjnilsson

repo: rabbitmq/rabbitmq-website


text:
🛑 Pet Project is down

In bae9b65, Pet Project ($RINFO_SITE) was down:

HTTP code: 500
Response time: 15423 ms

Resolved: Pet Project is back up in 7560293.


text:
🛑 Pet Project is down

In 2605c93, Pet Project ($RINFO_SITE) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Pet Project is back up in 0df3306.


text:
Add support for LINK and UNLINK verbs

Sinatra has added direct support for LINK and UNLINK. This commit
adds support for those verbs.

@iGEL and @carlad - thanks for the suggestion. I think we should discuss this a bit more before implementing it. The current implementation is perhaps not suitable as it is, so closing for now and we can continue the discussion in the PR anyway. If/when we reach a reasonable conclusion, either one of you could submit a PR after that.

authors: carlad perlun

repo: rack-test/rack-test


text:
New parent props don't re-render the component

Using react-redux: 4.3.0 I'm passing props to my connect()'ed component MyComponent from its parent component. However they're not re-rendering MyComponent. I only need connect() for  dispatch so I'm wrapping my component like this:
exports default connect()(MyComponent)

Removing connect() fixes the issues.
is this expected behavior?

If your props are mutated deeply, this is expected. React Redux assumes that if props.foo.a changes, props.foo also changes its reference. This is the only performant way to know when the props change.
If you are affected by this,

Either change your parent component to make sure the props are not mutated deeply,
or add { pure: false } as the fourth argument to connect() (note: it will be much slower than normally).

authors: alantrrs gaearon

repo: rackt/react-redux


text:
How to build a navigation controller?

This router is really cool! I love the way it abstracts your layout along with the routes.
I've been trying to build the concept of a UINavigationController and UITabBarController for React. This router looks pretty neat and I think it would be really cool to use a similar pattern to this router but I'm struggling to come up with something...
Have you guys thought much about this?
For example, imagine you have a simple social app like Twitter or Instagram. You can keep clicking through nested User / Post views forever and back out of them in order. But you can't just use browser history because there is a different navigation controller of each tab.
Imagine you have 3 tabs: profile, feed, and search.
<Router history={history}>
  <Route component={App}>
    <Route path="profile" nav={profileNavController} component={Profile}/>
    <Route path="feed" nav={feedNavController} component={Feed}/>
    <Route path="search" nav={searchNavController} component={Search}>
    <Route path="post/:id" component={Post}/>
    <Route path="user/:id" component={User}/>
  </Route>
</Router>

Each has its own navigation controller passed as props. So perhaps for linking, we could do something like this:
<Link to={'/user/' + id} push={this.props.navController}>{username}</Link>

Still trying to figure this out. But is this something of interest to anyone?

Am I understanding it right that a) you want to have a component that allows to have some standard navigation between views (with that pretty right to left transitions maybe) and b) that navigation between this views should not write to history (or at least be optionated)?
If it's true then I see at as you should create your own Component which will handle this stuff. As for me this is not direct responsibility of the routing library but I'm nobody here.
Do you already have something on this?

Yeah, its probably not the best to do with the router actually, but perhaps there could be some way. Imagine an app like Instagram. There are multiple Tabs which each have their own Nav history. Right now I'm building it much like the React Native NavigatorIOS API. This means lots of function callbacks, etc. but I really like how this Router somehow gets away with laying things out more declaratively.

authors: ccorcos zdespolit

repo: rackt/react-router


text:
After upgrading to 1.0.0-rc3 I get an error calling render(, document.body)

I've attempted to upgrade an application from pre 1.0 to the latest version of react-router and now I get the following when attempting to call the render method.
import { render } from 'react-dom'
var Router = require('react-router');

render(<Router />, document.body);

Error: Invariant Violation: Element type is invalid: expected a string (for built-in components) or a class/function (for composite components) but got: object.

Obviously the original code was much involved but this is what I've been able to reduce it too in an attempt to pinpoint the issue.

Ok, perhaps I've solved the issue for myself. As I was updating existing code and am pretty new to ES20015, I must have made a mistake by keeping the var Router = require('react-router') syntax. I'm not exactly sure why this made this difference but the change below works for me as expected and iit looks much nicer.
import { render } from 'react-dom'
import { Router } from 'react-router'

render(<Router />, document.body);


text:
oncomplete called after onteardown

Description:
In this fiddle, http://jsfiddle.net/sabob/mygdmrzv/, the oncomplete lifecycle is called after onteardown.
In my app I have a menu to switch between pages with a fading transition.
I generally use oncomplete to setup external libraries such as validations which need access to the form on the page.
When switching pages I teardown the current page, then render the new page.
If I quickly switch away from a page that is still fading in, I get an error because the current page dom has been removed by the time oncomplete is called.
I expected the teardown call to jump to the end of the transition, call oncomplete, unrender the dom and call the rest of the lifecycle callbacks.
Is this a bug?
Versions affected:
0.9, 0.8.x
Platforms affected:
Reproduction:
Code:

Perhaps a more accurate approach would be for a teardown() call to skip the remaining lifecycle calls?

I believe this is intended behavior, as weird as it is.
oncomplete is async because it has to wait for transitions and stuff. So what happens is that the setup, rendering, and teardown happen in the same tick while oncomplete is still pending. Putting breakpoints on each, it appears that oncomplete keys off from a resolved promise, which backs up the claim.
Setup and immediately tearing down is an odd use case tho. You could do view.teardown() inside oncomplete so it also waits with it.

Perhaps a more accurate approach would be for a teardown() call to skip the remaining lifecycle calls?

Yep, it's probably a good idea to cancel any pending stuff when the instance is being nuked. 😄

Setup and immediately tearing down is an odd use case tho. You could do view.teardown() inside oncomplete so it also waits with it.
I cannot

Setup and immediately tearing down is an odd use case tho. You could do view.teardown() inside oncomplete so it also waits with it.

My real life use case is explained in the description. Menus drive the teardown/render process, as users navigate around the site. The issue I saw arise because there are transitions between rendering pages. If users navigate away from a page to another page, before the transition completes, the issue arise. Another way this was produced is by pressing the browser back button twice :)

it's probably a good idea to cancel any pending stuff when the instance is being nuked. 😄

Unfortunately, Ractive doesn't expose a way to cancel the current transitions.
Still, technically it should be possible to reject the oncomplete promise and not take further part in the clifecycle?

We can probably add a check in the complete handler to make sure the component isn't torn down. Part of me says that complete is an async event, so it's up to the user to check the state of things. I'm not sure what the best thing to do is in this case.
Out of curiosity, would the destruct event, which is the teardown analog of complete, work in this case if you're using 0.9? Also, FWIW, there's an exposed property instance.torndown that will tell you if the component has been torn down. torndown is available from 0.8, so you could use it as a check in the complete handler.
I still haven't come up with a good way to have cancel-able transitions. The simple cases aren't too bad, but getting layered runloops caused by things like setting in observer callbacks makes things get pretty hairy.

Sorry, I had a bit of a reading comprehension fail. destruct probably wouldn't do anything for you and the issue as described. Are you cross-fading the views, or fading one out and a new one in? If the latter, I'd think that reasonably fast transitions along with keeping a queue of actions to drain would be a reasonable solution? I've been working on something similar, and that's the approach I'm taking.

Yep, fading out/ then in. The transitions is 200ms, so fairly quick. Even so, the error can still occur when user hits back button twice.
In terms of workarounds there are a couple. The simplest for me is to move the onComplete code to onRender. since that is a sync'd operation. However this approach is limited since the dom isn't visible at this stage.
Also onComplete is a natural place for me to perform further dom manipulations.

We can probably add a check in the complete handler to make sure the component isn't torn down.
Seems reasonable to me. It is an edge case, but if we can avoid it, it removes some cognitive overhead. ;-)

Part of me says that complete is an async event, so it's up to the user to check the state of things.
Nods, but that would create a bit of work since the check has to be done on every page.

Regarding the torndown check, that could be useful if there is a way for me to hook into Ractive lifecycle somehow to globally add this check? My Javascript ain't the best, but I know "prototype"ing does allow a fair amount of monkey patching.

I still haven't come up with a good way to have cancel-able transitions.
Are Ractive transitions in a queue of some sort? I know jQuery has the stop() method which stops all queued transitions and jump to their end state. As you mentioned this approach might not work very well in all cases for Ractive.

Tried to fix this locally, by checking if "ractive.torndown" is true before firing "oncomplete. But lots of tests fail after this change. Is firing oncomplete (even after a teardown) by design or is the next test kicked off before the current test finishes, thus causing the ractive instance of the current test to teardown before the oncomplete fires?

Is firing oncomplete (even after a teardown) by design

oncomplete should just be in the rendering side of things, not the teardown side. Here's a demo showing that oncomplete doesn't fire on teardown.
If you can open a PR or push up a branch in your fork, we could check what's going on. Tests do get wonky where transitions are involved, so it might be a tests problem. A quick tip is to run the failing tests solo (click rerun in the QUnit interface) to see if it's affected by the code change or the other tests.

authors: evs-chris fskreuz sabob

repo: ractivejs/ractive


text:
add EO extension JSON schema

Wrote JSON schema based off of https://github.com/radiantearth/stac-spec/blob/dev/extensions/stac-eo-spec.md.  I'm doing the same "inheritance" thing where an EO item is still a STAC item which is still a geoJSON feature.

By the way, I ran validation by calling npm run validate_extension -- -s "../extensions/json-schema/stac-eo-extension.json" -d "../extensions/examples/landsat8-sample.json"
Unfortunately, the landsat samples are not valid (missing eo:platform, eo:constallation and eo:instrument). We should add these fields to the examples, make sure they all validate and also add the above command to the validation readme.

@m-mohr I've added the min/max values you suggested.  Thanks again for the great proofing you are doing!

In testing I noticed that I had the eo:cloud_cover and other fields inside of the bands object and not inside of the properties objects.  I've fixed this in the latest commit.

By the way, the related issue is #94.

Needs to be adopted to the changes introduced by #247 (bands as arrays).

I'll merge this to a development branch in this repository so that we can update the JSON schema by @jeffnaus to the most recent developments.

authors: jeffnaus m-mohr

repo: radiantearth/stac-spec


text:
Updated the logo of X(Twitter)

As we all know, the logo of X(Twitter) has been changed, so I have updated the icon on the website.

@Reshrahim
Kindly review my PR and merge it please.

@Reshrahim Kindly review my PR and merge it please.

Thank you for your contribution. Looks like there is some issue with the merge validation workflow. Will get that fixed and merge the change in

repo: radius-project/website


text:
[Bug]: Reactivity on when using sub-property of v-model

Reproduction
tbd
Describe the bug
Ran into a bug when using a basing feature of Input. The value displayed in input aren't consistent and will often show default. Not sure if the issue would be with Radix or the Shad wrapper.
ex:
Obj = ref(null)
computed() = return Obj || { placeholderProp: 123 }
<Input :value="obj.child">
Later after api call...
Obj = {child: 'string inconsistently showing' , other: 123}
In my case, the Obj is a vue ref, in a parent component. Resorted to using a native HTML  as I couldn't figure a quick fix.
System Info
Binaries:
    Node: 16.17.1 - ~/.nvm/versions/node/v16.17.1/bin/node
    npm: 8.15.0 - ~/.nvm/versions/node/v16.17.1/bin/npm
    pnpm: 9.3.0 - ~/Library/pnpm/pnpm
  Browsers:
    Chrome: 126.0.6478.127
  npmPackages:
    @vueuse/core: ^10.11.0 => 10.11.0
    radix-vue: ^1.8.3 => 1.8.3
    shadcn-vue: ^0.10.5 => 0.10.5
    unplugin-auto-import: ^0.17.5 => 0.17.6
    vue: ^3.4.21 => 3.4.29

Contributes

[ ] I am willing to submit a PR to fix this issue
[ ] I am willing to submit a PR with failing tests

a Vue playground or reproduction would be great

Closing, for now, will reopen after reproduction

authors: iplanwebsites sadeghbarati

repo: radix-vue/shadcn-vue


text:
Watcher stops working when you delete watched files

@radovskyb Currently watcher stops working when you delete the watched file/directory. It's a bumper for my upcoming release.
It gives an error.
2017-07-21 12:01:02.729 ERROR Watch error:error: watched file or folder deleted

Doesn't return any events there after. And If you call w.Close() at this moment, program gets stuck.
Please let me know if you need further info.
PS: wether you call Close or not, watcher stops working

You can have a look watcher implementation for aah framework.
https://github.com/go-aah/tools/blob/v0-unstable/aah/run.go#L135-L217
Please let me know, if I'm doing something wrong or way to handle or fix.

Hey @jeevatkm,
I was going to suggest for you to ignore when that type of error occurs like so:
case err := <-w.Error:
    if err == watcher.ErrWatchedFileDeleted {
	fmt.Println("ignore and continue")
	continue
    }

However, I believe there is a deadlock that occurs now when that happens (must have missed it when I rewrote watcher last time), but I will fix it when I get a chance soon!

Hey @jeevatkm,
I removed the deadlock issue, so you can try again and let me know how it goes :)

@radovskyb  Thank you, this is very helpful.
I will very using against master branch and let you know soon. Then you can make a release (tag) for this fix.

Working perfectly :) thanks, Can you please make a release?

Released as v1.0.1 :)

authors: jeevatkm radovskyb

repo: radovskyb/watcher


text:
Clean up folder names

Cleaning up the folder names in the dcrios repo.  Lower case and without spaces.
refers to
*Decred Wallet.xcodeproj
*Decred Wallet.xcworkspace
*Decred Wallet
*Decred WalletTests

https://github.com/raedahgroup/dcrios/pull/49

This was resolved in https://github.com/raedahgroup/dcrios/pull/51

authors: ensoreus macsleven raedah

repo: raedahgroup/dcrios

license: ISC


text:
is-toast class not added since 0.6.2

Overview of the problem
Buefy version: [0.6.2]
Vuejs version: [2.5.9]
OS/Browser:
Description
The is-toast class is not added anymore in the Toast component :
https://github.com/rafaelpimpa/buefy/commit/5fa2dffb970635aff1bf6a3773e13c8099f174e7#diff-2f4b8565507a7062ea963009170f040fL30
Not sure if its an expected behavior

It is, just use .notices .toast

authors: adrlen rafaelpimpa

repo: rafaelpimpa/buefy