Issues replacing malloc() on Windows

I'm evaluating the possibility to replace malloc() for LLVM.
I hit some problems I'd like to point out here:
The README is wrong:
c:\Users\fluttershy\work\Hoard\src>nmake windows

Microsoft (R) Program Maintenance Utility Version 14.00.23918.0
Copyright (C) Microsoft Corporation.  All rights reserved.

NMAKE : fatal error U1073: don't know how to make 'windows'
Stop.

The correct command seems to be just nmake:
c:\Users\fluttershy\work\Hoard\src>nmake

Microsoft (R) Program Maintenance Utility Version 14.00.23918.0
Copyright (C) Microsoft Corporation.  All rights reserved.

*****
This Makefile is for Windows only. For other systems, use gmake.
*****
        cl /I. /Iinclude /Iinclude/util /Iinclude/hoard /Iinclude/superblocks /I
Heap-Layers /D "NDEBUG" /D "_WINDOWS" /D "_WINDLL" /D "_WINRT_DLL" /D "_UNICODE"
 /D "UNICODE" /Zi /Ox /MD /nologo /W1 /WX- /Ox /Oi /Oy- /Gm- /EHsc /MD /GS /Gy /
Zc:wchar_t /Zc:forScope /Gd /errorReport:queue "source\libhoard.cpp" "Heap-Layer
s\wrappers\winwrapper.cpp" "source\wintls.cpp" /GL /link /DLL /subsystem:console
 /OUT:libhoard.dll
libhoard.cpp
winwrapper.cpp
wintls.cpp
   Creating library libhoard.lib and object libhoard.exp
Generating code
Finished generating code
        cl /I. /Iinclude /Iinclude/util /Iinclude/hoard /Iinclude/superblocks /I
Heap-Layers /D "NDEBUG" /D "_WINDOWS" /D "_WINDLL" /D "_WINRT_DLL" /D "_UNICODE"
 /D "UNICODE" /Zi /Ox /MD /nologo /W1 /WX- /Ox /Oi /Oy- /Gm- /EHsc /MD /GS /Gy /
Zc:wchar_t /Zc:forScope /Gd /errorReport:queue /c "source\uselibhoard.cpp"
uselibhoard.cpp

The malloc() replacement example doesn't quite work, in basic cases:
$ cat patatino.cpp
#include <stdlib.h>

int main (void) {
        malloc(16);
        return (0);
}

If I try to run the way it's described on the website:
c:\Users\fluttershy\work\Hoard\src>cl /Ox /MD patatino.cpp source\libhoard.cpp libhoard.lib
Microsoft (R) C/C++ Optimizing Compiler Version 19.00.23918 for x64
Copyright (C) Microsoft Corporation.  All rights reserved.

patatino.cpp
libhoard.cpp
source\libhoard.cpp(33): fatal error C1083: Cannot open include file: 'heaplayer
s.h': No such file or directory
Generating Code...

It seems the issue is that it's not able to locate the headers, something like this might fix:
diff --git a/src/source/libhoard.cpp b/src/source/libhoard.cpp
index 54d3713..cb39efc 100644
--- a/src/source/libhoard.cpp
+++ b/src/source/libhoard.cpp
@@ -30,7 +30,7 @@
  * @author Emery Berger <http://www.cs.umass.edu/~emery>
  */

-#include "heaplayers.h"
+#include "../Heap-Layers/heaplayers.h"
 using namespace HL;

 #include <new>

But immediately after I hit another problem:
c:\users\fluttershy\work\hoard\src\heap-layers\heaps\combining\hybridheap.h(32):
 fatal error C1083: Cannot open include file: 'heaplayers.h': No such file or di
rectory

Any ideas on how to fix? I think the instructions on the website need some love.

Actually specifying a bunch of include paths, via \I, I'm able to get to link time, but that fails with two undefined references:
c:\Users\fluttershy\work\Hoard\src>cl /Ox /MD patatino.cpp source\libhoard.cpp l
ibhoard.lib /IHeap-Layers\ /Iinclude /Iinclude/hoard /Iinclude/util /Iinclude/su
perblocks
Microsoft (R) C/C++ Optimizing Compiler Version 19.00.23918 for x64
Copyright (C) Microsoft Corporation.  All rights reserved.

patatino.cpp
libhoard.cpp
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\exception(359): w
arning C4577: 'noexcept' used with no exception handling mode specified; termina
tion on exception is not guaranteed. Specify /EHsc
Generating Code...
Microsoft (R) Incremental Linker Version 14.00.23918.0
Copyright (C) Microsoft Corporation.  All rights reserved.

/out:patatino.exe
patatino.obj
libhoard.obj
libhoard.lib
libhoard.obj : error LNK2019: unresolved external symbol "class Hoard::ThreadLoc
alAllocationBuffer<11,&public: static int __cdecl HL::bins<class Hoard::HoardSup
erblockHeader<class HL::WinLockType,65536,class Hoard::SmallHeap>,65536>::getSiz
eClass(unsigned __int64),&public: static unsigned __int64 __cdecl HL::bins<class
 Hoard::HoardSuperblockHeader<class HL::WinLockType,65536,class Hoard::SmallHeap
>,65536>::getClassSize(int),256,2097152,class Hoard::HoardSuperblock<class HL::W
inLockType,65536,class Hoard::SmallHeap>,65536,class Hoard::HoardHeapType> * __c
decl getCustomHeap(void)" (?getCustomHeap@@YAPEAV?$ThreadLocalAllocationBuffer@$
0L@$1?getSizeClass@?$bins@V?$HoardSuperblockHeader@VWinLockType@HL@@$0BAAAA@VSma
llHeap@Hoard@@@Hoard@@$0BAAAA@@HL@@SAH_K@Z$1?getClassSize@23@SA_KH@Z$0BAA@$0CAAA
AA@V?$HoardSuperblock@VWinLockType@HL@@$0BAAAA@VSmallHeap@Hoard@@@Hoard@@$0BAAAA
@VHoardHeapType@6@@Hoard@@XZ) referenced in function xxmalloc
libhoard.obj : error LNK2019: unresolved external symbol "bool __cdecl isCustomH
eapInitialized(void)" (?isCustomHeapInitialized@@YA_NXZ) referenced in function
xxmalloc
patatino.exe : fatal error LNK1120: 2 unresolved externals

Can't quite understand from which library these symbols are coming from. The only file in which they appear is libhoard.obj and they're undefined, e.g.
$ ~/Downloads/llvm-nm.exe libhoard.obj | grep isCustom
         U ?isCustomHeapInitialized@@YA_NXZ

@emeryberger ^

Thanks for the ping. Will look into this soon (traveling today & tomorrow).

@emeryberger: did you get a chance to take a look at this?

Belatedly coming back to this, sorry. It builds fine for me on Windows 10, but now doesn't work properly. Looking into it.

Working now with latest commits.


cargo-watch: init at 7.2.1

Motivation for this change
A Cargo subcommand for watching over Cargo project's source

https://github.com/passcod/cargo-watch

Things done

[x] Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nix-review --run "nix-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[ ] Ensured that relevant documentation is up to date
[x] Fits CONTRIBUTING.md.

Notify maintainers
cc @

@GrahamcOfBorg build cargo-watch

@mmahut @ivan Thank you!


Restore the PCM and PWM clock original states after using waves

Currently it appears that PCM and PWM clocks are taken over and not restored when using waves. Ideally, gpioTerminate should restore these clocks. My understanding is that this could be done by saving clkReg[clkDiv] before the call to initClock(0) and restoring it through calls to initHWClk.

I'm working on a pull request to address this. @joan2937 can you please have a quick look at https://github.com/dspinellis/pigpio/commit/93f127f53d1ab37dfba7842f932c76ee6ca91cb0 to check if it's in the right direction?  This is still work in progress.
Currently the code is structured to save the hardware state of the five clocks, PWM, and PCM before modifying it, and to restore the saved state when gpioNotifyClose() gets called, which is also called from the Python stop() method.

Most recent work is at https://github.com/dspinellis/pigpio/tree/fix-567-pm-state. Saving and restoring seems to work, and all original tests pass. I am currently looking at ways to add unit tests.

The issue is now correctly linked in the initial description and reproduced below.
The following example program sends a short pulse on GPIO 14 using pigpio.
import pigpio

pi = pigpio.pi() # connect to Pi

pi.wave_add_new()
pi.set_mode(14, pigpio.OUTPUT)

wf=[]
wf.append(pigpio.pulse(1 << 14, 0, 500))
wf.append(pigpio.pulse(0, 1 << 14, 800))

pi.wave_clear()
pi.wave_add_generic(wf)
wid = pi.wave_create()
pi.wave_send_once(wid)

while pi.wave_tx_busy():
  pass

pi.wave_clear()
pi.stop()

Even after terminating pigpiod, the sound from IQaudio sounds garbled: played intermittently at a high speed with vlc or sounding like white noise with speaker_test. Killing and rerunning pigpiod doesn't help. Only a reboot fixes the problem. Running pigpiod without running the program, or configuring pigpio without using its wave functionality doesn't create a problem.
As explained in the answer to the corresponding Raspberry Pi StackExchange question, "pigpio takes over the PWM and PCM clocks when you use waves, and there is no provision made by pigpio to restore the clocks to the previous state."


"Primary Organization" scope for login

Is your feature request related to a problem? Please describe.
When using Zitadel with a primary domain scope, it would be nice to use the org ID as specifier. So as an additional method, a scope that uses the org id to define the "primary organization" would be nice to identify the primary login domain.
This would be useful to limit the users to a specific org (like now) but NOT via domain since they may change over time.
Describe the solution you'd like
A new https://docs.zitadel.ch/docs/apis/openidoauth/scopes#reserved-scopes
urn:zitadel:iam:org:primary:ORG-ID that allows the limitation of login to a specific organization like urn:zitadel:iam:org:domain:primary:acme.ch.

hi @buehler
Thanks for this enhancement. We will schedule it on Wednesday and update the issue.

Would still be nice though...

fixed by #4245


Self Serve Google Fonts

Issue
Right now, Google Fonts require to be fetched specifically over a URL (picked from google's css)
Solution
Use next/font like emitFile to emit fonts with the build.

Fixed with https://github.com/rishi-raj-jain/astro-font/commit/8d7790cfa8843ed103b0d2c59ae81a4ac76c45f3


Submit NetPyNE <IP_ADDRESS>

id: netpyne
version: <IP_ADDRESS>
specificationsUrl: https://raw.githubusercontent.com/biosimulators/Biosimulators_pyNeuroML/f5ea344d28c171a1a00918cac841a995e3fc5f68/biosimulators-netpyne.json
specificationsPatch:
version: <IP_ADDRESS>
image:
url: ghcr.io/biosimulators/biosimulators_pyneuroml/netpyne:<IP_ADDRESS>
validateImage: true
commitSimulator: true

Thank you @biosimulators-daemon for your submission to the BioSimulators simulator validation/submission system!
The BioSimulators validator bot is validating the specifications of your simulator, validating your Docker image, and committing your simulator to the BioSimulators registry.
We will discuss any concerns with your submission in this issue.
A complete log of your simulator submission job will be available for 90 days here. The results of the validation of your tool will also be saved as a JSON file. A link to this file will be available for 90 days from the "Artifacts" section at the bottom of this page.

The specifications of your simulator is valid!

Summary of tests

Executed 72 test cases

Passed 30 test cases:

cli.CliDescribesSupportedEnvironmentVariablesInline
cli.CliDisplaysHelpInline
cli.CliDisplaysVersionInformationInline
combine_archive.CombineArchiveHasSedDocumentsInNestedDirectories
combine_archive.CombineArchiveHasSedDocumentsWithSameNamesInDifferentInNestedDirectories
combine_archive.WhenACombineArchiveHasAMasterFileSimulatorOnlyExecutesThisFile
combine_archive.WhenACombineArchiveHasNoMasterFileSimulatorExecutesAllSedDocuments
docker_image.DeclaresSupportedEnvironmentVariables
docker_image.DefaultUserIsRoot
docker_image.HasBioContainersLabels
docker_image.HasOciLabels
docker_image.SingularityImageExecutesSimulationsSuccessfully
log.SimulatorReportsTheStatusOfTheExecutionOfCombineArchives
log.SimulatorReportsTheStatusOfTheExecutionOfSedDocuments
log.SimulatorReportsTheStatusOfTheExecutionOfSedOutputs
log.SimulatorReportsTheStatusOfTheExecutionOfSedTasks
published_project.SimulatorCanExecutePublishedProject:neuroml-lems/Hodgkin-Huxley-cell-CVODE
results_report.SimulatorGeneratesReportsOfSimulationResults
sedml.SimulatorCanResolveModelSourcesDefinedByUriFragments
sedml.SimulatorCanResolveModelSourcesDefinedByUriFragmentsAndInheritChanges
sedml.SimulatorProducesLinear2DPlots
sedml.SimulatorProducesLogarithmic2DPlots
sedml.SimulatorProducesMultiplePlots
sedml.SimulatorProducesReportsWithCuratedNumberOfDimensions
sedml.SimulatorSupportsDataGeneratorsWithDifferentShapes
sedml.SimulatorSupportsDataSetsWithDifferentShapes
sedml.SimulatorSupportsModelsSimulationsTasksDataGeneratorsAndReports
sedml.SimulatorSupportsMultipleReportsPerSedDocument
sedml.SimulatorSupportsMultipleTasksPerSedDocument
sedml.SimulatorSupportsUniformTimeCoursesWithNonZeroOutputStartTimes

Failed 0 test cases

Skipped 42 test cases:

published_project.SimulatorCanExecutePublishedProject:bngl/Dolan-PLoS-Comput-Biol-2015-NHEJ
published_project.SimulatorCanExecutePublishedProject:bngl/test-bngl
published_project.SimulatorCanExecutePublishedProject:cellml/Elowitz-Nature-2000-Repressilator
published_project.SimulatorCanExecutePublishedProject:cellml/Lorenz-system
published_project.SimulatorCanExecutePublishedProject:mass/Bordbar-Cell-Syst-2015-RBC-metabolism
published_project.SimulatorCanExecutePublishedProject:neuroml-lems/Hodgkin-Huxley-cell-Euler
published_project.SimulatorCanExecutePublishedProject:sbml-core/Caravagna-J-Theor-Biol-2010-tumor-suppressive-oscillations
published_project.SimulatorCanExecutePublishedProject:sbml-core/Ciliberto-J-Cell-Biol-2003-morphogenesis-checkpoint-Fehlberg
published_project.SimulatorCanExecutePublishedProject:sbml-core/Ciliberto-J-Cell-Biol-2003-morphogenesis-checkpoint-continuous
published_project.SimulatorCanExecutePublishedProject:sbml-core/Edelstein-Biol-Cybern-1996-Nicotinic-excitation
published_project.SimulatorCanExecutePublishedProject:sbml-core/Elowitz-Nature-2000-Repressilator
published_project.SimulatorCanExecutePublishedProject:sbml-core/Parmar-BMC-Syst-Biol-2017-iron-distribution
published_project.SimulatorCanExecutePublishedProject:sbml-core/Szymanska-J-Theor-Biol-2009-HSP-synthesis
published_project.SimulatorCanExecutePublishedProject:sbml-core/Tomida-EMBO-J-2003-NFAT-translocation
published_project.SimulatorCanExecutePublishedProject:sbml-core/Varusai-Sci-Rep-2018-mTOR-signaling-LSODA-LSODAR-SBML
published_project.SimulatorCanExecutePublishedProject:sbml-core/Vilar-PNAS-2002-minimal-circardian-clock
published_project.SimulatorCanExecutePublishedProject:sbml-core/Vilar-PNAS-2002-minimal-circardian-clock-continuous
published_project.SimulatorCanExecutePublishedProject:sbml-core/Vilar-PNAS-2002-minimal-circardian-clock-discrete-NRM
published_project.SimulatorCanExecutePublishedProject:sbml-core/Vilar-PNAS-2002-minimal-circardian-clock-discrete-SSA
published_project.SimulatorCanExecutePublishedProject:sbml-fbc/Escherichia-coli-core-metabolism
published_project.SimulatorCanExecutePublishedProject:sbml-qual/Chaouiya-BMC-Syst-Biol-2013-EGF-TNFa-signaling
published_project.SimulatorCanExecutePublishedProject:sbml-qual/Irons-J-Theor-Biol-2009-yeast-cell-cycle
published_project.SimulatorCanExecutePublishedProject:smoldyn/Lotka-Volterra
published_project.SimulatorCanExecutePublishedProject:xpp/Wu-Biochem-Pharmacol-2006-pituitary-GH3-cells
sedml.SimulatorProducesLinear3DPlots
sedml.SimulatorProducesLogarithmic3DPlots
sedml.SimulatorSupportsAddReplaceRemoveModelElementChanges
sedml.SimulatorSupportsAlgorithmParameters
sedml.SimulatorSupportsComputeModelChanges
sedml.SimulatorSupportsModelAttributeChanges
sedml.SimulatorSupportsRepeatedTasksWithChanges
sedml.SimulatorSupportsRepeatedTasksWithFunctionalRangeVariables
sedml.SimulatorSupportsRepeatedTasksWithFunctionalRanges
sedml.SimulatorSupportsRepeatedTasksWithLinearUniformRanges
sedml.SimulatorSupportsRepeatedTasksWithLogarithmicUniformRanges
sedml.SimulatorSupportsRepeatedTasksWithMultipleSubTasks
sedml.SimulatorSupportsRepeatedTasksWithNestedFunctionalRanges
sedml.SimulatorSupportsRepeatedTasksWithNestedRepeatedTasks
sedml.SimulatorSupportsRepeatedTasksWithSubTasksOfMixedTypes
sedml.SimulatorSupportsRepeatedTasksWithVectorRanges
sedml.SimulatorSupportsSubstitutingAlgorithms
sedml.SimulatorSupportsUniformTimeCoursesWithNonZeroInitialTimes

Skips
published_project.SimulatorCanExecutePublishedProject:bngl/Dolan-PLoS-Comput-Biol-2015-NHEJ (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_3972
Algorithm: KISAO_0000263

Reason for skip:
Case requires model formats format_3972 and simulation algorithms KISAO_0000263

Log:

published_project.SimulatorCanExecutePublishedProject:bngl/test-bngl (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_3972
Algorithm: KISAO_0000019

Reason for skip:
Case requires model formats format_3972 and simulation algorithms KISAO_0000019

Log:

published_project.SimulatorCanExecutePublishedProject:cellml/Elowitz-Nature-2000-Repressilator (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_3240
Algorithm: KISAO_0000019

Reason for skip:
Case requires model formats format_3240 and simulation algorithms KISAO_0000019

Log:

published_project.SimulatorCanExecutePublishedProject:cellml/Lorenz-system (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_3240
Algorithm: KISAO_0000019

Reason for skip:
Case requires model formats format_3240 and simulation algorithms KISAO_0000019

Log:

published_project.SimulatorCanExecutePublishedProject:mass/Bordbar-Cell-Syst-2015-RBC-metabolism (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000019

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000019

Log:

published_project.SimulatorCanExecutePublishedProject:neuroml-lems/Hodgkin-Huxley-cell-Euler (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_9004
Algorithm: KISAO_0000030

Reason for skip:
Case requires model formats format_9004 and simulation algorithms KISAO_0000030

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-core/Caravagna-J-Theor-Biol-2010-tumor-suppressive-oscillations (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000019

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000019

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-core/Ciliberto-J-Cell-Biol-2003-morphogenesis-checkpoint-Fehlberg (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000086

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000086

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-core/Ciliberto-J-Cell-Biol-2003-morphogenesis-checkpoint-continuous (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000019

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000019

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-core/Edelstein-Biol-Cybern-1996-Nicotinic-excitation (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000088

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000088

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-core/Elowitz-Nature-2000-Repressilator (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000019

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000019

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-core/Parmar-BMC-Syst-Biol-2017-iron-distribution (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_000019

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_000019

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-core/Szymanska-J-Theor-Biol-2009-HSP-synthesis (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000496

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000496

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-core/Tomida-EMBO-J-2003-NFAT-translocation (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000560

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000560

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-core/Varusai-Sci-Rep-2018-mTOR-signaling-LSODA-LSODAR-SBML (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000560

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000560

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-core/Vilar-PNAS-2002-minimal-circardian-clock (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000019
Format: format_2585
Algorithm: KISAO_0000027
Format: format_2585
Algorithm: KISAO_0000030

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000019, KISAO_0000027, KISAO_0000030

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-core/Vilar-PNAS-2002-minimal-circardian-clock-continuous (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000019
Format: format_2585
Algorithm: KISAO_0000030

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000019, KISAO_0000030

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-core/Vilar-PNAS-2002-minimal-circardian-clock-discrete-NRM (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000027

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000027

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-core/Vilar-PNAS-2002-minimal-circardian-clock-discrete-SSA (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000029

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000029

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-fbc/Escherichia-coli-core-metabolism (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000437

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000437

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-qual/Chaouiya-BMC-Syst-Biol-2013-EGF-TNFa-signaling (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000449

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000449

Log:

published_project.SimulatorCanExecutePublishedProject:sbml-qual/Irons-J-Theor-Biol-2009-yeast-cell-cycle (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_2585
Algorithm: KISAO_0000449

Reason for skip:
Case requires model formats format_2585 and simulation algorithms KISAO_0000449

Log:

published_project.SimulatorCanExecutePublishedProject:smoldyn/Lotka-Volterra (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_9001
Algorithm: KISAO_0000057

Reason for skip:
Case requires model formats format_9001 and simulation algorithms KISAO_0000057

Log:

published_project.SimulatorCanExecutePublishedProject:xpp/Wu-Biochem-Pharmacol-2006-pituitary-GH3-cells (0.0 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_9010
Algorithm: KISAO_0000019

Reason for skip:
Case requires model formats format_9010 and simulation algorithms KISAO_0000019

Log:

sedml.SimulatorProducesLinear3DPlots (0.8 s)
Test that a simulator produces linear 3D plots
Reason for skip:
No curated COMBINE/OMEX archives are available to generate archives for testing

Log:

sedml.SimulatorProducesLogarithmic3DPlots (1.0 s)
Test that a simulator produces logarithmic 3D plots
Reason for skip:
No curated COMBINE/OMEX archives are available to generate archives for testing

Log:

sedml.SimulatorSupportsAddReplaceRemoveModelElementChanges (1.0 s)
Test that a simulator supports model changes that involve adding, replacing, and removing model elements.
Reason for skip:
'cython_function_or_method' object has no attribute 'rpartition'

Log:

sedml.SimulatorSupportsAlgorithmParameters (0.9 s)
Test that a simulator supports setting the values of parameters of algorithms
Reason for skip:
No curated COMBINE/OMEX archives are available to generate archives for testing

Log:

sedml.SimulatorSupportsComputeModelChanges (1.0 s)
Test that a simulator supports compute model changes
Reason for skip:
'cython_function_or_method' object has no attribute 'rpartition'

Log:

sedml.SimulatorSupportsModelAttributeChanges (1.0 s)
Test that a simulator supports changes to the attributes of model elements
Reason for skip:
'cython_function_or_method' object has no attribute 'rpartition'

Log:

sedml.SimulatorSupportsRepeatedTasksWithChanges (1.0 s)
Test that a simulator supports repeated tasks with multiple subtasks
Reason for skip:
'cython_function_or_method' object has no attribute 'rpartition'

Log:

sedml.SimulatorSupportsRepeatedTasksWithFunctionalRangeVariables (0.8 s)
Test that a simulator supports repeated tasks over nested functional ranges based on model (specification) variables
Reason for skip:
'cython_function_or_method' object has no attribute 'rpartition'

Log:

sedml.SimulatorSupportsRepeatedTasksWithFunctionalRanges (10.5 s)
Test that a simulator supports repeated tasks over functional ranges
Reason for skip:
The image 'ghcr.io/biosimulators/biosimulators_pyneuroml/netpyne:<IP_ADDRESS>' could not execute the archive:

  Unknown error

Log:
/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The SED document is potentially incorrect.

  - Output `__repeated_task_report` may be invalid.

    - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The COMBINE/OMEX archive may be invalid.

  - The SED-ML file at location `simulation.sedml` may be invalid.

    - Output `__repeated_task_report` may be invalid.

      - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

Archive contains 1 SED-ML documents with 1 models, 1 simulations, 2 tasks, 2 reports, and 0 plots:

  simulation.sedml:

    Tasks (2):

      __repeated_task_0

      task

    Reports (2):

      __repeated_task_report: 5 data sets

      task_report: 5 data sets

Executing SED-ML file 0: simulation.sedml ...

Bundling outputs ...

Cleaning up ...

============= SUMMARY =============

Executed 1 SED documents:

  SED documents (1):

    Succeeded: 0

    Skipped: 0

    Failed: 1

  Tasks (2):

    Succeeded: 1

    Skipped: 0

    Failed: 1

  Outputs (2):

    Succeeded: 1

    Skipped: 1

    Failed: 0

The COMBINE/OMEX did not execute successfully:

  The SED document did not execute successfully:

    `pyNeuroML` was not able to execute `/tmp/tmpgwf2zqso.xml`:

      pyNeuroML >>> *** Problem running command:

      pyNeuroML >>>        Command 'java -Xmx5732M  -Djava.awt.headless=true -jar  "/usr/local/lib/python3.9/site-packages/pyneuroml/lib/jNeuroML-0.10.3-jar-with-dependencies.jar"  "/tmp/tmpc4pis_lj.xml"  -nogui -I ''' returned non-zero exit status 1.

      pyNeuroML >>>  jNeuroML >>   jNeuroML v0.10.3

      pyNeuroML >>>  jNeuroML >>  Loading: /tmp/tmpc4pis_lj.xml with jLEMS, NO GUI mode...

      pyNeuroML >>>  jNeuroML >>  org.lemsml.jlems.core.sim.ContentError: Can't find file at path: NaConductance.channel.nml

      pyNeuroML >>>  jNeuroML >>  Search directories are: [/tmp/tmp0z2agkxe, /tmp, /tmp, /tmp/tmp0z2agkxe]

      pyNeuroML >>>  jNeuroML >>  Search paths in jar are: [/NeuroML2CoreTypes]

      pyNeuroML >>>  jNeuroML >>

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.io.reader.JarResourceInclusionReader.getRelativeContent(JarResourceInclusionReader.java:179)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.getRelativeContent(NeuroMLInclusionReader.java:61)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.getIncludeContent(AbstractInclusionReader.java:41)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.insertIncludes(AbstractInclusionReader.java:71)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.insertIncludes(NeuroMLInclusionReader.java:102)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.read(AbstractInclusionReader.java:24)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:259)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:245)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils$1.importFile(Utils.java:505)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.viz.datadisplay.ControlPanel.initialise(ControlPanel.java:134)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.loadLemsFile(Utils.java:516)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.runLemsFile(Utils.java:493)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.JNeuroML.main(JNeuroML.java:595)

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:44  (INFO) Loading LEMS file from: /tmp/tmpc4pis_lj.xml

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:44  (INFO) Reading from: /tmp/tmpc4pis_lj.xml

      pyNeuroML >>>  jNeuroML >>

sedml.SimulatorSupportsRepeatedTasksWithLinearUniformRanges (10.6 s)
Test that a simulator supports repeated tasks over uniform ranges
Reason for skip:
The image 'ghcr.io/biosimulators/biosimulators_pyneuroml/netpyne:<IP_ADDRESS>' could not execute the archive:

  Unknown error

Log:
/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The SED document is potentially incorrect.

  - Output `__repeated_task_report` may be invalid.

    - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The COMBINE/OMEX archive may be invalid.

  - The SED-ML file at location `simulation.sedml` may be invalid.

    - Output `__repeated_task_report` may be invalid.

      - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

Archive contains 1 SED-ML documents with 1 models, 1 simulations, 2 tasks, 2 reports, and 0 plots:

  simulation.sedml:

    Tasks (2):

      __repeated_task_0

      task

    Reports (2):

      __repeated_task_report: 5 data sets

      task_report: 5 data sets

Executing SED-ML file 0: simulation.sedml ...

Bundling outputs ...

Cleaning up ...

============= SUMMARY =============

Executed 1 SED documents:

  SED documents (1):

    Succeeded: 0

    Skipped: 0

    Failed: 1

  Tasks (2):

    Succeeded: 1

    Skipped: 0

    Failed: 1

  Outputs (2):

    Succeeded: 1

    Skipped: 1

    Failed: 0

The COMBINE/OMEX did not execute successfully:

  The SED document did not execute successfully:

    `pyNeuroML` was not able to execute `/tmp/tmpykkj42vc.xml`:

      pyNeuroML >>> *** Problem running command:

      pyNeuroML >>>        Command 'java -Xmx5733M  -Djava.awt.headless=true -jar  "/usr/local/lib/python3.9/site-packages/pyneuroml/lib/jNeuroML-0.10.3-jar-with-dependencies.jar"  "/tmp/tmph5rlawbe.xml"  -nogui -I ''' returned non-zero exit status 1.

      pyNeuroML >>>  jNeuroML >>   jNeuroML v0.10.3

      pyNeuroML >>>  jNeuroML >>  Loading: /tmp/tmph5rlawbe.xml with jLEMS, NO GUI mode...

      pyNeuroML >>>  jNeuroML >>  org.lemsml.jlems.core.sim.ContentError: Can't find file at path: NaConductance.channel.nml

      pyNeuroML >>>  jNeuroML >>  Search directories are: [/tmp/tmpfpzlwega, /tmp, /tmp, /tmp/tmpfpzlwega]

      pyNeuroML >>>  jNeuroML >>  Search paths in jar are: [/NeuroML2CoreTypes]

      pyNeuroML >>>  jNeuroML >>

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.io.reader.JarResourceInclusionReader.getRelativeContent(JarResourceInclusionReader.java:179)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.getRelativeContent(NeuroMLInclusionReader.java:61)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.getIncludeContent(AbstractInclusionReader.java:41)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.insertIncludes(AbstractInclusionReader.java:71)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.insertIncludes(NeuroMLInclusionReader.java:102)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.read(AbstractInclusionReader.java:24)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:259)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:245)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils$1.importFile(Utils.java:505)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.viz.datadisplay.ControlPanel.initialise(ControlPanel.java:134)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.loadLemsFile(Utils.java:516)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.runLemsFile(Utils.java:493)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.JNeuroML.main(JNeuroML.java:595)

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:44  (INFO) Loading LEMS file from: /tmp/tmph5rlawbe.xml

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:44  (INFO) Reading from: /tmp/tmph5rlawbe.xml

      pyNeuroML >>>  jNeuroML >>

sedml.SimulatorSupportsRepeatedTasksWithLogarithmicUniformRanges (10.3 s)
Test that a simulator supports repeated tasks over uniform ranges
Reason for skip:
The image 'ghcr.io/biosimulators/biosimulators_pyneuroml/netpyne:<IP_ADDRESS>' could not execute the archive:

  Unknown error

Log:
/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The SED document is potentially incorrect.

  - Output `__repeated_task_report` may be invalid.

    - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The COMBINE/OMEX archive may be invalid.

  - The SED-ML file at location `simulation.sedml` may be invalid.

    - Output `__repeated_task_report` may be invalid.

      - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

Archive contains 1 SED-ML documents with 1 models, 1 simulations, 2 tasks, 2 reports, and 0 plots:

  simulation.sedml:

    Tasks (2):

      __repeated_task_0

      task

    Reports (2):

      __repeated_task_report: 5 data sets

      task_report: 5 data sets

Executing SED-ML file 0: simulation.sedml ...

Bundling outputs ...

Cleaning up ...

============= SUMMARY =============

Executed 1 SED documents:

  SED documents (1):

    Succeeded: 0

    Skipped: 0

    Failed: 1

  Tasks (2):

    Succeeded: 1

    Skipped: 0

    Failed: 1

  Outputs (2):

    Succeeded: 1

    Skipped: 1

    Failed: 0

The COMBINE/OMEX did not execute successfully:

  The SED document did not execute successfully:

    `pyNeuroML` was not able to execute `/tmp/tmpmz2r1e10.xml`:

      pyNeuroML >>> *** Problem running command:

      pyNeuroML >>>        Command 'java -Xmx5730M  -Djava.awt.headless=true -jar  "/usr/local/lib/python3.9/site-packages/pyneuroml/lib/jNeuroML-0.10.3-jar-with-dependencies.jar"  "/tmp/tmp2ibib1ju.xml"  -nogui -I ''' returned non-zero exit status 1.

      pyNeuroML >>>  jNeuroML >>   jNeuroML v0.10.3

      pyNeuroML >>>  jNeuroML >>  Loading: /tmp/tmp2ibib1ju.xml with jLEMS, NO GUI mode...

      pyNeuroML >>>  jNeuroML >>  org.lemsml.jlems.core.sim.ContentError: Can't find file at path: NaConductance.channel.nml

      pyNeuroML >>>  jNeuroML >>  Search directories are: [/tmp/tmprfujuesf, /tmp, /tmp, /tmp/tmprfujuesf]

      pyNeuroML >>>  jNeuroML >>  Search paths in jar are: [/NeuroML2CoreTypes]

      pyNeuroML >>>  jNeuroML >>

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.io.reader.JarResourceInclusionReader.getRelativeContent(JarResourceInclusionReader.java:179)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.getRelativeContent(NeuroMLInclusionReader.java:61)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.getIncludeContent(AbstractInclusionReader.java:41)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.insertIncludes(AbstractInclusionReader.java:71)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.insertIncludes(NeuroMLInclusionReader.java:102)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.read(AbstractInclusionReader.java:24)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:259)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:245)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils$1.importFile(Utils.java:505)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.viz.datadisplay.ControlPanel.initialise(ControlPanel.java:134)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.loadLemsFile(Utils.java:516)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.runLemsFile(Utils.java:493)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.JNeuroML.main(JNeuroML.java:595)

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:44  (INFO) Loading LEMS file from: /tmp/tmp2ibib1ju.xml

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:44  (INFO) Reading from: /tmp/tmp2ibib1ju.xml

      pyNeuroML >>>  jNeuroML >>

sedml.SimulatorSupportsRepeatedTasksWithMultipleSubTasks (10.6 s)
Test that a simulator supports repeated tasks with multiple subtasks
Reason for skip:
The image 'ghcr.io/biosimulators/biosimulators_pyneuroml/netpyne:<IP_ADDRESS>' could not execute the archive:

  Unknown error

Log:
/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The SED document is potentially incorrect.

  - Output `__repeated_task_report` may be invalid.

    - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The COMBINE/OMEX archive may be invalid.

  - The SED-ML file at location `simulation.sedml` may be invalid.

    - Output `__repeated_task_report` may be invalid.

      - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

Archive contains 1 SED-ML documents with 1 models, 1 simulations, 2 tasks, 2 reports, and 0 plots:

  simulation.sedml:

    Tasks (2):

      __repeated_task_0

      task

    Reports (2):

      __repeated_task_report: 5 data sets

      task_report: 5 data sets

Executing SED-ML file 0: simulation.sedml ...

Bundling outputs ...

Cleaning up ...

============= SUMMARY =============

Executed 1 SED documents:

  SED documents (1):

    Succeeded: 0

    Skipped: 0

    Failed: 1

  Tasks (2):

    Succeeded: 1

    Skipped: 0

    Failed: 1

  Outputs (2):

    Succeeded: 1

    Skipped: 1

    Failed: 0

The COMBINE/OMEX did not execute successfully:

  The SED document did not execute successfully:

    `pyNeuroML` was not able to execute `/tmp/tmptal4w7qd.xml`:

      pyNeuroML >>> *** Problem running command:

      pyNeuroML >>>        Command 'java -Xmx5727M  -Djava.awt.headless=true -jar  "/usr/local/lib/python3.9/site-packages/pyneuroml/lib/jNeuroML-0.10.3-jar-with-dependencies.jar"  "/tmp/tmp2_kr3ut4.xml"  -nogui -I ''' returned non-zero exit status 1.

      pyNeuroML >>>  jNeuroML >>   jNeuroML v0.10.3

      pyNeuroML >>>  jNeuroML >>  Loading: /tmp/tmp2_kr3ut4.xml with jLEMS, NO GUI mode...

      pyNeuroML >>>  jNeuroML >>  org.lemsml.jlems.core.sim.ContentError: Can't find file at path: NaConductance.channel.nml

      pyNeuroML >>>  jNeuroML >>  Search directories are: [/tmp/tmpnly5zik1, /tmp, /tmp, /tmp/tmpnly5zik1]

      pyNeuroML >>>  jNeuroML >>  Search paths in jar are: [/NeuroML2CoreTypes]

      pyNeuroML >>>  jNeuroML >>

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.io.reader.JarResourceInclusionReader.getRelativeContent(JarResourceInclusionReader.java:179)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.getRelativeContent(NeuroMLInclusionReader.java:61)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.getIncludeContent(AbstractInclusionReader.java:41)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.insertIncludes(AbstractInclusionReader.java:71)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.insertIncludes(NeuroMLInclusionReader.java:102)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.read(AbstractInclusionReader.java:24)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:259)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:245)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils$1.importFile(Utils.java:505)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.viz.datadisplay.ControlPanel.initialise(ControlPanel.java:134)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.loadLemsFile(Utils.java:516)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.runLemsFile(Utils.java:493)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.JNeuroML.main(JNeuroML.java:595)

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:44  (INFO) Loading LEMS file from: /tmp/tmp2_kr3ut4.xml

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:44  (INFO) Reading from: /tmp/tmp2_kr3ut4.xml

      pyNeuroML >>>  jNeuroML >>

sedml.SimulatorSupportsRepeatedTasksWithNestedFunctionalRanges (10.5 s)
Test that a simulator supports repeated tasks over nested functional ranges based on model (specification) variables
Reason for skip:
The image 'ghcr.io/biosimulators/biosimulators_pyneuroml/netpyne:<IP_ADDRESS>' could not execute the archive:

  Unknown error

Log:
/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The SED document is potentially incorrect.

  - Output `__repeated_task_report` may be invalid.

    - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The COMBINE/OMEX archive may be invalid.

  - The SED-ML file at location `simulation.sedml` may be invalid.

    - Output `__repeated_task_report` may be invalid.

      - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

Archive contains 1 SED-ML documents with 1 models, 1 simulations, 2 tasks, 2 reports, and 0 plots:

  simulation.sedml:

    Tasks (2):

      __repeated_task_0

      task

    Reports (2):

      __repeated_task_report: 5 data sets

      task_report: 5 data sets

Executing SED-ML file 0: simulation.sedml ...

Bundling outputs ...

Cleaning up ...

============= SUMMARY =============

Executed 1 SED documents:

  SED documents (1):

    Succeeded: 0

    Skipped: 0

    Failed: 1

  Tasks (2):

    Succeeded: 1

    Skipped: 0

    Failed: 1

  Outputs (2):

    Succeeded: 1

    Skipped: 1

    Failed: 0

The COMBINE/OMEX did not execute successfully:

  The SED document did not execute successfully:

    `pyNeuroML` was not able to execute `/tmp/tmp0r5xzkr5.xml`:

      pyNeuroML >>> *** Problem running command:

      pyNeuroML >>>        Command 'java -Xmx5732M  -Djava.awt.headless=true -jar  "/usr/local/lib/python3.9/site-packages/pyneuroml/lib/jNeuroML-0.10.3-jar-with-dependencies.jar"  "/tmp/tmp_9i5zqql.xml"  -nogui -I ''' returned non-zero exit status 1.

      pyNeuroML >>>  jNeuroML >>   jNeuroML v0.10.3

      pyNeuroML >>>  jNeuroML >>  Loading: /tmp/tmp_9i5zqql.xml with jLEMS, NO GUI mode...

      pyNeuroML >>>  jNeuroML >>  org.lemsml.jlems.core.sim.ContentError: Can't find file at path: NaConductance.channel.nml

      pyNeuroML >>>  jNeuroML >>  Search directories are: [/tmp/tmpa4oqzagy, /tmp, /tmp, /tmp/tmpa4oqzagy]

      pyNeuroML >>>  jNeuroML >>  Search paths in jar are: [/NeuroML2CoreTypes]

      pyNeuroML >>>  jNeuroML >>

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.io.reader.JarResourceInclusionReader.getRelativeContent(JarResourceInclusionReader.java:179)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.getRelativeContent(NeuroMLInclusionReader.java:61)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.getIncludeContent(AbstractInclusionReader.java:41)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.insertIncludes(AbstractInclusionReader.java:71)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.insertIncludes(NeuroMLInclusionReader.java:102)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.read(AbstractInclusionReader.java:24)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:259)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:245)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils$1.importFile(Utils.java:505)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.viz.datadisplay.ControlPanel.initialise(ControlPanel.java:134)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.loadLemsFile(Utils.java:516)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.runLemsFile(Utils.java:493)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.JNeuroML.main(JNeuroML.java:595)

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:44  (INFO) Loading LEMS file from: /tmp/tmp_9i5zqql.xml

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:44  (INFO) Reading from: /tmp/tmp_9i5zqql.xml

      pyNeuroML >>>  jNeuroML >>

sedml.SimulatorSupportsRepeatedTasksWithNestedRepeatedTasks (11.4 s)
Test that a simulator supports nested repeated tasks
Reason for skip:
The image 'ghcr.io/biosimulators/biosimulators_pyneuroml/netpyne:<IP_ADDRESS>' could not execute the archive:

  Unknown error

Log:
/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The SED document is potentially incorrect.

  - Output `__repeated_task_report` may be invalid.

    - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The COMBINE/OMEX archive may be invalid.

  - The SED-ML file at location `simulation.sedml` may be invalid.

    - Output `__repeated_task_report` may be invalid.

      - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

Archive contains 1 SED-ML documents with 1 models, 1 simulations, 3 tasks, 2 reports, and 0 plots:

  simulation.sedml:

    Tasks (3):

      __repeated_task_0

      __repeated_task_1

      task

    Reports (2):

      __repeated_task_report: 5 data sets

      task_report: 5 data sets

Executing SED-ML file 0: simulation.sedml ...

Bundling outputs ...

Cleaning up ...

============= SUMMARY =============

Executed 1 SED documents:

  SED documents (1):

    Succeeded: 0

    Skipped: 0

    Failed: 1

  Tasks (3):

    Succeeded: 1

    Skipped: 0

    Failed: 2

  Outputs (2):

    Succeeded: 1

    Skipped: 1

    Failed: 0

The COMBINE/OMEX did not execute successfully:

  The SED document did not execute successfully:

    `pyNeuroML` was not able to execute `/tmp/tmp27ggh9hu.xml`:

      pyNeuroML >>> *** Problem running command:

      pyNeuroML >>>        Command 'java -Xmx5723M  -Djava.awt.headless=true -jar  "/usr/local/lib/python3.9/site-packages/pyneuroml/lib/jNeuroML-0.10.3-jar-with-dependencies.jar"  "/tmp/tmpakpcr1wj.xml"  -nogui -I ''' returned non-zero exit status 1.

      pyNeuroML >>>  jNeuroML >>   jNeuroML v0.10.3

      pyNeuroML >>>  jNeuroML >>  Loading: /tmp/tmpakpcr1wj.xml with jLEMS, NO GUI mode...

      pyNeuroML >>>  jNeuroML >>  org.lemsml.jlems.core.sim.ContentError: Can't find file at path: NaConductance.channel.nml

      pyNeuroML >>>  jNeuroML >>  Search directories are: [/tmp/tmp2b4lt68l, /tmp, /tmp, /tmp/tmp2b4lt68l]

      pyNeuroML >>>  jNeuroML >>  Search paths in jar are: [/NeuroML2CoreTypes]

      pyNeuroML >>>  jNeuroML >>

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.io.reader.JarResourceInclusionReader.getRelativeContent(JarResourceInclusionReader.java:179)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.getRelativeContent(NeuroMLInclusionReader.java:61)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.getIncludeContent(AbstractInclusionReader.java:41)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.insertIncludes(AbstractInclusionReader.java:71)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.insertIncludes(NeuroMLInclusionReader.java:102)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.read(AbstractInclusionReader.java:24)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:259)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:245)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils$1.importFile(Utils.java:505)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.viz.datadisplay.ControlPanel.initialise(ControlPanel.java:134)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.loadLemsFile(Utils.java:516)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.runLemsFile(Utils.java:493)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.JNeuroML.main(JNeuroML.java:595)

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:44  (INFO) Loading LEMS file from: /tmp/tmpakpcr1wj.xml

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:44  (INFO) Reading from: /tmp/tmpakpcr1wj.xml

      pyNeuroML >>>  jNeuroML >>

    `pyNeuroML` was not able to execute `/tmp/tmp1imwlr8g.xml`:

      pyNeuroML >>> *** Problem running command:

      pyNeuroML >>>        Command 'java -Xmx5724M  -Djava.awt.headless=true -jar  "/usr/local/lib/python3.9/site-packages/pyneuroml/lib/jNeuroML-0.10.3-jar-with-dependencies.jar"  "/tmp/tmp6nsx194_.xml"  -nogui -I ''' returned non-zero exit status 1.

      pyNeuroML >>>  jNeuroML >>   jNeuroML v0.10.3

      pyNeuroML >>>  jNeuroML >>  Loading: /tmp/tmp6nsx194_.xml with jLEMS, NO GUI mode...

      pyNeuroML >>>  jNeuroML >>  org.lemsml.jlems.core.sim.ContentError: Can't find file at path: NaConductance.channel.nml

      pyNeuroML >>>  jNeuroML >>  Search directories are: [/tmp/tmphn750ij4, /tmp, /tmp, /tmp/tmphn750ij4]

      pyNeuroML >>>  jNeuroML >>  Search paths in jar are: [/NeuroML2CoreTypes]

      pyNeuroML >>>  jNeuroML >>

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.io.reader.JarResourceInclusionReader.getRelativeContent(JarResourceInclusionReader.java:179)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.getRelativeContent(NeuroMLInclusionReader.java:61)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.getIncludeContent(AbstractInclusionReader.java:41)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.insertIncludes(AbstractInclusionReader.java:71)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.insertIncludes(NeuroMLInclusionReader.java:102)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.read(AbstractInclusionReader.java:24)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:259)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:245)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils$1.importFile(Utils.java:505)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.viz.datadisplay.ControlPanel.initialise(ControlPanel.java:134)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.loadLemsFile(Utils.java:516)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.runLemsFile(Utils.java:493)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.JNeuroML.main(JNeuroML.java:595)

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:44  (INFO) Loading LEMS file from: /tmp/tmp6nsx194_.xml

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:44  (INFO) Reading from: /tmp/tmp6nsx194_.xml

      pyNeuroML >>>  jNeuroML >>

sedml.SimulatorSupportsRepeatedTasksWithSubTasksOfMixedTypes (11.1 s)
Test that a simulator supports repeated tasks whose sub-tasks have mixed types. Also tests that sub-types executed in order of the values of their order attributes and that reports of the results of repeated tasks handle sub-tasks to produce results of different shapes.
Reason for skip:
The image 'ghcr.io/biosimulators/biosimulators_pyneuroml/netpyne:<IP_ADDRESS>' could not execute the archive:

  Unknown error

Log:
/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The SED document is potentially incorrect.

  - Task `__repeated_task_1` may be invalid.

    - The outputs of the sub-tasks have different shapes.

  - Output `__repeated_task_report` may be invalid.

    - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The COMBINE/OMEX archive may be invalid.

  - The SED-ML file at location `simulation.sedml` may be invalid.

    - Task `__repeated_task_1` may be invalid.

      - The outputs of the sub-tasks have different shapes.

    - Output `__repeated_task_report` may be invalid.

      - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

Archive contains 1 SED-ML documents with 1 models, 1 simulations, 3 tasks, 2 reports, and 0 plots:

  simulation.sedml:

    Tasks (3):

      __repeated_task_0

      __repeated_task_1

      task

    Reports (2):

      __repeated_task_report: 5 data sets

      task_report: 5 data sets

Executing SED-ML file 0: simulation.sedml ...

Bundling outputs ...

Cleaning up ...

============= SUMMARY =============

Executed 1 SED documents:

  SED documents (1):

    Succeeded: 0

    Skipped: 0

    Failed: 1

  Tasks (3):

    Succeeded: 1

    Skipped: 0

    Failed: 2

  Outputs (2):

    Succeeded: 1

    Skipped: 1

    Failed: 0

The COMBINE/OMEX did not execute successfully:

  The SED document did not execute successfully:

    `pyNeuroML` was not able to execute `/tmp/tmpi33rla1f.xml`:

      pyNeuroML >>> *** Problem running command:

      pyNeuroML >>>        Command 'java -Xmx5727M  -Djava.awt.headless=true -jar  "/usr/local/lib/python3.9/site-packages/pyneuroml/lib/jNeuroML-0.10.3-jar-with-dependencies.jar"  "/tmp/tmp79tc56bj.xml"  -nogui -I ''' returned non-zero exit status 1.

      pyNeuroML >>>  jNeuroML >>   jNeuroML v0.10.3

      pyNeuroML >>>  jNeuroML >>  Loading: /tmp/tmp79tc56bj.xml with jLEMS, NO GUI mode...

      pyNeuroML >>>  jNeuroML >>  org.lemsml.jlems.core.sim.ContentError: Can't find file at path: NaConductance.channel.nml

      pyNeuroML >>>  jNeuroML >>  Search directories are: [/tmp/tmpjjoeuesh, /tmp, /tmp, /tmp/tmpjjoeuesh]

      pyNeuroML >>>  jNeuroML >>  Search paths in jar are: [/NeuroML2CoreTypes]

      pyNeuroML >>>  jNeuroML >>

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.io.reader.JarResourceInclusionReader.getRelativeContent(JarResourceInclusionReader.java:179)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.getRelativeContent(NeuroMLInclusionReader.java:61)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.getIncludeContent(AbstractInclusionReader.java:41)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.insertIncludes(AbstractInclusionReader.java:71)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.insertIncludes(NeuroMLInclusionReader.java:102)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.read(AbstractInclusionReader.java:24)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:259)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:245)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils$1.importFile(Utils.java:505)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.viz.datadisplay.ControlPanel.initialise(ControlPanel.java:134)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.loadLemsFile(Utils.java:516)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.runLemsFile(Utils.java:493)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.JNeuroML.main(JNeuroML.java:595)

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:45  (INFO) Loading LEMS file from: /tmp/tmp79tc56bj.xml

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:45  (INFO) Reading from: /tmp/tmp79tc56bj.xml

      pyNeuroML >>>  jNeuroML >>

    `pyNeuroML` was not able to execute `/tmp/tmps86m6oib.xml`:

      pyNeuroML >>> *** Problem running command:

      pyNeuroML >>>        Command 'java -Xmx5727M  -Djava.awt.headless=true -jar  "/usr/local/lib/python3.9/site-packages/pyneuroml/lib/jNeuroML-0.10.3-jar-with-dependencies.jar"  "/tmp/tmpaxq67eje.xml"  -nogui -I ''' returned non-zero exit status 1.

      pyNeuroML >>>  jNeuroML >>   jNeuroML v0.10.3

      pyNeuroML >>>  jNeuroML >>  Loading: /tmp/tmpaxq67eje.xml with jLEMS, NO GUI mode...

      pyNeuroML >>>  jNeuroML >>  org.lemsml.jlems.core.sim.ContentError: Can't find file at path: NaConductance.channel.nml

      pyNeuroML >>>  jNeuroML >>  Search directories are: [/tmp/tmpfik9i2zi, /tmp, /tmp, /tmp/tmpfik9i2zi]

      pyNeuroML >>>  jNeuroML >>  Search paths in jar are: [/NeuroML2CoreTypes]

      pyNeuroML >>>  jNeuroML >>

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.io.reader.JarResourceInclusionReader.getRelativeContent(JarResourceInclusionReader.java:179)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.getRelativeContent(NeuroMLInclusionReader.java:61)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.getIncludeContent(AbstractInclusionReader.java:41)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.insertIncludes(AbstractInclusionReader.java:71)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.insertIncludes(NeuroMLInclusionReader.java:102)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.read(AbstractInclusionReader.java:24)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:259)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:245)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils$1.importFile(Utils.java:505)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.viz.datadisplay.ControlPanel.initialise(ControlPanel.java:134)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.loadLemsFile(Utils.java:516)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.runLemsFile(Utils.java:493)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.JNeuroML.main(JNeuroML.java:595)

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:45  (INFO) Loading LEMS file from: /tmp/tmpaxq67eje.xml

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:45  (INFO) Reading from: /tmp/tmpaxq67eje.xml

      pyNeuroML >>>  jNeuroML >>

sedml.SimulatorSupportsRepeatedTasksWithVectorRanges (10.3 s)
Test that a simulator supports repeated tasks over vector ranges
Reason for skip:
The image 'ghcr.io/biosimulators/biosimulators_pyneuroml/netpyne:<IP_ADDRESS>' could not execute the archive:

  Unknown error

Log:
/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The SED document is potentially incorrect.

  - Output `__repeated_task_report` may be invalid.

    - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

/usr/local/lib/python3.9/site-packages/biosimulators_utils/warnings.py:31: BioSimulatorsWarning: The COMBINE/OMEX archive may be invalid.

  - The SED-ML file at location `simulation.sedml` may be invalid.

    - Output `__repeated_task_report` may be invalid.

      - Some simulation tools will not be able to generate this output because it uses data from repeated tasks. Output for repeated tasks is an experimental feature of SED-ML, which is not officially supported.

  warnings.warn(termcolor.colored(message, Colors.warning.value), category)

Archive contains 1 SED-ML documents with 1 models, 1 simulations, 2 tasks, 2 reports, and 0 plots:

  simulation.sedml:

    Tasks (2):

      __repeated_task_0

      task

    Reports (2):

      __repeated_task_report: 5 data sets

      task_report: 5 data sets

Executing SED-ML file 0: simulation.sedml ...

Bundling outputs ...

Cleaning up ...

============= SUMMARY =============

Executed 1 SED documents:

  SED documents (1):

    Succeeded: 0

    Skipped: 0

    Failed: 1

  Tasks (2):

    Succeeded: 1

    Skipped: 0

    Failed: 1

  Outputs (2):

    Succeeded: 1

    Skipped: 1

    Failed: 0

The COMBINE/OMEX did not execute successfully:

  The SED document did not execute successfully:

    `pyNeuroML` was not able to execute `/tmp/tmp2c9om8uk.xml`:

      pyNeuroML >>> *** Problem running command:

      pyNeuroML >>>        Command 'java -Xmx5728M  -Djava.awt.headless=true -jar  "/usr/local/lib/python3.9/site-packages/pyneuroml/lib/jNeuroML-0.10.3-jar-with-dependencies.jar"  "/tmp/tmp65f4pw9x.xml"  -nogui -I ''' returned non-zero exit status 1.

      pyNeuroML >>>  jNeuroML >>   jNeuroML v0.10.3

      pyNeuroML >>>  jNeuroML >>  Loading: /tmp/tmp65f4pw9x.xml with jLEMS, NO GUI mode...

      pyNeuroML >>>  jNeuroML >>  org.lemsml.jlems.core.sim.ContentError: Can't find file at path: NaConductance.channel.nml

      pyNeuroML >>>  jNeuroML >>  Search directories are: [/tmp/tmptq4adsey, /tmp, /tmp, /tmp/tmptq4adsey]

      pyNeuroML >>>  jNeuroML >>  Search paths in jar are: [/NeuroML2CoreTypes]

      pyNeuroML >>>  jNeuroML >>

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.io.reader.JarResourceInclusionReader.getRelativeContent(JarResourceInclusionReader.java:179)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.getRelativeContent(NeuroMLInclusionReader.java:61)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.getIncludeContent(AbstractInclusionReader.java:41)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.insertIncludes(AbstractInclusionReader.java:71)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.NeuroMLInclusionReader.insertIncludes(NeuroMLInclusionReader.java:102)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.core.sim.AbstractInclusionReader.read(AbstractInclusionReader.java:24)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:259)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.readLemsNeuroMLFile(Utils.java:245)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils$1.importFile(Utils.java:505)

      pyNeuroML >>>  jNeuroML >>  	at org.lemsml.jlems.viz.datadisplay.ControlPanel.initialise(ControlPanel.java:134)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.loadLemsFile(Utils.java:516)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.export.utils.Utils.runLemsFile(Utils.java:493)

      pyNeuroML >>>  jNeuroML >>  	at org.neuroml.JNeuroML.main(JNeuroML.java:595)

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:45  (INFO) Loading LEMS file from: /tmp/tmp65f4pw9x.xml

      pyNeuroML >>>  jNeuroML >>  INFO Aug 21,2021 19:45  (INFO) Reading from: /tmp/tmp65f4pw9x.xml

      pyNeuroML >>>  jNeuroML >>

sedml.SimulatorSupportsSubstitutingAlgorithms (31.3 s)
Check that a simulator can substitute algorithms that it doesn't implement with similar algorithms when the algorithm substitution policy is less restrictive than :obj:AlgorithmSubstitutionPolicy.SAME_METHOD. Also check that a simulator ignores unsupported algorithm parameters when the algorithm substitution policy is less restrictive than :obj:AlgorithmSubstitutionPolicy.NONE.
Reason for skip:
The image 'ghcr.io/biosimulators/biosimulators_pyneuroml/netpyne:<IP_ADDRESS>' could not execute the archive:

  Unknown error

Log:
Archive contains 1 SED-ML documents with 1 models, 1 simulations, 1 tasks, 1 reports, and 0 plots:

  simulation.sedml:

    Tasks (1):

      task

    Reports (1):

      report: 5 data sets

Executing SED-ML file 0: simulation.sedml ...

Bundling outputs ...

Cleaning up ...

============= SUMMARY =============

Executed 1 SED documents:

  SED documents (1):

    Succeeded: 0

    Skipped: 0

    Failed: 1

  Tasks (1):

    Succeeded: 0

    Skipped: 0

    Failed: 1

  Outputs (1):

    Succeeded: 0

    Skipped: 1

    Failed: 0

The COMBINE/OMEX did not execute successfully:

  The SED document did not execute successfully:

    No algorithm can be substituted for 'LSODA' (KISAO_0000088) at substitution policy 'NONE'. Algorithms can only be substituted for the following algorithm ...

Warnings
cli.CliDescribesSupportedEnvironmentVariablesInline (5.2 s)
Test that the inline help for a command-line interface describes the environment variables that the simulator supports.
Warnings:
The inline help for a command-line interface for a simulation tool should describe the environment variables that the simulation tool supports.

The command-line interface does not describe the following standard environment variables recognized by BioSimulators:
  - 'ALGORITHM_SUBSTITUTION_POLICY'
  - 'BUNDLE_OUTPUTS'
  - 'DEBUG'
  - 'H5_REPORTS_PATH'
  - 'KEEP_INDIVIDUAL_OUTPUTS'
  - 'LOG_PATH'
  - 'PLOTS_PATH'
  - 'REPORTS_PATH'
  - 'REPORT_FORMATS'
  - 'SAVE_PLOT_DATA'
  - 'VALIDATE_IMAGES'
  - 'VALIDATE_OMEX_MANIFESTS'
  - 'VALIDATE_OMEX_METADATA'
  - 'VALIDATE_SEDML'
  - 'VALIDATE_SEDML_MODELS'
  - 'VERBOSE'
  - 'VIZ_FORMATS'

If the simulation tool implements these variables, they should be described in the inline help for its command-line interface.

Note, support for these environment variables is optional. Simulation tools are not required to support these variables.

Log:

docker_image.DeclaresSupportedEnvironmentVariables (2.4 s)
Test if a Docker image declares the environment variables that is supports
Warnings:
Docker images for simulation tools should declare the environment variables that they support.

The Docker image does not declare the following standard environment variables recognized by BioSimulators:
  - 'ALGORITHM_SUBSTITUTION_POLICY'
  - 'BUNDLE_OUTPUTS'
  - 'DEBUG'
  - 'H5_REPORTS_PATH'
  - 'KEEP_INDIVIDUAL_OUTPUTS'
  - 'LOG_PATH'
  - 'PLOTS_PATH'
  - 'REPORTS_PATH'
  - 'REPORT_FORMATS'
  - 'SAVE_PLOT_DATA'
  - 'VALIDATE_IMAGES'
  - 'VALIDATE_OMEX_MANIFESTS'
  - 'VALIDATE_OMEX_METADATA'
  - 'VALIDATE_SEDML'
  - 'VALIDATE_SEDML_MODELS'
  - 'VIZ_FORMATS'

If the simulation tool implements these variables, they should be declared in the Dockerfile for the Docker image for the simulator.

Note, support for these environment variables is optional. Simulation tools are not required to support these variables.

Log:

docker_image.HasBioContainersLabels (0.5 s)
Test that a Docker image has BioContainers labels with metadata about the image
Warnings:
The Docker image should have the following BioContainers labels:
  extra.identifiers.biotools

Log:

published_project.SimulatorCanExecutePublishedProject:neuroml-lems/Hodgkin-Huxley-cell-CVODE (14.4 s)
Required model formats and simulation algorithms for SED tasks:

Format: format_9004
Algorithm: KISAO_0000019

Warnings:
Unexpected reports were produced:
  simulation.sedml/plot

Log:
Archive contains 1 SED-ML documents with 1 models, 1 simulations, 1 tasks, 1 reports, and 1 plots:

  simulation.sedml:

    Tasks (1):

      task

    Reports (1):

      report: 5 data sets

    Plots (1):

      plot: 4 curves

Executing SED-ML file 0: simulation.sedml ...

Bundling outputs ...

Cleaning up ...

============= SUMMARY =============

Executed 1 SED documents:

  SED documents (1):

    Succeeded: 1

    Skipped: 0

    Failed: 0

  Tasks (1):

    Succeeded: 1

    Skipped: 0

    Failed: 0

  Outputs (2):

    Succeeded: 2

    Skipped: 0

    Failed: 0

The image for your simulator is valid!

Your submission was committed to the BioSimulators registry. Thank you!
Future submissions of subsequent versions of netpyne to the BioSimulators registry will be automatically validated. These submissions will not require manual review by the BioSimulators Team.


Add hotkey to optimize feature list

Add hotkey action for "O" which will "optimize" the generated feature list by passing in all classes and user-specified features to the binary scanner.

This will be addressed by https://github.com/OpenLiberty/ci.common/pull/304 which enables the hotkey to call a method to generate features with all classes and user specified features.  The actual implementation of that method to generate features with all classes and user specified features will be part of https://github.com/OpenLiberty/ci.maven/issues/1263


Plots are unreadable when dark github theme is used

Consider either setting a white background for the plot images or at least not using black on transparent.

Closing as a duplicate of #2


Remove the premissions-misconifguration bug workarounds on CI

Given https://github.com/actions/cache/issues/133 is closed we might be lucky to remove the workarounds

Nice!
bors r+


Connectors: fix default value logic and export functions to yml

✅ No public API change.

✅ No public API change.


Diactoros support

Any reason that diactoros isn't supported for discovery?

It is supported:
https://github.com/php-http/message/blob/master/src/MessageFactory/DiactorosMessageFactory.php
It is automatically discovered when php-http/message is installed thanks to Puli.

It's not listed on http://php-http.org/en/latest/clients.html

Not sure I can follow. Diactoros is a message implementation, not a client.
Although it seems that the actual documentation for Guzzle and Diactoros factories are got lost in the middle of conversion to RST. /cc @ddeboer
It is mentioned here:
http://php-http.org/en/latest/message.html

i think it was never on that page. with the title of "Clients & Adapters", we should link to the message factory implementations page - reading the TOC when not too familiar with the naming, its not clear that messages are somewhere else and this is only about HTTPlug adapters.

Okay, that makes sense but it's really not clear at all. The docs should really have a table that shows all of the supported PSR-7 implementations and what kind of support they include. The headings would be something like:

Project
Client
ServerRequest
Request
Response
Stream
Uri
FileUpload

Guzzle5
x
-
x
x
x
x
x

Diactoros
-
x
x
x
x
x
x

That's a good idea.
One question though: how is client related to the message implementation? Those are two separate things.
(Also, I guess it is Guzzle 6, right?)

I see "client" as a separate designation to make it clear that the adapter supports sending HTTP requests, not just generating them. As you said, Diactoros is not a HTTP client but Guzzle is.
Personally I still find HTTPlug pretty heavy to abstraction. I think a lot would be gained by making the code less "smart" and having more hard-coded aliases in place.

@shadowhand good idea! do you want to do a PR to add a page "Message Factory Implementations" in the Message section and add this table there? it should link to the factory concept explanation and then have this table you proposed and the class names for those factories.
@sagikazarmark "how is client related to the message implementation": before i started contributing to php-http, i would not have been able to spot the difference between guzzle the http client and guzzle the (psr7) request / response implementation. its kind of not-obvious to separate them. (i agree it technically makes sense, but the doc needs to help avoid the confusion).

re: abstraction: i don't see how HTTPlug could not be abstract - it only an interface about sending psr requests and returning psr responses which are described purely as interfaces. when you write an application, this might well be enough abstraction for you, and you can do new Guzzle\Psr\Response (or whatever the exact namespace is). when writing a reusable library that needs to do http requests, you really want the abstraction to avoid binding to a specific message implementation. you want the factory and HTTPlug injected and only use those. then users of the library can choose both client and message implementation themselves.

but if you have concrete cases where a php-http part tries too much to be "smart", please point them out. now we can still fix things, and if we can simplify without creating hard limits, i am all for it.

Using Puli for example... just adds a whole new layer of abstraction that really doesn't need to be there.

well, discovery in itself is a tricky business. with puli, there is at least a decent solution if one wants to do it.
but i think most of the time, rather than using discovery, you want to instantiate the correct client, adapter and factory yourself and inject that in your classes. or use the HttplugBundle when using symfony. in those situations, you don't need php-http/discovery at all.

Why is it tricky? That sounds like a solution in search of a problem. Why isn't it as simple as having a list of supported classes and searching for one that is available?

That was the initial plan, but that required maintenance and it was less flexible.
With puli, it is enough to place a puli.json in the package root and discovery will find it. No need to maintain a static list of resources and it even works with your custom implementations, which wouldn't make it to the core repository anyway.

Sure it would require a minimal amount of maintenance. I'd take that over the overhead of Puli.

Actually maintenance is not the biggest problem, but the mentioned features worth having puli IMO.
Also, using puli is ALMOST transparent, if not 100%. See puli/issues#165

@shadowhand are there any unclear parts left about diactoros being supported?
Please don't hesitate asking if you have any questions.

@shadowhand we made Puli optional by reintroducing some custom strategies in #59


Failed to load next.config.js and 'hls.js' doesn't contain a default export

When I tried to install the library or run the video sync command. I got this error in my terminal, but the further process continued.

My project structure.

I somehow edited the next.config.js file manually using docs. But you can fix it.
When I tried to run the app. I got this error -

Which crashed the app, how can I fix it?

Thanks for the heads up! I haven't seen this before when working with brand new next.js projects. Can you tell me anymore about your project that might help? Could it be a file system permissions issue? I think we're going to update the first error to provide more details.
The hls.js error I think happens when it's loaded on the server. Can you tell me about where/how you're loading he video in a page?

we just noticed that the hls.js error is probably the same issue than
https://github.com/muxinc/next-video/issues/109#issuecomment-1836679432
it's caused by a Next.js bundle bug. try upgrading to the latest canary or downgrading to 14.0.1 I think.

@heff I haven't modified anything regarding permissions just created the next app using the cmd mentioned in next.js docs.
As far as video is concerned I'm just exporting a react component which returns the Video component provided by next-video. And is rendered on page.

2nd issue is fixed in https://github.com/muxinc/next-video/issues/109#issuecomment-1846333718
it was a Next.js bug
the 1st issue, could it be caused by you having run npx next-video sync not in the root folder of your next.js project?
it requires a next.config.js or next.config.mjs in the current working directory...
I'm closing but please let me know if you keep running into the 1st issue.


eliminate cpu architecture constraint for nvcc

This PR simply removes the @platforms//cpu:x86_64 constraint from the nvcc toolchain template. I'm not sure if this is the preferred way to achieve this, but CUDA on linux is compatible with aarch64 for both servers and embedded use cases. This enables builds with on these platforms as well.

It might need some extra work if you remove that constraint. The toolchain itself needs more configuration to take care of. I am not familiar with cross compiling, could you please share some basic project setup with me so that I can test it out?

Hi @cloudhan. Nice project, by the way.
Indeed this change is not sufficient for cross compiling. This is to enable your rules to work on a native aarch64 system. If you try running arm64 bazel on an arm server or a jetson device natively, bazel fails to determine a toolchain that can work (despite having all the requisite developer tools):
ERROR: /home/ryan/devel/rules_cuda/examples/basic/BUILD.bazel:5:13: While resolving toolchains for target //examples/basic:kernel: no matching toolchains found for types //cuda:toolchain_type

You can at least test compilation (but not executing the compiled code) with multiarch docker via qemu.
# set up your host for qemu docker
sudo apt-get install qemu binfmt-support qemu-user-static
docker run --rm --privileged multiarch/qemu-user-static --reset -p yes

# pull base cuda image for x86_64 and aarch64 architectures
docker pull nvcr.io/nvidia/cuda:11.7.0-devel-ubuntu20.04
docker pull --platform linux/arm64 nvcr.io/nvidia/cuda:11.7.0-devel-ubuntu20.04

# confirm that you qemu is working properly, first command should return `x86_64`, second `aarch64`
docker run --rm -t nvcr.io/nvidia/cuda:11.7.0-devel-ubuntu20.04 uname -m
docker run --platform linux/arm64 --rm -t nvcr.io/nvidia/cuda:11.7.0-devel-ubuntu20.04 uname -m

# get an interactive session going w/ qemu. map in rules_cuda repo
docker run --platform linux/arm64 -v $PATH_TO_RULES_CUDA:/workspace --rm -it nvcr.io/nvidia/cuda:11.7.0-devel-ubuntu20.04 /bin/bash

# inside container, install wget, download bazel
apt-get update && apt-get install -y wget
cd /usr/local/bin && wget https://github.com/bazelbuild/bazel/releases/download/5.2.0/bazel-5.2.0-linux-arm64 && mv bazel-5.2.0-linux-arm64 bazel && chmod u+x bazel

cd /workspace
bazel build //examples/basic:main
# fails to compile
# apply patch to remove constraint
bazel build //examples/basic:main
# succeeds

OK, lets merge it first since it won't break existing code.


Destination loaded only once

Is there any way of making LazyView load the wrapped view each time a navigationLink is tapped?
Currently it loads only once and reuses that view on subsequent navigations

you could try combining it with this technique https://github.com/joehinkle11/AutoRerenderingView

probably better if you rely on onAppear though

Thanks, I'll have a look into the AutoRenderingView. The problem that I see with onAppear() is that if I'm in a navigation stack and do a network call on appear, it will be done both when the view is pushed, as well as popped. An event hook similar to viewDidLoad would be best

you can always use this janky hack I use...make a static variable and put a "didLoad" flag there. Then check if it's already flipped on onAppear.
ahhh SwiftUI...


How to instantiate sleepMode

Total noob question: The readme states that the usage is
var sleepMode = new SleepMode();
However, that produces a build error as the class SleepMode is not found.
SleepModeBase cannot be instantiated because it is abstract, ISleepMode is an interface.
Please advise how to instantiate a new SleepMode object.

I copied this to my project from some previous version here on GitHub and compiled it, but I couldn't test it because I need this to run async. And async'ed it didn't avoid to go to sleep mode on iOS and Android (real devices running with USB disconnected and not debugging). Maybe it can help you more in something or maybe it's wrong:
namespace Xam.Plugins.ManageSleep
{
	/// <summary>
	/// Manage auto-sleep / auto-lock. This is useful when dealing with long running processes.
	/// </summary>
	public class SleepMode : SleepModeBase
	{
		/// <summary>
		/// Activates or desactivates the auto sleep mode. True to activate it (default), False to deactivate it.
		/// Use with caution: if you deactivated auto sleep you will need to reactivate it.
		/// DoWithoutSleep and DoWithoutSleepAsync methods are preferred since they automatically resume auto sleep.
		/// </summary>
		/// <param name="activateAutoSleepMode">If set to <c>true</c> activate auto sleep mode.</param>
		public override void ActivateAutoSleepMode(bool activateAutoSleepMode)
		{
			NotImplementedInReferenceAssembly();
		}

		internal static Exception NotImplementedInReferenceAssembly()
		{
			return new NotImplementedException("This functionality is not implemented in the portable version of this assembly.  You should reference the Xam.Plugins.TextToSpeech NuGet package from your main application project in order to reference the platform-specific implementation.");
		}
	}
}

@eternalbard I see. I didn't think to create my own class based on the interface.

@eternalbard Ultimately this was way to complicated to implement. I just decided to use Xamarin.Forms Dependency Service and platform specific code to accomplish the task.

Thanks, I think it's a good idea.


Enhance property matching in markup

Currently the property in markup is mapped on RedwoodProperties. When a redwood property is not found, we should try to map it to the actual property on the class.

Won't be implemented.


BZ1303024 - Fix for SSUI specific dynamic dropdown setup with auto refresh not working properly

Dates and date time dialog fields were not being handled correctly when refreshed, causing the default date to be set instead of the date that was sent back from the API. I also found an issue while testing where the first refresh of a date field would return a script error so that has been fixed as well.
https://bugzilla.redhat.com/show_bug.cgi?id=1303024

@himdel @AparnaKarve please review


Update devcontainer schema

Update the devcontainer schema to support parallel lifecycle scripts.
See https://github.com/devcontainers/spec/blob/main/proposals/parallel-lifecycle-script-execution.md for more information.

cc @chrmarti


aur-build: distcc support

Hi,
Would it be nice to have a distcc support added to aurbuild. Currently I've created /usr/share/devtools/makepkg-x86_64_distcc.conf with according distcc configuration and add --distcc switch to aurbuild to select this configuraiont, and append distcc alongside base-devel to mkarchroot.
I think a solution could be to infect options=(distcc) to PKBUILDs and export DISTCC_HOSTS environment variable to build chroot.
cheers, Bartus.

What you mention up until DISTCC_HOSTS should already be possible via aur-build -M and installing distcc with arch-nspawn /path/to/container pacman -S distcc (compare https://github.com/AladW/aurutils/blob/master/man1/aur-build-nspawn.1#L65-L66). For the latter, compare https://github.com/AladW/aurutils/issues/334#issuecomment-376008109

#370 should cover this issue and #334
Note that devtools shipped makepkg.conf doesn't change that often, so using a custom config makes more sense than a fragile approach of modifying PKGBUILDs.


Clarify authors vs. contributors

Discussions in the Governance Panel have shown that we need to

Update the PR templates so that enhancements can predicate an update to the author list, whereas defects predicate an update to the contributors list
Update Rules to be in line with the templates
Moving forward, list additional contributors by name. I’m not sure if it would be as straightforward looking back but would be open to that too.

This issue will help us pursue these items, but note that the first point will need to be pursued in the Conventions repo.

Thanks, @erget. Do you have text changes to propose to the rules?
As contributors to the conventions, I agree that we should name all those who've contributed a defect issue that has been implemented in the conventions document in GitHub. I think we can make best efforts to identify such contributors of trac tickets in the past as well.

Hi @JonathanGregory , not yet - I'm a bit short on time this week and haven't started following it up yet but I think once after the ESIP Summer Meeting ends next week I'll focus on concluding #122 first. There are a number of comments pending feedback - including from you - that I want to make sure don't go unaddressed before starting this one. Feel free to jump in if you like; otherwise I'll come back to it once I get a chance.


[SPARK-44299][SQL] Assign names to the error class _LEGACY_ERROR_TEMP_227[4-6,8]

What changes were proposed in this pull request?
The pr aims to assign names to the error class, include:

_LEGACY_ERROR_TEMP_2274 => UNSUPPORTED_FEATURE.REPLACE_NESTED_COLUMN
_LEGACY_ERROR_TEMP_2275 => CANNOT_INVOKE_IN_TRANSFORMATIONS
_LEGACY_ERROR_TEMP_2276 => UNSUPPORTED_FEATURE .HIVE_WITH_ANSI_INTERVALS
_LEGACY_ERROR_TEMP_2278 => INVALID_FORMAT.MISMATCH_INPUT

Why are the changes needed?
The changes improve the error framework.
Does this PR introduce any user-facing change?
No.
How was this patch tested?

Update & Add new UT.
Manually test.
Pass GA.

cc @MaxGekk

+1, LGTM. Merging to master.
Thank you, @panbingkun.


[BUG] [CAPR] Upgrading Rancher during etcd restoration from < v2.7.5 to v2.7.5+ can lead to implausible joined server for entry

Rancher Server Setup

Rancher version: v2.7.6

Information about the Cluster
Downstream CAPR K3s or RKE2
Describe the bug
If a Rancher installation is upgraded from before v2.7.5 to v2.7.5 or newer during an etcd restoration operation, it is possible to have the planner start stalling out on implausible joined server for entry.
To Reproduce
Run Rancher v2.7.3, and provision a cluster, break it, and attempt to restore it in a way that is not compatible with v2.7.3. Upgrade to v2.7.6 and attempt to restore the cluster -- observe that the planner will start to error out during etcd restoration shutdown plan generation as the joined-to annotation has not been set.
Result
Planner does not restore the cluster.
Expected Result
Planner restores the cluster.
Screenshots

Additional context
The temporary workaround for this issue is to annotate the machine plan secrets within the local cluster with the corresponding joined-to annotation that corresponds to the join URL of the new init node (the node you are going to restore the etcd snapshot to)
For RKE2 with an init node at <IP_ADDRESS> and a cluster called my-rke2-cluster, this would look like:
kubectl annotate secret -n fleet-default -l cluster.x-k8s.io/cluster-name=my-rke2-cluster,rke.cattle.io/init-node=true rke.cattle.io/join-url=https://<IP_ADDRESS>:9345
kubectl annotate secret -n fleet-default -l cluster.x-k8s.io/cluster-name=my-rke2-cluster,rke.cattle.io/init-node!=true rke.cattle.io/joined-to=https://<IP_ADDRESS>:9345

For a K3s cluster with an init node at <IP_ADDRESS> and a cluster called my-k3s-cluster, this would look like:
kubectl annotate secret -n fleet-default -l cluster.x-k8s.io/cluster-name=my-rke2-cluster,rke.cattle.io/init-node=true rke.cattle.io/join-url=https://<IP_ADDRESS>:6443
kubectl annotate secret -n fleet-default -l cluster.x-k8s.io/cluster-name=my-rke2-cluster,rke.cattle.io/init-node!=true rke.cattle.io/joined-to=https://<IP_ADDRESS>:6443

Note the port difference between K3s and RKE2.

Okay, I was able to come up with a solid reproduction to prove that the fix I am merging fixes this issue:

Provision 3 nodes total, and then provision a custom cluster with 1 controlplane+etcd node and 1 worker node using  K3s v1.23.17+k3s1 on Rancher v2.7.4 (NOTE: K3s version is important here because the newest K3s minors/patches have broken etcd snapshot functionality with 2.7.4)
Take 2 snapshots
Copy one of the snapshot files from the corresponding directory on the etcd node to your local machine
Go onto the server node and delete the snapshot from /var/lib/rancher/k3s/server/db/snapshots/
Attempt to do an “etcd only” restore of the snapshot that you just deleted
Wait for the restore to fail “operation etcd restore failed”
Delete the etcd machine from the cluster
Upgrade to v2.7.9
Wait for the etcd machine to be deleted from the cluster
Add your second, clean machine to the cluster
Copy the etcd snapshot (NOT THE ONE YOU ARE ALREADY TRYING TO RESTORE) to the NEW controlplane+etcd machine, into /var/lib/rancher/k3s/server/db/snapshots (make the directory if you need to, i.e. mkdir -p /var/lib/rancher/k3s/server/db/snapshots)
Restore this snapshot by setting the .spec.etcdSnapshotRestore.Name of the clusters.provisioning.cattle.io object to the name of the file you copied to your new node
Observe that the cluster will start erroring with the implausible joined server for entry error
Upgrade the cluster to a version that contains my merged fix
Watch the cluster go through its etcd restoration and come back to life

Moved out of v2.9-Next1 to v2.9-Next2 (with increased priority there) to free up QA capacity for higher priority issues.

Ticket #42856 - Test Results - ✅
Verified on Rancher v2.9-db81de3553c19f63d92666d13a71ba85a44e2142-head:

Scenario
Test Case
Result

1.
Reproduce issue, then upgrade to v2.9-head and watch cluster self-resolve
✅

Scenario 1 - ✅

Fresh install of HA Helm Rancher v2.7.4
Once active, provision a downstream Custom K3s cluster w/ k8s v1.23.17+k3s1 - [ 1 etcd/cp + 1 wkr ]
Once active, take two snapshots
Move one to your local machine, and delete the other
Snap/restore to deleted snapshot w/ etcd only option selected
Observe operation etcd restore failed error message
Attempt to delete etcd machine from cluster - (mine just hung in same error state)
Upgrade Rancher to v2.7.9
Re-delete etcd machine from cluster - (this time it was successfully removed)
Register new etcd/cp node to custom cluster
Create snapshot directory on newly registered etcd/cp node by running the following command:

mkdir -p /var/lib/rancher/k3s/server/db/snapshots

Move snapshot you're storing locally to directory you created in step 11, on newly registered etcd/cp node
Edit cluster object for downstream Custom k3s, and modify .spec.etcdSnapshotRestore.Name to reflect snapshot from step 12, then save yaml.  This should be formatted as shown below:

spec:
  rkeConfig:
    etcdSnapshotRestore:
      name: <cluster_name>-<snapshot_name>-local

Reproduced
Upgrade Rancher to v2.9-head
Once upgraded, observe etcd restore proceed and cluster come up active
Verified - planner is able to restore the cluster; as expected

Noting that the fix will be release noted in the v2.9.2 draft


[Docs]: Google sheets code snippets on documentation is generic and returns an error when we use it on the application

Is there an existing issue for this?

[X] I have searched the existing issues

Documentation Link
https://docs.appsmith.com/datasource-reference/querying-google-sheets#creating-queries
Describe the problem
Code snippets for various query types (create, update, insert....) are the same and don't have any difference even though the query types are different. Using these snippets on the application returns an error.
Describe the improvement
User expects to have a working snippet present in our documentation that provides ample information about expected structure and values.

@nidhi-nair - I've updated the code snippets as per UQI. Please verify.

LGTM @jnikhila

latest doc is published.


Job State is only tracked for the Extract and Load parts of an ELT pipeline

Migrated from GitLab: https://gitlab.com/meltano/meltano/-/issues/1050
Originally created by @iroussos on 2019-09-26 11:53:55

At our current version, we track a job only for the E-L parts and then mark it as Successful.
That means that a job is reported as finished before dbt starts running.
That means that a user can see a job as done on her pipelines page in Meltano UI, go to the Analyze page and no data will be there for a while. It also explains some similar weird behavior we were witnessing some times when testing with new installations (with the dbt never run, which means that there was no analytics schema).
We should track all three parts of the ELT pipeline, both with respect to updating the final state and the ended_at timestamp.

View 5 previous comments from the original issue on GitLab


Excel 2000 support

Support is being added for new Excel formats now.
I use Excel 2000 for my star charts "database" and would like to see the program export and import into that as well.

I updated the code to work with either .xls or xlsx format


Added metric reporting functions

Description of changes:
Adds metric report functions that are platform specific that can be used in the Device Defender custom metrics. Needed for the following PR: https://github.com/aws/aws-iot-device-sdk-cpp-v2/pull/401

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

I wouldn't make these "custom_metric" I'd just make them top-level functions, likely adding to either process.* or system_info.*

Will do 👍

Also, restricted to posix-only, does the implementation still need to check defines? Does it work on a mac?

Unfortunately, as sysinfo.h isn't available on Mac. There is a similar function that provides some of the information used, but since Device Defender doesn't support Mac I haven't added the support for it.

Thanks for the reviews! Merging into main...