couchup replicate issue

Trying to use the replicate function to migrate my 686GB collection of databases...
First 3-4 databases (about 5GB) work great... but now I get something like this when I try it
first got it using the -a feature and now am trying individual db to see if I can find a pattern
/usr/local/couchdb/bin/couchup replicate -l USER -p PASSWORD -t 3600 -f eridu
Starting replication for eridu...
{"error":"not_found","reason":"Could not open source database http://<IP_ADDRESS>:5986/eridu/: {db_not_found,<<"http://<IP_ADDRESS>:5986/eridu/\">>}"}

In couchdb.stderr I see
[notice] 2017-08-14T19:39:48.354189Z<EMAIL_ADDRESS><0.10691.7> b3b8c7e8e0 <IP_ADDRESS>:5984 <IP_ADDRESS> tcuser POST /_replicate 404 ok 3
[notice] 2017-08-14T19:39:49.353059Z<EMAIL_ADDRESS><0.10715.7> -------- <IP_ADDRESS> - - GET /eridu 200
[notice] 2017-08-14T19:39:49.355750Z<EMAIL_ADDRESS><0.10717.7> 1ce9ddd1df <IP_ADDRESS>:5984 <IP_ADDRESS> undefined GET /eridu 404 ok 1
[notice] 2017-08-14T19:39:50.359934Z<EMAIL_ADDRESS><0.10731.7> 53ab98918d <IP_ADDRESS>:5984 <IP_ADDRESS> undefined GET /eridu 404 ok 1
[notice] 2017-08-14T19:39:50.363785Z<EMAIL_ADDRESS><0.5320.2> 57e260d3dc couchdb-2-3.irbfocus-qa:6984 <IP_ADDRESS> undefined GET /_active_tasks 200 ok 1
[notice] 2017-08-14T19:39:51.364333Z<EMAIL_ADDRESS><0.10759.7> f0718ec5e4 <IP_ADDRESS>:5984 <IP_ADDRESS> undefined GET /eridu 404 ok 1

if I curl http://<IP_ADDRESS>:5986/eridu/ ( and add the user and pass ) I get
{"db_name":"eridu","doc_count":7438871,"doc_del_count":511625,"update_seq":8168757,"purge_seq":0,"compact_running":false,"disk_size":81804304630,"other":{"data_size":109},"data_size":12273332816,"sizes":{"file":81804304630,"active":12273332816,"external":109},"instance_start_time":"1502734780758722","disk_format_version":6,"committed_update_seq":8168757,"compacted_seq":0,"uuid":"4a84be53b812cac9b71915eab09f3be9"}

So the db sure seems to be there... I can go to 5986/_utils and see the db... can view data etc
Any pointers?

Does the problem persist when you leave off the -f option?

Yes my first attempts did not have the -f option

I really don't know what to say here, @jvabob . This line:
[notice] 2017-08-14T19:39:48.354189Z<EMAIL_ADDRESS><0.10691.7> b3b8c7e8e0 <IP_ADDRESS>:5984 <IP_ADDRESS> tcuser POST /_replicate 404 ok 3

says that Couch (on the clustered port) failed to POST to /_replicate with a 404 error, which means couch itself got a 404 back on the source database.
Were you able to track down any sort of pattern here?

I wound up writing my own routine to migrate the data.


[#5276] Update code analysis to latest VS recommendations - Disable rules

Addresses # 5276
#minor

IMPORTANT!
Note: These changes are being address as part of enabling the .NET Analyzers library in the PR # XXX.

Description
This PR disables new rules detected by the new .NET Analyzers that are considered high impact.
List:

CA1002
CA1024
CA1711
CA2109
CA2326
CA2327
CA2329
CA5394
CA5404

Testing
This image shows the CI pipeline successfully running after the changes.

promoted 6245


Installation using Pipenv failed

Hi, thanks for your work on this.
I just ran into the following error while trying to install via pipenv, using python 3.6.6
It looks like a checksum failure on the package, or a dependency. Let me know if you can reproduce it please!
$ pipenv install djangorestframework-guardian
Courtesy Notice: Pipenv found itself running within a virtual environment, so it will automatically use that environment, instead of creating its own for any project.
Installing djangorestframework-guardian…
Requirement already satisfied: djangorestframework-guardian in /home/jules/.local/share/virtualenvs/django-poc-mXC5fPn1/lib/python3.6/site-packages (0.3.0)
Requirement already satisfied: djangorestframework in /home/jules/.local/share/virtualenvs/django-poc-mXC5fPn1/lib/python3.6/site-packages (from djangorestframework-guardian) (3.10.3)
Requirement already satisfied: django in /home/jules/.local/share/virtualenvs/django-poc-mXC5fPn1/lib/python3.6/site-packages (from djangorestframework-guardian) (2.2.6)
Requirement already satisfied: django-guardian in /home/jules/.local/share/virtualenvs/django-poc-mXC5fPn1/lib/python3.6/site-packages (from djangorestframework-guardian) (2.1.0)
Requirement already satisfied: pytz in /home/jules/.local/share/virtualenvs/django-poc-mXC5fPn1/lib/python3.6/site-packages (from django->djangorestframework-guardian) (2018.4)
Requirement already satisfied: sqlparse in /home/jules/.local/share/virtualenvs/django-poc-mXC5fPn1/lib/python3.6/site-packages (from django->djangorestframework-guardian) (0.3.0)

Adding djangorestframework-guardian to Pipfile's [packages]…
Pipfile.lock not found, creating…
Locking [dev-packages] dependencies…
Locking [packages] dependencies…
", line 341, in open_local_or_remote_file
    response = session.get(url, headers=headers, stream=True)
  File "/usr/lib/python3/dist-packages/pipenv/vendor/pip9/_vendor/requests/sessions.py", line 488, in get
    return self.request('GET', url, **kwargs)
  File "/usr/lib/python3/dist-packages/pipenv/vendor/pip9/download.py", line 386, in request
    return super(PipSession, self).request(method, url, *args, **kwargs)
  File "/usr/lib/python3/dist-packages/pipenv/vendor/pip9/_vendor/requests/sessions.py", line 475, in request
    resp = self.send(prep, **send_kwargs)
  File "/usr/lib/python3/dist-packages/pipenv/vendor/pip9/_vendor/requests/sessions.py", line 596, in send
    r = adapter.send(request, **kwargs)
  File "/usr/lib/python3/dist-packages/pipenv/vendor/pip9/_vendor/cachecontrol/adapter.py", line 37, in send
    cached_response = self.controller.cached_request(request)
  File "/usr/lib/python3/dist-packages/pipenv/vendor/pip9/_vendor/cachecontrol/controller.py", line 111, in cached_request
    resp = self.serializer.loads(request, cache_data)
  File "/usr/lib/python3/dist-packages/pipenv/vendor/pip9/_vendor/cachecontrol/serialize.py", line 114, in loads
    return getattr(self, "_loads_v{0}".format(ver))(request, data)
  File "/usr/lib/python3/dist-packages/pipenv/vendor/pip9/_vendor/cachecontrol/serialize.py", line 176, in _loads_v2
    cached = json.loads(zlib.decompress(data).decode("utf8"))
zlib.error: Error -3 while decompressing data: incorrect data check''

Hi @780Farva. I tried this locally and didn't run into an issue. I noticed that your pipenv has vendored pip9, which indicates that you're at best using the pipenv 2018.6.25 release. Try upgrading and let me know if you run into an issue.

Hey @rpkilby, good catch. Looks like apt on debian is serving up pipenv v11.9.0! I've made sure pipenv is up to date and as you suspected everything is cool now.
Thanks!


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Note: There is a known issue with the layout when displaying an error message on mobile devices. This is due to how Mailchimp's JS library inserts an element when an error occur:

I tested that this seems to work, merging.


Fix omitted dtype params in efficient memory attention function.

Add dtype params to efficient_dot_product_attention

Ref: #81

Already fixed. closed :)


fix: remove functionName from transform-host lambdas

The @searchable and @predictions directives create a Lambda
function via context.api.host.addLambdaFunction(). This commit
updates addLambdaFunction() to not set the optional functionName
in the CFN. This lets CFN generate a unique name.
The mock functionality also needed to be updated because mock
expects all Lambdas to have this optional property. If the CFN
does not contain a functionName, fall back to the resource name.
Fixes: https://github.com/aws-amplify/amplify-cli/issues/9480

Codecov Report

Merging #9491 (c4e1c7d) into master (c66de92) will not change coverage.
The diff coverage is 0.00%.

@@           Coverage Diff           @@
##           master    #9491   +/-   ##
=======================================
  Coverage   56.13%   56.13%
=======================================
  Files         902      902
  Lines       50632    50632
  Branches    10944    10945    +1
=======================================
  Hits        28422    28422
  Misses      20179    20179
  Partials     2031     2031

Impacted Files
Coverage Δ

...ify-graphql-transformer-core/src/transform-host.ts
23.07% <ø> (ø)

...l-mock/src/CFNParser/resource-processors/lambda.ts
0.00% <0.00%> (ø)

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LGTM

Waiting on this to be able to deploy to production

Can this please be deployed to npm ASAP? It is blocking deployments to production, and downgrading is not a 100% error-proof workaround

Please deploy... Pretty please...


Kubernetes refactoring

What does this PR change?
The installation, migration, upgrade and uninstall for Kubernetes has been refactored to:

no longer use a helm chart
use jobs for the migration phases
merge all the installation, migration and upgrade code into a single Reconcile() function.

This PR paves the way for the transition to an operator and improves the reliability of migrations.
As a collateral, SSH agent can no longer be used as that would require
running on a cluster node again. The tool creates a ConfigMap to store the SSH config and known_hosts and a Secret
for a password-less SSH key.
Using Kubernetes API modules also helps for code reuse with a future operator.
Test coverage

Unit tests were added

[X] DONE

Links
Issue(s): https://github.com/uyuni-project/uyuni-tools/issues/431 https://github.com/uyuni-project/uyuni-tools/issues/432 https://github.com/uyuni-project/uyuni-tools/issues/433 https://github.com/uyuni-project/uyuni-tools/issues/436

[X] DONE

Changelogs
Make sure the changelogs entries you are adding are compliant with https://github.com/uyuni-project/uyuni/wiki/Contributing#changelogs and https://github.com/uyuni-project/uyuni/wiki/Contributing#uyuni-projectuyuni-repository
If you don't need a changelog check, please mark this checkbox:

[ ] No changelog needed

If you uncheck the checkbox after the PR is created, you will need to re-run changelog_test (see below)
Before you merge
Check How to branch and merge properly!

🎉


ContentEditor admin requires TemplateMixin

It appears from the documentation that all the plugins(mixing) are optional including TemplateMixin which appears to be required only for multiple template formats. However the ContentEditor admin requires instance.regions which are only available from TemplateMixin
Have I missed something?
EDIT: Although the documentation does state that the ContentEditorAdmin uses the template regions but it should either make the TemplateMixin a dependency or we should move the region related functions from the TemplateMixin to the AbstractPage model or another ContentEditor related Mixin since forcing a template_key in all models just to get ContentEditorAdmin seems to be superflous

The ContentEditor requires a regions attribute on the model, and the TemplateMixin is one way to provide this attribute. The django-content-editor documentation contains a static regions definition which works as well. Copy-pasted from http://django-content-editor.readthedocs.io/en/latest/#example-articles-with-rich-text-plugins:
class Article(models.Model):
    title = models.CharField(max_length=200)
    pub_date = models.DateField(blank=True, null=True)

    regions = [
        Region(key='main', title='main region'),
        Region(key='sidebar', title='sidebar region',
               inherited=False),
    ]

    def __str__(self):
        return self.title

Maybe you don't even need two regions, then regions = [Region(key='main', title='Main')] would already be sufficient.
I agree that forcing a template_key field would be superfluous.

Agreed that TemplateMixin has to provide that as an override but my two cents say that the documentation for ContentEditorAdmin should mention the regions setting as a compulsory requirement (esp since the documentation is quite good and thorough otherwise)
With that done, we can close this query. Thanks

Thank you! I added a note to the django-content-editor docs. Feedback is very welcome!

@matthiask, adding this note here because the more I use this, it appears that an Admin requiring a field on a model is backwards. If we think about it, the ContentEditor admin should use a default regions setting of [] if none are provided and only use regions if the model has the same. An admin throwing an error due to a missing field on the model isn't intuitive. If something is added into the admin which is not valid for the model then an error makes sense. What say?

The list of regions is both used in the ContentEditor and also in content_editor.contents.Contents. The region CharFields exist on all plugins.
The model is available everywhere, so I didn't give this too much thought. Do you have a proposal how the regions list should be made available to all the places it's being used instead? Or maybe we should just introduce a system check here: https://github.com/matthiask/django-content-editor/blob/master/content_editor/admin.py#L19 ?


Evaluating a model with a simplex parameter type gives segmentation fault

When evaluating the density of a model containing a simplex parameter, bridgestan gives a seg fault:
import bridgestan as bs
import numpy as np
model = bs.StanModel.from_stan_file("../test_models/simplex/simplex.stan")
param_length = model.param_num()
theta = np.array([1/param_length] * param_length)
theta_unc = model.param_unconstrain(theta)
log_p = model.log_density(theta_unc)

Output:
[1]    12697 segmentation fault (core dumped)  /usr/bin/python

The same occurs with the R interface.
As a side note, the model in test_models/simplex/simplex.stan had a misspecified prior which I've fixed in #37

I can't recreate this, running the same example for me yields
>>> log_p
-16.094379124341003

Can you share some information about your system/environment, python versions, etc?

Hm, my setup is CmdStan 2.30.1, Ubuntu 20.04, gcc 9.40, python 3.9.13
Do you have any environment variables (or changes to $cmdstan/make/local) which would affect compilation? CXXFLAGS etc

Can't find anything that looks like it would affect compilation.
Just tried on a Ubuntu 20.04 install with gcc/g++ 9.4.0 and python 3.9.5 (built with gcc 9.3.0) which works fine. Later versions of gcc to blame?

That would be a bummer if GCC broke something here. If you're willing to give some more time to debugging this, it would be great to get a full backtrace out of the core dump python produces, to see if it's anything we could fix easily

Output from gdb on Ubuntu 22.04.1 with gcc 11.2.0 (easier to get python debug symbols than on arch):
(gdb) bt
#0  0x00007fffeb7369eb in stan::math::internal::reverse_pass_callback_vari<stan::math::simplex_constrain<Eigen::Map<Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, (void*)0>(Eigen::Map<Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > const&, stan::scalar_type<Eigen::Map<Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, void>::type&)::{lambda()#1}>::chain() () from /home/alecks/git/bridgestan/test_models/simplex/simplex_model.so
#1  0x00007fffeb75b73f in void stan::math::gradient<model_functor<stan::model::model_base*> >(model_functor<stan::model::model_base*> const&, Eigen::Matrix<double, -1, 1, 0, -1, 1> const&, double&, Eigen::Matrix<double, -1, 1, 0, -1, 1>&) () from /home/alecks/git/bridgestan/test_models/simplex/simplex_model.so
#2  0x00007fffeb74d217 in model_rng::log_density(bool, bool, double const*, double*) () from /home/alecks/git/bridgestan/test_models/simplex/simplex_model.so
#3  0x00007fffeb74d532 in log_density () from /home/alecks/git/bridgestan/test_models/simplex/simplex_model.so
#4  0x00007ffff6982e2e in ?? () from /lib/x86_64-linux-gnu/libffi.so.8
#5  0x00007ffff697f493 in ?? () from /lib/x86_64-linux-gnu/libffi.so.8
#6  0x00007ffff6bed451 in _call_function_pointer (argtypecount=<optimised out>, argcount=5, resmem=0x7fffffffd660, restype=<optimised out>, atypes=<optimised out>, avalues=<optimised out>, pProc=0x7fffeb74d520 <log_density>,
    flags=4353) at ./Modules/_ctypes/callproc.c:916
#7  _ctypes_callproc (pProc=<optimised out>, argtuple=<optimised out>, flags=<optimised out>, argtypes=<optimised out>, restype=<optimised out>, checker=<optimised out>) at ./Modules/_ctypes/callproc.c:1259
#8  0x00007ffff6bf6ce2 in PyCFuncPtr_call (self=<optimised out>, inargs=<optimised out>, kwds=0x0) at ./Modules/_ctypes/_ctypes.c:4201
#9  0x00005555556a73bb in _PyObject_MakeTpCall (tstate=0x555555b5ca60, callable=<_FuncPtr(__name__='log_density') at remote 0x7ffff3bc3a00>, args=<optimised out>, nargs=<optimised out>, keywords=0x0) at ../Objects/call.c:215
#10 0x000055555569ff59 in _PyObject_VectorcallTstate (kwnames=0x0, nargsf=<optimised out>, args=<optimised out>, callable=<_FuncPtr(__name__='log_density') at remote 0x7ffff3bc3a00>, tstate=<optimised out>)
    at ../Include/cpython/abstract.h:112
#11 _PyObject_VectorcallTstate (kwnames=0x0, nargsf=<optimised out>, args=0x7ffff41c2940, callable=<_FuncPtr(__name__='log_density') at remote 0x7ffff3bc3a00>, tstate=<optimised out>) at ../Include/cpython/abstract.h:99
#12 PyObject_Vectorcall (kwnames=0x0, nargsf=<optimised out>, args=0x7ffff41c2940, callable=<_FuncPtr(__name__='log_density') at remote 0x7ffff3bc3a00>) at ../Include/cpython/abstract.h:123
#13 call_function (kwnames=0x0, oparg=<optimised out>, pp_stack=<synthetic pointer>, trace_info=0x7fffffffda40, tstate=<optimised out>) at ../Python/ceval.c:5891
#14 _PyEval_EvalFrameDefault (tstate=<optimised out>, f=<optimised out>, throwflag=<optimised out>) at ../Python/ceval.c:4181
#15 0x00005555556b112c in _PyEval_EvalFrame (throwflag=0,
    f=Frame 0x7ffff41c27a0, for file /home/alecks/git/bridgestan/python/bridgestan/model.py, line 386, in log_density (self=<StanModel(lib_path='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', stanlib=<CDLL(_name='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', _FuncPtr=<_ctypes.PyCFuncPtrType at remote 0x55555600b0f0>, _handle=93825003467936, construct=<_FuncPtr(__name__='construct') at remote 0x7ffff3bc3340>, name=<_FuncPtr(__name__='name') at remote 0x7ffff3bc3400>, param_num=<_FuncPtr(__name__='param_num') at remote 0x7ffff3bc34c0>, param_unc_num=<_FuncPtr(__name__='param_unc_num') at remote 0x7ffff3bc3580>, param_names=<_FuncPtr(__name__='param_names') at remote 0x7ffff3bc3640>, param_unc_names=<_FuncPtr(__name__='param_unc_names') at remote 0x7ffff3bc3700>, param_constrain=<_FuncPtr(__name__='param_constrain') at remote 0x7ffff3bc37c0>, param_unconstrain=<_FuncPtr(__name__='param_unconstrain') at remote 0x7ffff3bc3880>, param_unconstrain_json=<_FuncPtr(__name__='param_unc...(truncated), tstate=0x555555b5ca60) at ../Include/internal/pycore_ceval.h:46
#16 _PyEval_Vector (kwnames=<optimised out>, argcount=<optimised out>, args=<optimised out>, locals=0x0, con=0x7fffeb7c07a0, tstate=0x555555b5ca60) at ../Python/ceval.c:5065
#17 _PyFunction_Vectorcall (func=<function at remote 0x7fffeb7c0790>, stack=<optimised out>, nargsf=<optimised out>, kwnames=<optimised out>) at ../Objects/call.c:342
#18 0x00005555556999e6 in _PyObject_VectorcallTstate (kwnames=0x0, nargsf=<optimised out>, args=0x7ffff6d91da8, callable=<function at remote 0x7fffeb7c0790>, tstate=0x555555b5ca60) at ../Include/cpython/abstract.h:114
#19 PyObject_Vectorcall (kwnames=0x0, nargsf=<optimised out>, args=0x7ffff6d91da8, callable=<function at remote 0x7fffeb7c0790>) at ../Include/cpython/abstract.h:123
#20 call_function (kwnames=0x0, oparg=<optimised out>, pp_stack=<synthetic pointer>, trace_info=0x7fffffffdc10, tstate=<optimised out>) at ../Python/ceval.c:5891
#21 _PyEval_EvalFrameDefault (tstate=<optimised out>, f=<optimised out>, throwflag=<optimised out>) at ../Python/ceval.c:4198
#22 0x0000555555696026 in _PyEval_EvalFrame (throwflag=0, f=Frame 0x7ffff6d91c40, for file /home/alecks/git/bridgestan/python/simplex_test.py, line 12, in <module> (), tstate=0x555555b5ca60)
    at ../Include/internal/pycore_ceval.h:46
#23 _PyEval_Vector (tstate=0x555555b5ca60, con=<optimised out>, locals=<optimised out>, args=<optimised out>, argcount=<optimised out>, kwnames=<optimised out>) at ../Python/ceval.c:5065
#24 0x000055555578c106 in PyEval_EvalCode (co=<code at remote 0x7ffff6c473c0>,
    globals={'__name__': '__main__', '__doc__': None, '__package__': None, '__loader__': <SourceFileLoader(name='__main__', path='/home/alecks/git/bridgestan/python/simplex_test.py') at remote 0x7ffff6c2d2a0>, '__spec__': None, '__annotations__': {}, '__builtins__': <module at remote 0x7ffff6df85e0>, '__file__': '/home/alecks/git/bridgestan/python/simplex_test.py', '__cached__': None, 'bs': <module at remote 0x7ffff6c87920>, 'np': <module at remote 0x7ffff69b7a10>, 'model': <StanModel(lib_path='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', stanlib=<CDLL(_name='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', _FuncPtr=<_ctypes.PyCFuncPtrType at remote 0x55555600b0f0>, _handle=93825003467936, construct=<_FuncPtr(__name__='construct') at remote 0x7ffff3bc3340>, name=<_FuncPtr(__name__='name') at remote 0x7ffff3bc3400>, param_num=<_FuncPtr(__name__='param_num') at remote 0x7ffff3bc34c0>, param_unc_num=<_FuncPtr(__name__='param_unc_num') at remote 0x7ffff3bc3580>, param_names=<_FuncPtr(_...(truncated), locals=<optimised out>) at ../Python/ceval.c:1134
#25 0x00005555557b8e18 in run_eval_code_obj (tstate=0x555555b5ca60, co=0x7ffff6c473c0,
    globals={'__name__': '__main__', '__doc__': None, '__package__': None, '__loader__': <SourceFileLoader(name='__main__', path='/home/alecks/git/bridgestan/python/simplex_test.py') at remote 0x7ffff6c2d2a0>, '__spec__': None, '__annotations__': {}, '__builtins__': <module at remote 0x7ffff6df85e0>, '__file__': '/home/alecks/git/bridgestan/python/simplex_test.py', '__cached__': None, 'bs': <module at remote 0x7ffff6c87920>, 'np': <module at remote 0x7ffff69b7a10>, 'model': <StanModel(lib_path='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', stanlib=<CDLL(_name='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', _FuncPtr=<_ctypes.PyCFuncPtrType at remote 0x55555600b0f0>, _handle=93825003467936, construct=<_FuncPtr(__name__='construct') at remote 0x7ffff3bc3340>, name=<_FuncPtr(__name__='name') at remote 0x7ffff3bc3400>, param_num=<_FuncPtr(__name__='param_num') at remote 0x7ffff3bc34c0>, param_unc_num=<_FuncPtr(__name__='param_unc_num') at remote 0x7ffff3bc3580>, param_names=<_FuncPtr(_...(truncated),
    locals={'__name__': '__main__', '__doc__': None, '__package__': None, '__loader__': <SourceFileLoader(name='__main__', path='/home/alecks/git/bridgestan/python/simplex_test.py') at remote 0x7ffff6c2d2a0>, '__spec__': None, '__annotations__': {}, '__builtins__': <module at remote 0x7ffff6df85e0>, '__file__': '/home/alecks/git/bridgestan/python/simplex_test.py', '__cached__': None, 'bs': <module at remote 0x7ffff6c87920>, 'np': <module at remote 0x7ffff69b7a10>, 'model': <StanModel(lib_path='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', stanlib=<CDLL(_name='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', _FuncPtr=<_ctypes.PyCFuncPtrType at remote 0x55555600b0f0>, _handle=93825003467936, construct=<_FuncPtr(__name__='construct') at remote 0x7ffff3bc3340>, name=<_FuncPtr(__name__='name') at remote 0x7ffff3bc3400>, param_num=<_FuncPtr(__name__='param_num') at remote 0x7ffff3bc34c0>, param_unc_num=<_FuncPtr(__name__='param_unc_num') at remote 0x7ffff3bc3580>, param_names=<_FuncPtr(_...(truncated)) at ../Python/pythonrun.c:1291
#26 0x00005555557b1c6b in run_mod (mod=<optimised out>, filename=<optimised out>,
    globals={'__name__': '__main__', '__doc__': None, '__package__': None, '__loader__': <SourceFileLoader(name='__main__', path='/home/alecks/git/bridgestan/python/simplex_test.py') at remote 0x7ffff6c2d2a0>, '__spec__': None, '__annotations__': {}, '__builtins__': <module at remote 0x7ffff6df85e0>, '__file__': '/home/alecks/git/bridgestan/python/simplex_test.py', '__cached__': None, 'bs': <module at remote 0x7ffff6c87920>, 'np': <module at remote 0x7ffff--Type <RET> for more, q to quit, c to continue without paging--
69b7a10>, 'model': <StanModel(lib_path='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', stanlib=<CDLL(_name='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', _FuncPtr=<_ctypes.PyCFuncPtrType at remote 0x55555600b0f0>, _handle=93825003467936, construct=<_FuncPtr(__name__='construct') at remote 0x7ffff3bc3340>, name=<_FuncPtr(__name__='name') at remote 0x7ffff3bc3400>, param_num=<_FuncPtr(__name__='param_num') at remote 0x7ffff3bc34c0>, param_unc_num=<_FuncPtr(__name__='param_unc_num') at remote 0x7ffff3bc3580>, param_names=<_FuncPtr(_...(truncated),
    locals={'__name__': '__main__', '__doc__': None, '__package__': None, '__loader__': <SourceFileLoader(name='__main__', path='/home/alecks/git/bridgestan/python/simplex_test.py') at remote 0x7ffff6c2d2a0>, '__spec__': None, '__annotations__': {}, '__builtins__': <module at remote 0x7ffff6df85e0>, '__file__': '/home/alecks/git/bridgestan/python/simplex_test.py', '__cached__': None, 'bs': <module at remote 0x7ffff6c87920>, 'np': <module at remote 0x7ffff69b7a10>, 'model': <StanModel(lib_path='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', stanlib=<CDLL(_name='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', _FuncPtr=<_ctypes.PyCFuncPtrType at remote 0x55555600b0f0>, _handle=93825003467936, construct=<_FuncPtr(__name__='construct') at remote 0x7ffff3bc3340>, name=<_FuncPtr(__name__='name') at remote 0x7ffff3bc3400>, param_num=<_FuncPtr(__name__='param_num') at remote 0x7ffff3bc34c0>, param_unc_num=<_FuncPtr(__name__='param_unc_num') at remote 0x7ffff3bc3580>, param_names=<_FuncPtr(_...(truncated), flags=<optimised out>, arena=<optimised out>) at ../Python/pythonrun.c:1312
#27 0x00005555557b8b65 in pyrun_file (fp=fp@entry=0x555555b5ee30, <EMAIL_ADDRESS>start=start@entry=257,
    globals=globals@entry={'__name__': '__main__', '__doc__': None, '__package__': None, '__loader__': <SourceFileLoader(name='__main__', path='/home/alecks/git/bridgestan/python/simplex_test.py') at remote 0x7ffff6c2d2a0>, '__spec__': None, '__annotations__': {}, '__builtins__': <module at remote 0x7ffff6df85e0>, '__file__': '/home/alecks/git/bridgestan/python/simplex_test.py', '__cached__': None, 'bs': <module at remote 0x7ffff6c87920>, 'np': <module at remote 0x7ffff69b7a10>, 'model': <StanModel(lib_path='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', stanlib=<CDLL(_name='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', _FuncPtr=<_ctypes.PyCFuncPtrType at remote 0x55555600b0f0>, _handle=93825003467936, construct=<_FuncPtr(__name__='construct') at remote 0x7ffff3bc3340>, name=<_FuncPtr(__name__='name') at remote 0x7ffff3bc3400>, param_num=<_FuncPtr(__name__='param_num') at remote 0x7ffff3bc34c0>, param_unc_num=<_FuncPtr(__name__='param_unc_num') at remote 0x7ffff3bc3580>, param_names=<_FuncPtr(_...(truncated),
    locals=locals@entry={'__name__': '__main__', '__doc__': None, '__package__': None, '__loader__': <SourceFileLoader(name='__main__', path='/home/alecks/git/bridgestan/python/simplex_test.py') at remote 0x7ffff6c2d2a0>, '__spec__': None, '__annotations__': {}, '__builtins__': <module at remote 0x7ffff6df85e0>, '__file__': '/home/alecks/git/bridgestan/python/simplex_test.py', '__cached__': None, 'bs': <module at remote 0x7ffff6c87920>, 'np': <module at remote 0x7ffff69b7a10>, 'model': <StanModel(lib_path='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', stanlib=<CDLL(_name='/home/alecks/git/bridgestan/test_models/simplex/simplex_model.so', _FuncPtr=<_ctypes.PyCFuncPtrType at remote 0x55555600b0f0>, _handle=93825003467936, construct=<_FuncPtr(__name__='construct') at remote 0x7ffff3bc3340>, name=<_FuncPtr(__name__='name') at remote 0x7ffff3bc3400>, param_num=<_FuncPtr(__name__='param_num') at remote 0x7ffff3bc34c0>, param_unc_num=<_FuncPtr(__name__='param_unc_num') at remote 0x7ffff3bc3580>, param_names=<_FuncPtr(_...(truncated), closeit=closeit@entry=1, flags=0x7fffffffdeb8) at ../Python/pythonrun.c:1208
#28 0x00005555557b8048 in _PyRun_SimpleFileObject (fp=0x555555b5ee30, filename='/home/alecks/git/bridgestan/python/simplex_test.py', closeit=1, flags=0x7fffffffdeb8) at ../Python/pythonrun.c:456
#29 0x00005555557b7d43 in _PyRun_AnyFileObject (fp=0x555555b5ee30, filename='/home/alecks/git/bridgestan/python/simplex_test.py', closeit=1, flags=0x7fffffffdeb8) at ../Python/pythonrun.c:90
#30 0x00005555557a917e in pymain_run_file_obj (skip_source_first_line=0, filename='/home/alecks/git/bridgestan/python/simplex_test.py', program_name='/usr/bin/python3') at ../Modules/main.c:353
#31 pymain_run_file (config=0x555555b40f60) at ../Modules/main.c:372
#32 pymain_run_python (exitcode=0x7fffffffdeb4) at ../Modules/main.c:587
#33 Py_RunMain () at ../Modules/main.c:666
#34 0x000055555577f0dd in Py_BytesMain (argc=<optimised out>, argv=<optimised out>) at ../Modules/main.c:720
#35 0x00007ffff7c79d90 in __libc_start_call_main (main=main@entry=0x55555577f0a0 <main>, argc=argc@entry=2, argv=argv@entry=0x7fffffffe0c8) at ../sysdeps/nptl/libc_start_call_main.h:58
#36 0x00007ffff7c79e40 in __libc_start_main_impl (main=0x55555577f0a0 <main>, argc=2, argv=0x7fffffffe0c8, init=<optimised out>, fini=<optimised out>, rtld_fini=<optimised out>, stack_end=0x7fffffffe0b8)
    at ../csu/libc-start.c:392
#37 0x000055555577efd5 in _start ()

Apologies if that's not what you meant

No that’s exactly what I wanted, sadly it doesn’t point me toward anything too specific.  We recently changed some of the code mentioned there in #41. If you git pull and rebuild does the segfault still occur?

Segfault is gone! How strange.
Thanks!

I think we had some very subtle UB in our memory management before that PR, which maybe later versions of GCC brought out. Glad it’s fixed!


privacy manifest required

See https://github.com/pointfreeco/swift-composable-architecture/discussions/2559#discussioncomment-8005185
I don't believe SwiftUIIntrospect leverages any APIs that require a privacy manifest, and it definitely doesn't collect any user data. Correct me if I'm wrong though.
Originally posted by @davdroman in https://github.com/siteline/swiftui-introspect/discussions/398#discussioncomment-8262451

Sorry, but even the SDK collect no data, the sdk must contain the manifest which say explicitly it doesn't collect data. Even RxSwift must contain the maniest

The library should provide Privacy Manifest if it collects information or access "Required Reasons API"

I'm getting emails back from Apple about this because your library is not compliant.

ITMS-91053: Missing API declaration - Your app’s code in the “YourApp” file references one or more APIs that require reasons, including the following API categories: NSPrivacyAccessedAPICategoryUserDefaults. While no action is required at this time, starting May 1, 2024, when you upload a new app or app update, you must include a NSPrivacyAccessedAPITypes array in your app’s privacy manifest to provide approved reasons for these APIs used by your app’s code. For more details about this policy, including a list of required reason APIs and approved reasons for usage, visit: https://developer.apple.com/documentation/bundleresources/privacy_manifest_files/describing_use_of_required_reason_api.

UserDefaults is not used anywhere in this library.

@davdroman to reproduce it, create an empty project, integrate SwiftUI-Introspect, and then attempt to publish it. Within a few minutes, you will automatically receive that email from Apple

@davdroman, you're absolutely right. While the core functionality of the package doesn't rely on UserDefaults, I discovered that the SimulatorStatusMagic dependency actually utilizes UserDefaults.

@davdroman maintainer of SSM here, I'm just getting into this via a ping from @Muhammadbarznji (thanks again!). My assumption is that as a framework that's not shipped with the product, but just used for testing, I don't need to worry about the privacy manifest. Does that sound right? Was your fix just to remove it from release builds of SwiftUIIntrospect? Trying to figure out if I need to do anything more here.


feat: contract manager resubmit #ntrn-84

https://hadronlabs.atlassian.net/browse/NTRN-84

https://github.com/neutron-org/neutron-tests/actions/runs/5896212533

https://github.com/neutron-org/neutron-tests/actions/runs/5896234877

TODO_RELAYER_NODE

https://github.com/neutron-org/neutron-tests/actions/runs/5929600149

https://github.com/neutron-org/neutron-tests/actions/runs/5936584543

https://github.com/neutron-org/neutron-tests/actions/runs/5939048525

https://github.com/neutron-org/neutron-tests/actions/runs/5939743946

https://github.com/neutron-org/neutron-tests/actions/runs/5998807948


App: reimplement React UI per new designs

We have a bunch of amazing Figma mocks we need to translate to HTML + CSS.

Almost same as https://github.com/webaverse/app/issues/1915
Closing.


Named exports from ol/index.js

This adds named exports to ol/index.js.  For backwards compatibility, the default export is an object with all of the old API properties.  Internally, we only use the named exports.

I am so happy to see us finally moving in this direction. Thanks Andreas and Tim!
I hope to cut some time tomorrow for looking into this, if you review each other before that, that is fine as well.


Add RuboCop

Add RuboCop check to Danger
Also remove travis config

Codecov Report

Merging #115 into development will not change coverage.
The diff coverage is n/a.

@@             Coverage Diff              @@
##           development     #115   +/-   ##
============================================
  Coverage        70.69%   70.69%
============================================
  Files               33       33
  Lines             1522     1522
============================================
  Hits              1076     1076
  Misses             446      446

Continue to review full report at Codecov.

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Running inference without gradio

Hi,
Thank you for the fantastic work.
I would like to ask if there is a way to run inference without gradio.
My goal is to give a desired pose for the diffusion guidance and just obtain a novel view of the image saved in some dir.
Thank you in advance

I haven't tested this code.
good luck :)
predict.zip

Thank you very much!
I will test it asap

Thank you very much! I will test it asap

can you inference with this file? thanks!

Hello
Yes the code works fine.
Just on the line in which the concatenation is performed
c = torch.cat([c, T], dim=-1)
should be substituted by
c = torch.cat([c, T], dim=-1).float()
In my case it throws an error for type mismatching.
predict.zip

Could you tell me if the code can generate new views for a batch images?  My goal is to give a batch images and a batch poses, and generate one view for every image from a batch.

@yesterday-Luo
The code is meant to generate one novel view given one image and one pose.
However, I think that it should be straightforward to adapt it for your use case, by just creating a for-loop for the batch of images-poses.


[Feature] : Add subscribe to NewsLetter

Description
Adding subscribe to news letter
Screenshots
No response
Checklist

[X] I have checked the existing issues.
[X] I follow Contributing Guidelines of this project.
[X] I am a GSSoC'24 contributor.
[X] I want to work on this issue.

Code of Conduct

[X] I agree to follow this project's "Code of Conduct".

@CSEdgeOff  please assign me the issue

@Saipradyumnagoud
the same issue #398 was already open you need to use the code we provided their

No need To take input of email ? @CSEdgeOff

it looks like ths @CSEdgeOff

@Saipradyumnagoud Yes Basically the code was provided by LinkedIn Place it in a good spot like below About us description
That make looks good

@CSEdgeOff  yeah sure


feat: AlibabaCloud-EIP support to define EIP name & description

Codecov Report

Merging #91 (6a74cee) into master (1b05801) will decrease coverage by 0.04%.
The diff coverage is 0.00%.

:exclamation: Your organization is not using the GitHub App Integration. As a result you may experience degraded service beginning May 15th. Please install the Github App Integration for your organization. Read more.
@@            Coverage Diff             @@
##           master      #91      +/-   ##
==========================================
- Coverage   29.30%   29.26%   -0.04%
==========================================
  Files          19       19
  Lines        2464     2467       +3
==========================================
  Hits          722      722
- Misses       1697     1700       +3
  Partials       45       45

Flag
Coverage Δ

unittests
29.26% <0.00%> (-0.04%)
:arrow_down:

Flags with carried forward coverage won't be shown. Click here to find out more.

Files Changed
Coverage Δ

cloudprovider/alibabacloud/eip.go
5.97% <0.00%> (-0.28%)
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@chrisliu1995 更新官网文档后合并。


Issue while installing in mac

I have tried changing the compiler args to C++11 too in the setup.py file.
OS: MAC OS High Sierra
clang-1<IP_ADDRESS>

For O

#Refer


Invalid GeoJSON

My GeoJSON wasn't rendering properly in combination with geojson-vt, and after filing a bug with them, they identified that the GeoJSON from geojsoncontour was not valid.
https://github.com/mapbox/tippecanoe/issues/580

The fundamental problem is that many of the outer polygon rings are marked in the GeoJSON as being interior rings.
o  For Polygons with more than one of these rings, the first MUST be
the exterior ring, and any others MUST be interior rings.  The
exterior ring bounds the surface, and the interior rings (if
present) bound holes within the surface.
Ignoring the GeoJSON spec and detecting inner/outer rings by winding rather than by ring order within the geometry gives the intended result:

Can this be fixed within geojsoncontour?

@Plantain Thank you for reporting this issue and sorry for my late reply.
From what I understand, this should be fixed in geojsoncontour.
@ucyo wrote the conversion to polygons. I am not sure how much work it is to fix this. I hope to find some time to have a look at it, but don't count on it.
Here is the related code: https://github.com/bartromgens/geojsoncontour/blob/79e30718fa0c1d96a2459eb1f45d06d699d240ed/geojsoncontour/contour.py#L68
PRs are more than welcome!

Hi, we bumped into this as well. Here is a minimal example that demonstrates the problem using the validation feature from the shapely library:
import numpy as np
import matplotlib.pyplot as plt
import shapely.geometry
import json
import geojsoncontour

arr = np.array([
    [0, 1, 0],
    [1, 1, 1],
    [0, 1, 0],
])

contour = plt.contourf(arr)
geodata = geojsoncontour.contourf_to_geojson(contour, serialize=False)
for feature in geodata["features"]:
    print(shapely.geometry.asShape(feature["geometry"]).is_valid)

This code prints False for each feature except the last one.
In case it might help, my coworker managed to fix the GeoJSON afterwards using this code:
for n  in np.arange(0, len(geodata['features'])):
    poly = shapely.geometry.asPolygon(geodata['features'][n]["geometry"]["coordinates"][0][0])
    for i in np.arange(0, len(geodata['features'][n]["geometry"]["coordinates"])):
        for k in np.arange(1, len( geodata['features'][n]["geometry"]["coordinates"][i])):
            n_poly = shapely.geometry.asPolygon(geodata['features'][n]["geometry"]["coordinates"][i][k])
            if poly.contains(n_poly):
                poly = poly.difference(n_poly)
            else:
                poly = poly.union(n_poly)
    geodata["features"][n]["geometry"] = poly.__geo_interface__

@MarySymons Thanks for the update. There is no progress on this issue :( I would like to dive into it but cannot find the time right now.
@amarandon Thanks for the minimal example that demonstrates the problem. I hope to give it a try soon.

Update for you... I have used @amarandon's colleagues fix using shapely and it works for my problem too! Combining these things isn't particularly efficient as you can imagine, but it gets my desired outcome :)

Any chance of taking a look at this @bartromgens ? I am using a very inefficient workaround, and so far I haven't been able to understand the code to come up with a better fix.

Hi @Plantain,
original author of the polygon converter here. Next month I will have more spare time and will work on this 👍

I had a look at this issue and found the following issues with the current multipolygon representation in comparison to the geojson standard:

A single contour level is currently represented as single Polygon of multiple LineStrings (linear rings) inside a MultiPolygon, instead of multiple Polygons
geojson only considers the first LineString of a Polygon as exterior ring, all others are interior rings (holes)
Hole coordinates should be defined clockwise

Things to check/fix:

Independent areas (exterior rings) of a single level should be individual Polygons inside a MultiPolygon

This simply means moving the coordinate list one level up in the coordinates of the MultiPolygon. This works, but ignores holes, which become independent exterior rings.

Holes should be defined as part of a single Polygon

The first linear ring of a Polygon is the exterior ring
How to know when a matplotlib Path is a hole?

Holes should be defined clockwise

This seems to pose no real problem in most implementations if the two points above are fixed

Relevant geojson documentation:

A linear ring MUST follow the right-hand rule with respect to the
area it bounds, i.e., exterior rings are counterclockwise, and
holes are clockwise.

For Polygons with more than one of these rings, the first MUST be
the exterior ring, and any others MUST be interior rings.  The
exterior ring bounds the surface, and the interior rings (if
present) bound holes within the surface.

https://www.rfc-editor.org/rfc/rfc7946.html#section-3.1.6

@bartromgens thank you for the research. It seems that „simply“ the ordering/direction of the Polygons are the problem. Matplotlib seems not to care about the specific order contrary to GeoJSON. But this seems reasonable since matplotlib does not support „holes“ in polygons as GeoJSON interprets different clockwise directions as an indicator for this. Anyway... soon I’ll have spare time and work on this 😺

It seems the winding is fine, because using the --use-source-polygon-winding flag on tippecanoe makes it work with geojsoncontour just fine https://github.com/mapbox/tippecanoe/issues/580 &  https://github.com/mapbox/tippecanoe/pull/581

I tried to fix the issues by simply making every matplotlib path its own Polygon inside the MultiPolygon (instead of a Polygon with multiple LineStrings).
In this case, http://geojson.io rendered the holes as filled areas while http://geojson.tools rendered the holes correct.
Likely because the winding is indeed correct (holes clockwise, exterior ccw), but geojson.io requires the holes to be part of a Polygon in which it is a hole, as by the standard.
The real problem is knowing when a path is a hole (check winding?) and to which exterior this belongs. If we have this information, it is fairly easy to create the correct MultiPolygon.

I tried reordering the polygons manually through sorting by winding so the clockwise winding was always the exterior, but it still doesn't seem valid and I'm not sure why:
def ccw(a):
return (shapely.geometry.LinearRing(a).is_ccw)
polygon.coordinates[0] = sorted(polygon.coordinates[0], key=ccw)

I think I have a fix for this issue. Need to debug one last problem observed by OP (@Plantain). Then I will submit a pull request.

Pull Request #14 submitted

Fixed by @veloman-yunkan in PR #14.
Will release a new version later today.


Fix bug

2x the speed!
The variable was defined, just not used, leading to double the work done.

Uh strange, it seems like https://github.com/raybellwaves/xskillscore/pull/171/files doesn't exist in master?

Good spot @ahuang11. Don't forget to update the CHANGELOG

Thanks @ahuang11


Add flux-local hr diff command

Add flux-local hr diff command, and update the documentation.
This includes a breaking change to the path argument, making it an optional flag rather than an optional positional.
Issue #35

Codecov Report

Merging #57 (7088db2) into main (21c2adb) will increase coverage by 0.21%.
The diff coverage is 92.59%.

@@            Coverage Diff             @@
##             main      #57      +/-   ##
==========================================
+ Coverage   91.35%   91.57%   +0.21%
==========================================
  Files          14       14
  Lines         671      724      +53
==========================================
+ Hits          613      663      +50
- Misses         58       61       +3

Impacted Files
Coverage Δ

flux_local/tool/diff.py
91.17% <92.15%> (+0.98%)
:arrow_up:

flux_local/git_repo.py
98.05% <100.00%> (+0.97%)
:arrow_up:

flux_local/helm.py
98.03% <100.00%> (+0.08%)
:arrow_up:

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Get selected completion/get code as if it was selected

I'm experimenting with using Monaco zones for live-previewing data that is calculated in the script written in my language hosted in Monaco editor. It all works neatly :).
The one thing that is tricky is that when you are typing code and using auto-completion, you often end up with invalid code (that's fine, I can deal with that), but when the user is selecting option in auto-complete, I would like to be notified about it and get code "as if the option was selected". A gif to illustrate this:

As you can see, the zone displays preview based on the current cursor position. When you start typing, it still parses the code, but it has no idea about the selected option in the auto-complete.
Is there a way to get the current selection so that I can render preview based on the selected option?

AFAIK the suggest widget does not expose in any API the current selected suggestion. fyi @jrieken @joaomoreno

You could use the resolve command for that, though it might have some quirks.


Debouncing Support ?

Is there a possibility of adding a debounce strategy (with an upper limit) ? E.g. debounce changes for 50ms with a hard limit of 500ms. The diff would be between the value at the start of the debounce period (since thats the version matching the client) and the value at the end of the period.
As a use case I'm building an api to a queueing engine, and certain queries can get chatty at high concurrency. Most of the values I'm monitoring are gauges/counters and other entities for which from a dashboard perspective intermediate values (within a certain granularity) are not important.

I think the correct term is throtteling? I would accept a contribution for this 😇

Not saying I'm committing to this :-), but where's a good place to start ?

This is the function that could be debounced: https://github.com/n1ru4l/graphql-live-query/blob/3eca29866c8e7046bfd2f00c342dbb4a93e24693/packages/in-memory-live-query-store/src/InMemoryLiveQueryStore.ts#L269

Hey @n1ru4l , could you have a quick look at https://github.com/ccollie/graphql-live-query/commit/929e67  to see if this is a viable direction?
Or should I just go ahead with a PR ?
BTW, I'm still figuring out the tests for InMemoryLiveQueryStore

@ccollie Feel free to open a PR so I can comment on that and start the conversation!

This is now published 😎

@n1ru4l thanks for the followthrough. I've been knee-deep in projects the past month.


Option to change "orient to sketch" behavior off or on

Low priority.
Mentioned here.
https://github.com/KittyCAD/modeling-app/discussions/477#discussioncomment-7539125
This would give the user a checkbox (or equivalent) to turn off the default behavior of orienting to the sketch plane after selecting "new sketch".
Current Default Example:
https://github.com/KittyCAD/modeling-app/assets/114548659/36b3392a-cb7b-4282-9cbc-0b19289ae0cb
Video is sped up quite a bit because latency was pretty bad on the plane
Some users prefer not to sketch normal to the plan all the time. The setting option would remove the default behavior in the video

reference this in a new engine issue plz


update installation guide

It seems that latest version is 0.5.3. README.md guide line should be fixed :)

Thank you @engkimbs , merged.


Crash when RecursiveError should be thrown

class C():
    @property
    def x(self):
        return self.x
C().x

See here; same if running as a file (main) or from within IPython.
Restarting kernel later rather than sooner, it's non-responsive, so I closed the terminal - yielding this:

Closing again worked properly; opened Console 3/A.

This is rather strange as some users reported reproducing it from terminal - opened parallel IPython Issue.

This also crashes:
def f(*args):
    f(*args)
f()

but THESE don't, and properly throw RecursionError:
def f():
    f()
f()

def f(x):
    f(x)
f(5)

@impact27 do you know what might be going on? Thanks!

I tried it on macOS and it raises RecursionError

I think the IPKernelApp warning should not prevent the console from being reopened, it is confusing for the user.

@OverLordGoldDragon, since your code generates a kernel crash on Windows, the only thing we can do is to properly restart it.
That's not happening right now because we're showing the message about comms displayed in your screenshot above. However, it'll be fixed in PR #12972.

I can confirm this is a problem in IPython (not in Python), so it has to be fixed there.

@ccordoba12 How would one test if it's "pure Python" that fails? Run python file.py from terminal?

I started a Python interpreter in a terminal and introduced by hand your first example.

@ccordoba12 Last comment here confirms reproducing it in terminal (also slightly up: "but from Windows terminal").  I, however, can't reproduce it. There were some steps posted in IPython that I'll try today, for reference.

I could reproduce it on IPython terminal and the IPython maintainer mentioned a workaround for it.


[BUG] Docker Compose dev environment fails to setup hyperswitch-server

Bug Description
hyperswitch-hyperswitch-server-1 container stops abruptly without spinning up the server.  Container can't find protobuf-compiler debian package and fails. Below are the logs of the container
➜  hyperswitch git:(main) docker logs hyperswitch-hyperswitch-server-1

Reading package lists...
Building dependency tree...
Reading state information...
E: Unable to locate package protobuf-compiler

Protobuf compiler mentioned here https://github.com/juspay/hyperswitch/blob/a3c2694943a985d27b5bc8b0371884d17a6ca34d/docker-compose-development.yml#L64
Expected Behavior
hyperswitch-hyperswitch-server-1 should run
Actual Behavior
Container simply exits
➜  hyperswitch git:(main) docker ps -a
CONTAINER ID   IMAGE                                           COMMAND                  CREATED         STATUS                          PORTS                                                 NAMES
3569baada69f   rust:latest                                     "apt-get install -y …"   3 minutes ago   Exited (100) 3 minutes ago                                                            hyperswitch-hyperswitch-server-1

Steps To Reproduce

Clone the repo on a new machine
Run docker compose --file docker-compose-development.yml up -d

Context For The Bug
No response
Environment
Are you using hyperswitch hosted version? No
If yes, please provide the value of the x-request-id response header to help us debug your issue.
If not (or if building/running locally), please provide the following details:

Operating System or Linux distribution: Debian 12

Have you spent some time checking if this bug has been raised before?

[X] I checked and didn't find a similar issue

Have you read the Contributing Guidelines?

[X] I have read the Contributing Guidelines

Are you willing to submit a PR?
Yes, I am willing to submit a PR!

Hey @akhildevelops
Thanks for participating!
Kindly fill this form once all of your PRs are merged.


[Bug] Fix the flink on k8s application build failed and savepointPath saved failed bug when use h2 as database

fix the flink on k8s application build failed and savepointPath save failed bug when use h2 as database

Problem Summary:

because the initSetting has @PostConstruct in SettingServiceImpl class ,the variable settings size is 0 when  streampark console start.
so when update setting the code settings.get(setting.getSettingKey()).setSettingValue(value) will case Nullpoint Exception and the variable settings'size will  be 0 Always.

the table t_flink_savepoint in H2 missing a column 'chk_id'。

What is changed and how it works?
Proposal: xxx
Feel free to ping committers for the review!
Contribution Checklist

Make sure that the pull request corresponds to a GITHUB issue.

Name the pull request in the form "[Feature] [component] Title of the pull request", where Feature can be replaced by Hotfix, Bug, etc.

Minor fixes should be named following this pattern: [hotfix] [docs] Fix typo in README.md doc.

Purpose of this pull request

@wolfboys PTAL


feat(TokenRegistry.t.sol)

Motivation
Test TokenRegistry.sol
Solution
Write tests for running tests using Foundry
PR Checklist

[x] Added Tests
[x] Updated Documentation
[x] Updated CHANGELOG.md for the appropriate package

Yes, it’s the representation of a remote token.
Le 26 sept. 2022 à 2:45 PM -0400, James Prestwich @.***>, a écrit :

@prestwich commented on this pull request.
In packages/contracts-bridge/contracts/test/BridgeRouter.t.sol:

     senderDomain = localDomain;

    receiverDomain = remoteDomain;

   remoteToken = BridgeToken(remoteTokenLocalAddress);

this is a representation token, not a remote token
—
Reply to this email directly, view it on GitHub, or unsubscribe.
You are receiving this because you were assigned.Message ID: @.***>

Yes, it’s the representation of a remote token.

yes. it is a representation token, and it is not a remote token, which is why the variable name was confusing to me


Nested documents unexpected behavior

Hello, I wrote the question already on stackoverflow:
http://stackoverflow.com/questions/41353024/couchbase-lite-android-unexpected-behavior
Basically :

Query all records, I get all documents with nested objects
Change condition, execute same query, no results (expected)
Do first query again (query all records) with working condition, I get all documents WITHOUT nested objects

What could cause such behavior?
Is this expected or a major bug?

It seems that question is handled on stackoverflow.


Portainer 2.17.0 Business Edition no longer able to recreate containers - Error 500

Previously version 2.16 I could click on a container in Portainer, click on recreate, and then select to pull a new image - everything worked just fine.
Recently when I try this, I'll get a spinning circle in the top right of the screen, and after a minute or two I'll get an error message saying;
Failure
Request failed with status code 500

The container will then be restarted with the original non-updated image, although the image will show up as having been renamed from its original name to a hex string such as fdf04daf6952.

Can confirm this.
You can workaround by pulling the latest image first, then recreate the container without the "Re-Pull image" switch.

@socza
Thank you for the information.  I am currently investigating.  I will update you as I learn more.
Thanks!

@socza
Can you please open the Web Developer Tools >> open up the Network tab >> and screenshot the Request and Response for review?
Thanks!

I was the original reporter on Reddit.  This happened on every container I’ve tried to update so far.

This happens on specific containers, e.g. "minio" (I have it deployed too), "gitlab-ce", gitlab-runner", "jenkins".
They are all tagged with "latest".
As you wrote eg "registry:2" action "recreate" works.

I was the original reporter on Reddit. This happened on every container I’ve tried to update so far.

Yes, I copied your post and pasted it on github.
Sorry, I wanted to report a case quickly.

I was the original reporter on Reddit. This happened on every container I’ve tried to update so far.

@Andrew-H2O Yes, I copied your post and pasted it on GitHub. Sorry, I wanted to report a case quickly (I didn't want to describe the problem again on GitHub).  ;)

Haha, it’s all good - I was just establishing my credentials :)

@socza
The containers you mentioned: "minio", "gitlab-ce", gitlab-runner", "jenkins" Were these created via docker run or via the Portainer UI?
Thanks!

The containers were created via docker run.

Update:
Upon further testing, this only occurs on containers that were created via docker run  and not Portainer.
I have forwarded this information to the team for review.
Thanks!

Happens to me on containers built in Portainer (stacks/web ui). Whether containers/stacks are on the host (win 10 / wsl2) or agents (synology).

@theRealKLH
Please provide container example for further review.
Thanks!

Hi
I have the same problem. For containers I have not yet tried to update via the Pull new Image button as usual, if I first pulle the image and then Recreate it works. Unfortunately, this does not work for those containers that I have already tried before.
Can someone help me?
Thanks!

We've just released 2.17.1 which should fix this issue - are you able to update and retest?

We've just released 2.17.1 which should fix this issue - are you able to update and retest?

Just updated and tested - it worked as expected.  Thanks for the fix!

Yes, I confirm it works correct.

For me it's the same error again...
Von: James Carppe @.>
Gesendet: Mittwoch, 22. Februar 2023 03:58
An: portainer/portainer @.>
Cc: Kassel Marco Daniel Andrin BZBS INS20a @.>; Comment @.>
Betreff: Re: [portainer/portainer] Portainer 2.17.0 Business Edition no longer able to recreate containers - Error 500 (Issue #8507)
Sie erhalten nicht oft eine E-Mail von<EMAIL_ADDRESS>Erfahren Sie, warum dies wichtig isthttps://aka.ms/LearnAboutSenderIdentification
We've just released 2.17.1 which should fix this issue - are you able to update and retest?

Reply to this email directly, view it on GitHubhttps://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fportainer%2Fportainer%2Fissues%2F8507%23issuecomment-1439369789&data=05|01|marco.kassel%40stud.bzbs.ch|1aa1a18025a24f8637c408db148094d9|5daf41bd338c4311b1b0e1299889c34b|0|0|638126314708616069|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D|3000|||&sdata=OcBUNpvgE5uGMVN14O9%2BJBsvqm2L5go1QjU2btWTFtA%3D&reserved=0, or unsubscribehttps://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-auth%2FA5YDIFA2A5ITK4X6PET4ONDWYV6CXANCNFSM6AAAAAAU54MC2U&data=05|01|marco.kassel%40stud.bzbs.ch|1aa1a18025a24f8637c408db148094d9|5daf41bd338c4311b1b0e1299889c34b|0|0|638126314708616069|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D|3000|||&sdata=Ss9I1q5FjKRkp8kZD%2B92ofZu5Kl%2FktyIaEeE2g%2BCXs4%3D&reserved=0.
You are receiving this because you commented.Message ID<EMAIL_ADDRESS>

@marco-kasl
Can you provide the following:
[1] What are the container images
[2] How did you create the containers
[3] Web Developer Tools >> open up the Network tab >> and screenshot the Request and Response for review
I have 2 containers minio ldap that I had initially created via docker run that were not able to be re-created in 2.17.0.  Upon upgrade, I am no longer seeing the 500 error.
https://user-images.githubusercontent.com/20426210/220763497-ae452c83-aa69-465e-ad70-d288e7f2194c.mov
Thanks!

Problem still present in 2.17.1 with containers deployed trough the stack feature in portainer (not via docker run). Recreate container with re-pull fails with code 500, while updating the stack (containing the target container) with re-pull works as intended, which is what I'm using as a workaround.

@Jikeh
I performed the following:
[1] Create Wordpress Stack
[2] Re-create wordpress-wordpress-1 without re-pull
[3] No Error
[4] Re-create wordpress-wordpress-1 with re-pull
[5] No Error
https://user-images.githubusercontent.com/20426210/220787941-2cdcf083-27cd-4fe7-9df0-bc3d166483cc.mov
https://user-images.githubusercontent.com/20426210/220787975-f6c6aa19-10bc-4c83-9cc8-dc226309adde.mov
Can you provide the following:
[1] What are the container images
[2] How did you create the containers
[3] Web Developer Tools >> open up the Network tab >> and screenshot the Request and Response for review
Thanks!

Sure thing.
I also created a wordpress stack and I got no errors when recreating it, so I thought it was a problem with my config and I played around. I found out that containers with 0-1 networks can be recreated, while containers with multiple networks attached cannot (error 500). All containers in my setup (except for Portainer itself) are deployed through stacks.
And in fact, testing recreation on a simple cointainer (mpepping/cyberchef) with 2 networks got the following response message:
{"message":"Error recreating container","details":"create container error: Error response from daemon: Container cannot be connected to network endpoints: cyberchef-net, nginx-proxy-manager-net"}
Should I open another issue or do you thing it is related?

@theRealKLH
Please provide container example for further review.
Thanks!

ooof.. sorry for the late reply. AFK since posting. Before coming back here, saw there was an upgrade to 2.17.1. Applied it and same outcome. I am seeing the same as @Jikeh both now and prior to upgrading. Stack update w/pull works, but container recreate w/pull does not.
However, my response is different...
{"message":"Error recreating container","details":"pull image error docker.io/willfarrell/autoheal:latest: Cannot connect to the Docker daemon at tcp://<IP_ADDRESS>:9001. Is the docker daemon running?"}
I have also received...
{"message":"Error recreating container","details":"pull image error docker.io/willfarrell/autoheal:latest: context deadline exceeded (Client.Timeout or context cancellation while reading body)"}
It does appear that it is only happening on my 'agent' based systems (2 Synology NAS). I am not able to reproduce it on the stand-alone host (Win 10) even though I'm pretty sure it was acting the same prior to upgrading Portainer. I've tested all containers on that system and they are not showing the issue. I was just about to write that "it's only affecting containers pre-2.17" but I just tried a container that I created via stack post 2.17.1 and it failed. AND tried again just now and it was successful.
So my issue seems to be one of timeout with my agents? Now, is that a "coincidental environmental" issue (net/hw/os-at times my Synos can be bogged down) or a "portainer" issue (app version)? GRIN
I will say that I reverted everything down to 2.16.2 and didn't experience a single failure with the recreate process no matter how many times I tried (still failure until host Portainer system downgraded). Going to try upgrading again.

@Jikeh
Can you share one of your stack's code that is not re-creating the containers and I can test further on my end?
Thanks!

@Jikeh
Can you share one of your stack's code that is not re-creating the containers and I can test further on my end?
Thanks!

There it is:
version: '3.8'
services:
  cyberchef:
    container_name: cyberchef
    image: mpepping/cyberchef
    restart: unless-stopped
    environment:
      - "TZ=Europe/Rome"
    user: 1000:1000
    ports:
      - '10230:8000'
    networks:
      - cyberchef-net
      - nginx-proxy-manager-net

networks:
  cyberchef-net:
    name: cyberchef-net
    driver: bridge

  nginx-proxy-manager-net:
    name: nginx-proxy-manager-net
    driver: bridge

@Jikeh
Thank you for the additional information.  I am able to reproduce.  I have logged an internal request for the unable to re-create containers with multiple networks.  I do not yet have a timeline or release.  I will update you as I learn more.
Thanks!

@Jikeh
Thank you for the additional information. I am able to reproduce. I have logged an internal request for the unable to re-create containers with multiple networks. I do not yet have a timeline or release. I will update you as I learn more.
Thanks!

That's great to hear, thank you!

@kroese
Can you provide the following:
[1] How did you create the container?  docker run or Portainer UI?
[2] Is this container part of a Stack?
[3] Stack code or image tag
Thanks!

I have a similar problem. I added a stack of grafana, prometheus, endlessh and node-exporter and called it "monitoring".

I upgraded my portainer to Business Edition and lost the possibility to edit or see the docker compose code inside the stack

I tried to update grafana to the latest version, but failed with Request failed with status code 500. The latest Image gets downlaoded, but it doesn't get used. The iamge gets renamed to a random hex string.
What I tried and didn't help:

moving the container to another network and retry
recreate without pulling the new container
Duplicate/Edit and then Deploy the container throws Duplicate mount point

I cannot delete the stack without the docker compose code I once put into stack. I cannot reach the docker-compose code because of the upghrade to BE.
First of all, if you have an idea, how to get the docker compose code back, would be awesome. Secondly please explain how to update my grafana container

Also noticed the issue in the latest version along with the errors in the logs which are highlighted in another issue.
The main reason I use Portainer is for the ease of recreating containers and pulling a new image with little effort but the current version just seems to fail at every turn.

I have also experienced this issue. An ETA on the fix would be appreciated.

I solved this problem today with a short run of watchtower. This solved it flawlessly for me.
docker-compose.yml:
version: '3.7'

services:
  watchtower:
    image: containrrr/watchtower
    container_name: watchtower
    restart: unless-stopped
    volumes:
      - /var/run/docker.sock:/var/run/docker.sock:ro
    environment:
      - TZ=Europe/Berlin
      - WATCHTOWER_CLEANUP=true
      - WATCHTOWER_INCLUDE_STOPPED=true
      - WATCHTOWER_POLL_INTERVAL=1800
      - WATCHTOWER_DEBUG=true

@kroese
I created a homeassistance container via docker run with :latest and :stable images
sudo docker run -d   --name homeassistant-2   --privileged   --restart=unless-stopped   -p 8123:8123   -e TZ="Europe/London"   -v homeassistant_config-2:/config   --network=host   ghcr.io/home-assistant/home-assistant:latest
I am able to Recreate without re-pull image and with re-pull image:
https://user-images.githubusercontent.com/20426210/228091449-b71f287d-cebc-4872-9273-f310bdb25ac9.mov
Can you provide the following:
[1] Launch Web Dev Tools >> Network tab
[2] Try recreate
[3] Post screenshots of the Request and Response tabs
[4] What type of network do you create in your docker run?
Thanks!

@GFNiko
Can you post your Stack code and I can test on my end?
@zinkscott
Please provide the following information so I can test your issue:
[1] How did you create the container? docker run or Portainer UI?
[2] Is this container part of a Stack?
[3] Stack code or image tag
Thanks!

@GFNiko
Can you post your Stack code and I can test on my end?

No either there is an export function I couldn't find or, like I already wrote, there is no access to the stack code since I upgraded to portainer-be
It just shows 'limited' in the stack overview

I mostly got those error 500 errors when using re-create without stopping the container first. since I changed my habit to first stopping the containers and then use re-recreate with pull new image the errors are gone.

I have just about give up on this as a solution, that a Business Edition application can have such huge problems for so many weeks without it being fixed or rolled back is ridiculous.

For me it stopped working one i added my account to dockerhub

This happened with 2.18 for me and 2.19.0, but only for containers created via stack. For non-stack containers, I can do recreate + re-pull, but for containers created via stack, I get a 500 and it fails.

can confirm 2.19.0 CE has this issue again. I'm having to change ports every time to get containers back up and running. Just had my portainer freak out and kick 4 apps and have this 500 Status Failure when trying to start them back up.

I feel like this issue may have deviated into a few different scenarios that may be unrelated to each other - unfortunately 500 is a very generic error message. Originally this thread was referring to stacks with containers that were on multiple networks, but I'm not sure if this is the case for all of you experiencing issues now. Those that have posted recently here, can you confirm whether your containers are on multiple networks?

Try this stack. Start it up, wait for an update to either container. Try doing recreate + re-pull on the outdated container and you’ll get a 500.
version: '3.3'
services:
    tailscale:
        hostname: fastenhealth
        image: tailscale/tailscale:latest
        volumes:
            - /volume1/docker/fastenhealth/tailscale:/var/lib/tailscale:rw
        environment:
            - TS_USERSPACE=1
            - TS_STATE_DIR=/var/lib/tailscale
        restart: unless-stopped

    fastenhealth:
        image: ghcr.io/fastenhealth/fasten-onprem:main
        network_mode: service:tailscale
        depends_on:
            - tailscale
        volumes:
            - /volume1/docker/fastenhealth/db:/opt/fasten/db:rw
        restart: unless-stopped

@tamarahenson Just returning to this since Feb. I no longer have the issue "across the board". Now it has become isolated to a single container. That container is homeassistant. Like @kroese I am starting to believe it's some kind of timeout happening. When recreate from containers fail, recreate from stacks usually works, but I have also seen it pull the image but fail to stop/recreate the actual container. The container is left running referencing the "old" image as if I only performed a pull. One of the things I believe helped me was the system I was running back in Feb was kinda on the "slow" side. now on a more powerful NAS (but not TOO powerful I guess).

Not working for me again after updating to 2.19.0

Try this stack. Start it up, wait for an update to either container. Try doing recreate + re-pull on the outdated container and you’ll get a 500.
version: '3.3'
services:
    tailscale:
        hostname: fastenhealth
        image: tailscale/tailscale:latest
        volumes:
            - /volume1/docker/fastenhealth/tailscale:/var/lib/tailscale:rw
        environment:
            - TS_USERSPACE=1
            - TS_STATE_DIR=/var/lib/tailscale
        restart: unless-stopped

    fastenhealth:
        image: ghcr.io/fastenhealth/fasten-onprem:main
        network_mode: service:tailscale
        depends_on:
            - tailscale
        volumes:
            - /volume1/docker/fastenhealth/db:/opt/fasten/db:rw
        restart: unless-stopped

I also get error 500's when doing this with a stack that has a depends on and network mode.  Other stacks work fine.  Stopping, removing images, starting seems to work fine, and it's likely that recreating twice would work as it does download the new images.

There is another even bigger issues with occurring as well. The old container is being deleted after failing to create the new one. This leaves no means of recovery.

Having the same issue since update to 2.19.4
Happening to all my containers regardless of network config.
And also happening regardless of how the container was created.
Getting a 500 error on recreate and repull, 2nd attempt works but wipes env

Having the same issue since update to 2.19.4 BE Happening to all my containers regardless of network config. And also happening regardless of how the container was created. Getting a 500 error on recreate and repull, 2nd attempt works but wipes env

Same issue here with Portainer BE

Same here. Please fix this :(

Since my last post back in 09/2023.. (we are now 1.5 years since my first post 02/2023. that was on version 2.16)
Not sure when the issue went back to "across the board" from "only two remaining containers".  I've updated versions multiple times and the issue remains. My current situation....
ALL containers (local & via agent) whether the image is already downloaded (doesn't matter if the image is the same or newer) require updating from "stacks editor" as opposed to "containers recreate".
The "two remaining containers" from my last post (calibre & home assistant) require that I first manually download the images otherwise no matter how I attempt (via stacks editor or container recreate) the update fails.

the exacty issue is alive on my sys aswell as of today

Same issue:

what should i do guys?

Same here, running appreciate 40 containers.  A lot containers can't even ping or connect to  the docker host using omda stuff here

I gave up on this and used https://github.com/mag37/dockcheck it was more reliable.


PSUseProcessBlockForPipelineCommand : The rule is triggered once for each set name parameter present

The rule is triggered once for each set name parameter present.
Steps to reproduce
Function TestParameterSet{
  [CmdletBinding(DefaultParameterSetName = "Functionality3")]
  Param (
      [Parameter(ValueFromPipeline = $true,ParameterSetName="Functionality1")]
    [String] $Avariable,

      [Parameter(ParameterSetName="Functionality2")]
    [Switch] $Bvariable,

      [Parameter(ValueFromPipelineByPropertyName = $true,ParameterSetName="Functionality3")]
    [Switch] $Cvariable,

      [Parameter(ParameterSetName="Functionality1")]
      [Parameter(ValueFromPipelineByPropertyName = $true,ParameterSetName="Functionality2")]
      [Parameter(ParameterSetName="Functionality3")]
    [String] $Dvariable
  )

    Write-Verbose "Traitement..."
}

Expected behavior
RuleName                            Severity     ScriptName Line  Message
--------                            --------     ---------- ----  -------
PSUseProcessBlockForPipelineCommand Warning      MixedVFP   5     Command accepts pipeline input but has not defined a
                                                 One by           process block.
                                                 PSN
                                                 Without pr
                                                 ocessblock
                                                 .ps1

Actual behavior

RuleName                            Severity     ScriptName Line  Message
--------                            --------     ---------- ----  -------
PSUseProcessBlockForPipelineCommand Warning      MixedVFP   5     Command accepts pipeline input but has not defined a
                                                 One by           process block.
                                                 PSN
                                                 Without pr
                                                 ocessblock
                                                 .ps1
PSUseProcessBlockForPipelineCommand Warning      MixedVFP   11    Command accepts pipeline input but has not defined a
                                                 One by           process block.
                                                 PSN
                                                 Without pr
                                                 ocessblock
                                                 .ps1
PSUseProcessBlockForPipelineCommand Warning      MixedVFP   16    Command accepts pipeline input but has not defined a
                                                 One by           process block.
                                                 PSN
                                                 Without pr
                                                 ocessblock
                                                 .ps1

Environment data

$PSVersionTable

Name                           Value
----                           -----
PSVersion                      5.1.18362.752
PSEdition                      Desktop
PSCompatibleVersions           {1.0, 2.0, 3.0, 4.0, 5.0, 5.1.18362.752}
BuildVersion                   10.0.18362.752
CLRVersion                     4.0.30319.42000
WSManStackVersion              3.0
PSRemotingProtocolVersion      2.3
SerializationVersion           <IP_ADDRESS>

(Get-Module -ListAvailable PSScriptAnalyzer).Version | ForEach-Object { $_.ToString() }
1.19.0
1.18.3
1.18.1
1.18.0
1.17.1

If I add a process block there are no more warnings.

thanks for the report. That sounds like something we could try to tweak

@LaurentDardenne If it should only trigger once, then what should the reported Extent be in the violation?. At the moment, it points out which parameters are the one that declare pipeline support.  The Param block or function name (if available)? Highlighting the whole Param block might look odd in VS-Code due to the squigglies.

>> If it should only trigger once, then what should the reported Extent be in the violation?
The first Violation I think.
The Param block can contain one or more parameters using the pipeline (by value or by property name).
The presence of the process block does not trigger this rule and this for all the parameter definitions that could trigger it.
The param block contains many implicit or explicit rules, this is one.
>> At the moment, it points out which parameters are the one that declare pipeline support.
I agree, here the cardinality is 1..n (a process block for one or more parameters using the pipeline).
The question here is not which parameter uses the pipeline, but that a declaration of this type is ineffective if the process block is absent.
And if I am not mistaken the reverse rule is also possible:
https://github.com/LaurentDardenne/ParameterSetRules/blob/master/RuleDocumentation/MissingArgumentToManageIncomingPipelineObject.md
>> The Param block or function name (if available)?
The function name. But here I have not considered scriptblocks.
>> Highlighting the whole Param block might look odd in VS-Code due to the squigglies.
This is another problem I think, I may not be using VS-Code.
What would be strange would be to display 'here there is a problem', to us to know which one ;-)
If I am told 'A parameter using the pipeline requires a process block', I no longer need to search for the treasure.
That said I use VSCode, but I don't focus on problem notifications, since sometimes we have to specify in the code 'this, is not a problem' :-)
So for this rule, personally I want to know what is missing, not what triggers it.


Windows [TP4] Fix push to not kill daemon

Signed-off-by: John Howard<EMAIL_ADDRESS>This fixes push (v2) in the Windows daemon.  (@tonistiigi It can be updated or merged with your PR https://github.com/docker/docker/pull/17945 to use allowBaseParentImage instead of the runtime.GOOS check)
Currently, without this fix the Windows daemon will SIGSEGV and die if it attempts to push to a DTR. So this is certainly a step in the right direction. The fix is to not attempt to push the base layer on Windows.
However, even with cherry-picking your pull PR fix, the overall push/delete/pull workflow does not appear to work correctly as I cannot run anything from the pulled image.
I have narrowed at least one problem down to the layer IDs being pushed to the repository. Removing a pulled image and re-pulling it will always get the same IDs for the layers. But they are different layer IDs to that in the image originally being pushed.
So that suggests that something in the pull v2 code on Windows is altering the layer IDs as they are being pushed to the repository. My best guess (I really don't have enough knowledge of this code unfortunately and am still trying to find where) is that it is something to do with the v1 compatibility that is changing the IDs in the manifest.
Here's an example of a clean-down, build an image and push:

Note that the image ID is 958eed.... and has another layer f94ce18, both of which are pushed to the DTR.
Now another clean-down and pull (after cherry-picking your commit obviously):

Notice how on both pull attempts, the layer IDs this time are fd2d54 and 3dcc15, and do NOT match what appeared to have been pushed.
@swernli @powersplay @aaronlehmann @tonistiigi

Thanks for getting this to move forward.
Dan
On Nov 14, 2015 5:45 PM, "John Howard (Microsoft)"<EMAIL_ADDRESS>wrote:

Signed-off-by: John Howard<EMAIL_ADDRESS>This fixes push (v2) in the Windows daemon. (@tonistiigi
https://github.com/tonistiigi It can be updated or merged with your PR
#17945 https://github.com/docker/docker/pull/17945 to use
allowBaseParentImage instead of the runtime.GOOS check)
Currently, without this fix the Windows daemon will SIGSEGV and die if it
attempts to push to a DTR. So this is certainly a step in the right
direction. The fix is to not attempt to push the base layer on Windows.
However, even with cherry-picking your pull PR fix, the overall
push/delete/pull workflow does not appear to work correctly as I cannot run
anything from the pulled image.
I have narrowed at least one problem down to the layer IDs being pushed to
the repository. Removing a pulled image and re-pulling it will always get
the same IDs for the layers. But they are different layer IDs to that in
the image originally being pushed.
So that suggests that something in the pull v2 code on Windows is altering
the layer IDs as they are being pushed to the repository. My best guess (I
really don't have enough knowledge of this code unfortunately and am still
trying to find where) is that it is something to do with the v1
compatibility that is changing the IDs in the manifest.
Here's an example of a clean-down, build an image and push:
[image: push]
https://cloud.githubusercontent.com/assets/10522484/11166704/5ad6ef30-8af6-11e5-85b5-5048304c46ef.JPG
Note that the image ID is 958eed.... and has another layer f94ce18, both
of which are pushed to the DTR.
Now another clean-down and pull (after cherry-picking your commit
obviously):
[image: pull]
https://cloud.githubusercontent.com/assets/10522484/11166723/131257f6-8af7-11e5-83fb-086632c168de.JPG
Notice how on both pull attempts, the layer IDs this time are fd2d54 and
3dcc15, and do NOT match what appeared to have been pushed.
@swernli https://github.com/swernli @powersplay
https://github.com/powersplay @aaronlehmann
https://github.com/aaronlehmann @tonistiigi
https://github.com/tonistiigi
You can view, comment on, or merge this pull request online at:
https://github.com/docker/docker/pull/17988
Commit Summary

Windows [TP4] Fix push to not kill daemon

File Changes

M graph/push_v2.go
https://github.com/docker/docker/pull/17988/files#diff-0 (6)

Patch Links:

https://github.com/docker/docker/pull/17988.patch
https://github.com/docker/docker/pull/17988.diff

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Reply to this email directly or view it on GitHub
https://github.com/docker/docker/pull/17988.

@tonistiigi Rebased to use allowBaseParentImage following the merge of #17945.
@Other Reviewers - ignore the overall workflow problem described above. That is still be investigated :confused:. After speaking to Tonis on IRC yesterday evening, this fix is the right thing for push in terms of what layers get pushed. Certainly we shouldn't have the daemon die if a push is attempted :innocent:
@thaJeztah Could you tag TP4 please :heart:

@tonistiigi Well I'm not quite sure what was causing the failure not being able to run the pulled image yesterday, but after rebooting the container host, I can run the pulled image. Will try some more repros just to be sure. So now, I think it's just a question of the different IDs :smile:

@n054 - Not sure what you mean?

@jhowardmsft so what's the status of this? Does it need more changes?
ping @tonistiigi @aaronlehmann

LGTM

This fix is good. But yes, there will be another fix still needed.

LGTM

LGTM


Support personal access tokens

See also https://github.com/seamapi/nextlove/pull/124 and https://github.com/seamapi/fake-seam-connect/issues/124

@razor-x we have withAccessToken middleware. The fake also supports pat_with_workspace and pat_without_workspace [source].
What else this issue requires to be implemented?

@andrii-balitskyi Yea, the auth methods were added but were not working. Getting these tests to pass is the first step in verifying those auth methods work https://github.com/seamapi/javascript-http/pull/150/files#diff-8f55516b1f0506eb134563710a3c6be8690e5f149de0810491a634f536fbcd4c


[App]: Separating config and metrics

Current Behavior
In the Run Comparer, I would like it to only show the config of the models (e.g. hyperparameters) so that I can compare differences between runs. The Run comparer seems to show every single logged metric, which is counterintuitive since config and metrics are different types of things.
More to the point, this seems to occur consistently in other places which might classify as a bug. In particular, in the run Overview page, the left side shows the config and the right side shows the metrics as appropriate (screenshot)

However, when I tried to download the config as raw dictionary data (pressing the "View Raw Data" button on the left), it exports not only the config but all the metrics again. I think this is a bug, unless it was an intentional design choice for some reason? This makes it very hard to do side-by-side comparisons of run hyperparameters which is a common use case
Expected Behavior
Better separation of config and metrics where appropriate

In the "View Raw Data" exports, the config export should only give the config and the metrics export should only give the metrics
[feature request] in the Run Comparer, add a flag to only show config or metrics if desired

Steps To Reproduce
No response
Screenshots
No response
Environment
OS: macOS 13.3
Browsers: Chrome
Version:
Additional Context
No response

Hi @albertfgu, I can make the feature request and also report the bug to our engineering team. I'm not sure if they showing both metrics and config when you click Raw Data is by design but I agree that it would make sense to break these out and separate them.
I can follow up once the engineering team has had a chance to look into these.
Thank you,
Nate

Thanks!

Hi @albertfgu, I wanted to follow up on this. I'm not seeing the same behavior when it comes to downloading the raw config file. I see the config that is passed to wandb.init along with the additional metadata we collect but I don't see any metric values here. Could you possibly share a link to a run where you are seeing this?
Thank you,
Nate

Hi @albertfgu, just wanted to follow up on this and see if you had a run where you were seeing the config and summary combined?

Hi Nate, sorry for getting back late - I don't have much time to look into it for a few weeks. I think this happens in all my wandb runs, here's an old random run I pulled out: https://wandb.ai/hazy-research/hippo/runs/d66uw9ly/overview?workspace=
Now that I look at it more carefully, though, all the metrics are under a _wandb key. Now I'm wondering if this is something automatically added to the config by Lightning's wandblogger which I'm using, although I can't imagine why/how they're getting logged to the config.

Hi @albertfgu, Sorry for the delay on this but I've made a feature request to remove these from the config when using PTL's WandbLogger class. I can follow up once the engineering team has a chance to look into this.


[ENH] Conditional_join on an equi-join with numba

PR Description
Please describe the changes proposed in the pull request:

numba support for equi-join
limited to single equi-join and either a less than join or a greater than join, or a range join.
Not equal (!=) join is not supported
limited to numeric and datetime dtypes.
performance is significant for many to many joins with wide ranges

This PR improves conditional_join.
Example:
Data adapted from here and based on this paper
url = "https://raw.githubusercontent.com/samukweku/data-wrangling-blog/master/notebooks/Data_files/flights.csv"
flights = pd.read_csv(url, sep = '\t', names=['orig','dest','orig_time', 'dest_time'], parse_dates  = ['orig_time', 'dest_time'])
flights = flights.factorize_columns(['orig','dest']).iloc[:, 2:]
flights.columns = [ent.split("_")[0] if ent.endswith('enc') else ent for ent in flights]
flights.columns = ['takeoff','landing','orig','dest']
flights = flights.assign(start=flights.landing+pd.Timedelta(minutes=45), end=flights.landing+pd.Timedelta(hours=3))
flights.head()

                takeoff	                 landing	orig	dest	start	                  end
0	2021-11-27 07:15:00	2021-11-27 08:55:00	0	0	2021-11-27 09:40:00	2021-11-27 11:55:00
1	2021-11-27 20:05:00	2021-11-28 00:50:00	1	1	2021-11-28 01:35:00	2021-11-28 03:50:00
2	2021-11-27 21:00:00	2021-11-27 21:35:00	2	2	2021-11-27 22:20:00	2021-11-28 00:35:00
3	2021-11-27 21:15:00	2021-11-27 22:25:00	0	2	2021-11-27 23:10:00	2021-11-28 01:25:00
4	2021-11-26 11:40:00	2021-11-26 14:45:00	3	3	2021-11-26 15:30:00	2021-11-26 17:45:00

# classic Pandas merge and filter
%%timeit
outt = (flights
        .merge(flights, left_on='dest', right_on='orig')
        .loc[lambda f: f.takeoff_y.between(f.start_x, f.end_x) & (f.orig_x != f.orig_y),
             ['start_x', 'takeoff_y', 'start_y', 'dest_x', 'orig_y']
             ]
        )
8.93 s ± 74.3 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

# dev, with use_numba=False
%%timeit
outer = (flights
 .conditional_join(
     flights,
     ('end', 'takeoff' ,'>='),
     ('start', 'takeoff', '<='),
     ('orig','orig','!='),
    ('dest', 'orig', '=='),
    df_columns = ['start', 'end', 'dest'],
     right_columns = ['takeoff', 'orig'],
     use_numba=False)
)
904 ms ± 10.6 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

# this PR, with use_numba=True
%%timeit
out = (flights
 .conditional_join(
     flights,
     ('end', 'takeoff' ,'>='),
    ('start', 'takeoff', '<='),
     ('orig','orig','!='),
     ('dest', 'orig', '=='),
     df_columns = ['start', 'end', 'dest'],
     right_columns = ['takeoff', 'orig'],
     use_numba=True)
)
66.2 ms ± 2.14 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

# compare outputs
(out
 .sort_values(out.columns.tolist(), ignore_index=True)
 .equals(outer.sort_values(outer.columns.tolist(), ignore_index=True))
)
True

PR Checklist

Please ensure that you have done the following:

[x] PR in from a fork off your branch. Do not PR from <your_username>:dev, but rather from <your_username>:<feature-branch_name>.

[x] If you're not on the contributors list, add yourself to AUTHORS.md.

[x] Add a line to CHANGELOG.md under the latest version header (i.e. the one that is "on deck") describing the contribution.

Do use some discretion here; if there are multiple PRs that are related, keep them in a single line.

Automatic checks
There will be automatic checks run on the PR. These include:

Building a preview of the docs on Netlify
Automatically linting the code
Making sure the code is documented
Making sure that all tests are passed
Making sure that code coverage doesn't go down.

Relevant Reviewers

Please tag maintainers to review.

@ericmjl

🚀 Deployed on https://deploy-preview-1267--pyjanitor.netlify.app

@samukweku I'm not quite sure how to handle this conflict here. Would you be kind enough to help please?

LGTM!

With things passing, I merged, @samukweku!


Better forked module support

Rationale, workflow jobs generate a lot of unnecessary action noise on forking a repo.
Gate what make sense, and open others up.
Adds inputs to acceptance workflow so modules (like mysql and firewall) can take advantage of these templates.

changing the branch


Acrylic plate is scaled too large

The acrylic plate DXF files seem to be scaled way too large, measuring over 3000mm length for the plates.

Okay so I found a way to get around it, convert ai files to svg instead and then convert that to a dxf and the dimensions are fine


add cargo clean to doc script

encountered an issue that an outdated reference caused cargo doc to fail. cargo clean fixed it, and it should probably be included in the doc ci script

added to ps1, missing sh


educate people on how to add custom exceptions

So, borrowed from somewhere on the Internet, we were doing custom exceptions that looked something like this:
var ValueError;

ValueError = (function() {
  function ValueError() {}
  ValueError.prototype = Object.create(Error.prototype);
  return ValueError;
})();

module.exports = ValueError;

Unfortunately if you call sentry.client.captureError(new ValueError("foobar")), Sentry doesn't have the stack trace.

Was thinking raven could take the lead here and actually document the right way to create/subclass exceptions so this kind of data doesn't get lost / your Sentry data is more useful.

The best way I've seen is the way I do it inside raven.js: https://github.com/getsentry/raven-js/blob/master/src/raven.js#L381-L386
Not sure the pros/cons though. :)

fwiw, I think doing this.stack = new Error(this.message).stack is not the best. You're also not carrying over the name. Also, the stack attribute is typically lazily evaluated. So by initializing it here, you're forcing it to be evaluated. And lastly, this will add an extra frame to your stack trace.

Useful. +1

There's a great post on how to achieve it: https://coderwall.com/p/m3-cqw/subclassing-error-in-javascript-is-harder-than-it-seems
I don't think we will add this to our docs anytime soon, so closing it for now.


Unable to resolve dependency for ':@debug/compileClasspath': Could not resolve org.apache.commons:commons-math3:3.6.1.

Getting the dependency error in YoloClassifier.java  Unable to resolve dependency for ':@debug/compileClasspath': Could not resolve org.apache.commons:commons-math3:3.6.1. where I have injected the jar file to project and Missing the Sigmoid class.
Could you people assist us while resolving the issue

Hi,
Theoretically, you don't need to add the dependencies manually, it should be done automatically by the Gradle. Could you tell me please more details about how you tried to build the project?
Do you have any kind of proxy settings?
Could you try please to run from the root folder ./gradlew clean install -xtest ?

I had build the gradle by installing required dependencies and i got stucked here..
how to check the proxy setting..

What is the version of your TensorFlow?
Usually, this error appear when you train with a different TF version then your TFLight version.
Could you please check if your TF version which you use for training is the same like the TFLight version which you use on the Android?

this problem was resolved.. but facing the other issues when I changed the trained modelthrowing the Exception..org.tensorflow.TensorFlowException: Op type not registered 'TFLite_Detection_PostProcess' in binary running on localhost. Make sure the Op and Kernel are registered in the binary running in this process.
Sai Kartik Nistala
Research Associate
Phone :<PHONE_NUMBER>
Mobile :<PHONE_NUMBER>
Email<EMAIL_ADDRESS>	Miracle Heights - APAC HQ
Hill No. 1, IT SEZ, Chinna Rushi Konda
Visakhapatnam, AP - 530045, India
www.miraclesoft.com
From: "Zoltán Szabó"<EMAIL_ADDRESS>To: "szaza/android-yolo-v2"<EMAIL_ADDRESS>Cc: "nistala"<EMAIL_ADDRESS>"Author"<EMAIL_ADDRESS>Sent: Monday, August 6, 2018 7:11:58 PM
Subject: Re: [szaza/android-yolo-v2] Unable to resolve dependency for ':@debug/compileClasspath': Could not resolve org.apache.commons:commons-math3:3.6.1. (#8)
What is the version of your TensorFlow?
Usually, this error appear when you train with a different TF version then your TFLight version.
Could you please check if your TF version which you use for training is the same like the TFLight version which you use on the Android?
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EmbedAnything Pinecone Integeration Notebook

EmbedAnything Pinecone Integeration Notebook added in the examples folder

Hi Krishna,
the notebook isn't an integration so it would be misleading, can you just rename it pinecone example. I think then it would be good to go


Pr/48

Hey @Cooky420! I'm closing this PR since something equivalent was already implemented on https://github.com/BuilderIO/gpt-crawler/pull/69 :hugs:


build: minor CMake cleanups

These are minor cleanups that do not affect the behaviour of the script.
In particular, I removed most DESTINATION arguments from install(), since they are automatically deduced based on the type of file to be installed.
In #662 I also added doxygen_add_docs and gtest_discover_tests, but they require CMake version 3.9 and 3.10 respectively, and I think that the advantages they provide are not worth dropping support for older versions

Thanks!