Add an article assessment extractor

Something like this:
Extracts article assessments from a Wikipedia XML dump.

Usage:
    extract_assessments <dumpfile>... [--extractor=<classpath>]

Since assessments appear on an article's talk page in English Wikipedia, this script would not be able to determine what revision of an article a particular assessment was applied to.  It would write a TSV of rows containing:

article_title -- The title of the assessed article
talk_page_id -- The page_id of the talk page where the assessment appeared
assessment -- The assessment class (e.g. Stub, Start, C, B, GA, A, FA)
index -- The nth assessment the article has received
start -- The timestamp of when the assessment started
end -- The timestamp of when the assessment ended

We'd need a post-processing script to be able to extract the revision ID that an assessment belongs to.  Something like this:
Looks up the relevant article revision for the start of an assessment.

Usage:
    lookup_assessments [--assessments=<path>] [--api=<url>]'

This would ultimately return the <rev_id>  pairs that  revscoring extract_features needs.

For the latter part, there's some code in /data/project/suggestbot/projects/improved-qualpred/clean-training-set.py on Tool Labs that you could look at. To improve the classifier, we walk through the talk page history to find when a specific assessment changed, and then find the associated article revision ID. My code's quite messy, though.

This now exists.  See http://pythonhosted.org/wikiclass/utilities.html#module-wikiclass.utilities.extract_labelings


Added Daepyong Middle school

Middle school website: http://www.daepyong.ms.kr/wah/main/index.htm
Email form: (name goes<EMAIL_ADDRESS>From south korea
Thank you 😄

@choeminjun I am sorry, do you have any high school students who study in the school? Please notice that free educational license for JetBrains tools is for high and higher schools students, i.e. those who are over 13 of age.
Also, please give us an URL of a page or another proof (.pdf or a screenshot are OK) showing that the school recognizes the domain which you are submitting as an official email domain for the students.
Thank you!

@choeminjun You might miss my previous comment. Please reply.

@choeminjun I am sorry, this request remains unanswered for a while. I have to close it without merging. Please reopen and comment if you have an update regarding the abovementioned issue. Thank you for the understanding!

@philipto As I mentioned 2 years ago, the mail services are provided by our government, not school.
If you got some request from Korean students, please remember that the domain could be government's domain and approve it.
@DESECTORCON This PR should be approved. Please reopen it if you still need this domain.


[WIP] Adding TCN Layers to TFA Layers

[Not Ready for Merge]
This PR adds TCN layer as well as the Residual Block layer to TFA layers.
TODO(shunlin):
Clean up code.
Add more comments / documentations.
Write unit tests.
Make a Colab tutorial.
Associated Issues:
https://github.com/tensorflow/addons/issues/661
https://github.com/philipperemy/keras-tcn/issues/73
Source Implementations:
https://github.com/philipperemy/keras-tcn (In Pure Keras)
https://github.com/locuslab/TCN (In Pytorch)
Relevant Paper:
https://arxiv.org/pdf/1803.01271.pdf

closing this PR because I messed up fetching in changes from upstream master again, will open another PR haha.


Static linking and dynamic loading of Vulkan functions

I just used MoltenVK for the first time, porting a small application that uses SDL and Vulkan to iOS. It worked fine on macOS with the Vulkan SDK. However, on iOS, SDL reported "Failed to load Vulkan Portability library", which really confused me. The problem turned out to be as follows:
The application generally uses a Vulkan loader (volk) to dynamically load the Vulkan functions. No Vulkan function is called directly. Because of that, it seems that on iOS, where all of the Vulkan functions are linked statically, they were stripped from the executable because they were unused from the compiler's point of view. Thus, dlsym(), as used internally by volk and SDL, could not find the functions and returned null.
As a workaround, I edited the MVK_PUBLIC_SYMBOL define in MoltenVK's Common/MVKCommonEnvironment.h, adding __attribute__((used)):
/** Directive to identify public symbols. */
#define MVK_PUBLIC_SYMBOL        	__attribute__((visibility("default"))) __attribute__((used))

While this workaround is not ideal, as directly calling the Vulkan functions would be more efficient, it allowed the application to run without possibly larger changes (and for this specific application which is an internal tool, neither the binary size nor the performance matter strongly).
Since it took me some time to figure out what the exact problem was here, I would like to suggest to add a note about this somewhere in the Readme (unless I missed it and it is already there somewhere), warning that the use of dynamic Vulkan function lookup (as used by volk or SDL, for example) may not work with the static linking. There is a section "Hiding Vulkan API Symbols" in the main Readme, which actually contributed to my confusion because it seemed to imply that the symbols are always available by default, and are only unavailable if using the optional flag MVK_HIDE_VULKAN_SYMBOLS.
Since it seems to me like nearly every project that uses SDL and MoltenVK on iOS would run into this issue, I am also speculating whether this may not be the default behavior, and instead my (CMake-generated) XCode project might have gotten some non-standard option for aggressive stripping of unused functions enabled accidentally.

all of the Vulkan functions are linked statically, they were stripped from the executable because they were unused from the compiler's point of view

The symbols are visible in the static build of MoltenVK, as built by the MoltenVK build configuration. So, if I understand correctly, you mean that these static symbols are subsequently stripped during the app build, because the app itself never calls the static functions?
If that is the case, I'm surprised that the app build is not recognizing the link to the static functions established within the MoltenVK build in MVKInstance.mm:
https://github.com/KhronosGroup/MoltenVK/blob/7a320974d1b349c86149b0dbc9a2e796d8992ee0/MoltenVK/MoltenVK/GPUObjects/MVKInstance.mm#L397-L398

As a workaround, I edited the MVK_PUBLIC_SYMBOL define in MoltenVK's Common/MVKCommonEnvironment.h, adding __attribute__((used)):

In principal, I don't see a problem in formally marking the static functions as used, either in MVK_PUBLIC_SYMBOL or ADD_ENTRY_POINT_MAP, once we understand why the app build is not already seeing that the static links are being used in ADD_ENTRY_POINT_MAP.

[...] you mean that these static symbols are subsequently stripped during the app build, because the app itself never calls the static functions?

Yes, I believe that this is what happened. (And in principle that should be fine, except for the ability to conveniently use the same dynamic function loading code in the app as is used on other platforms.)

once we understand why the app build is not already seeing that the static links are being used in ADD_ENTRY_POINT_MAP.

Is there any chance that the function in which the ADD_ENTRY_POINT macros are used, MVKInstance::initProcAddrs(), is itself seen as unused?

Is there any chance that the function in which the ADD_ENTRY_POINT macros are used, MVKInstance::initProcAddrs(), is itself seen as unused?

MVKInstance::initProcAddrs() flows procedurally from vkCreateInstance(). If the app build is tearing things apart at that level, it would basically be removing the entire MoltenVK code base.
How does your app call vkCreateInstance()?

I don't think that there is any static link from my app to MoltenVK. The initialization flow should be as follows:
In SDL2/src/video/uikit/SDL_uikitvulkan.m, in code called by SDL_CreateWindow(), the pointer to vkGetInstanceProcAddr is retrieved with dlsym():
#define DEFAULT_HANDLE RTLD_DEFAULT

// [...]

PFN_vkGetInstanceProcAddr vkGetInstanceProcAddr = NULL;

// [...]

/* Handle the case where Vulkan Portability is linked statically. */
vkGetInstanceProcAddr =
(PFN_vkGetInstanceProcAddr)dlsym(DEFAULT_HANDLE,
                                 "vkGetInstanceProcAddr");

// [...]

_this->vulkan_config.vkGetInstanceProcAddr = (void *)vkGetInstanceProcAddr;

Then my app uses SDL_Vulkan_GetVkGetInstanceProcAddr() to get this pointer and passes it to volkInitializeCustom(). That function stores it in a global function pointer pvkGetInstanceProcAddr that is declared in volk.h, and uses it with a null instance parameter to query functions like vkCreateInstance():
static PFN_vkVoidFunction vkGetInstanceProcAddrStub(void* context, const char* name)
{
	return pvkGetInstanceProcAddr((VkInstance)context, name);
}

void volkInitializeCustom(PFN_vkGetInstanceProcAddr handler)
{
	pvkGetInstanceProcAddr = handler;

	volkGenLoadLoader(NULL, vkGetInstanceProcAddrStub);
}

static void volkGenLoadLoader(void* context, PFN_vkVoidFunction (*load)(void*, const char*))
{
	/* VOLK_GENERATE_LOAD_LOADER */
#if defined(VK_VERSION_1_0)
	pvkCreateInstance = (PFN_vkCreateInstance)load(context, "vkCreateInstance");
	pvkEnumerateInstanceExtensionProperties = (PFN_vkEnumerateInstanceExtensionProperties)load(context, "vkEnumerateInstanceExtensionProperties");
	pvkEnumerateInstanceLayerProperties = (PFN_vkEnumerateInstanceLayerProperties)load(context, "vkEnumerateInstanceLayerProperties");
#endif /* defined(VK_VERSION_1_0) */
#if defined(VK_VERSION_1_1)
	pvkEnumerateInstanceVersion = (PFN_vkEnumerateInstanceVersion)load(context, "vkEnumerateInstanceVersion");
#endif /* defined(VK_VERSION_1_1) */
	/* VOLK_GENERATE_LOAD_LOADER */
}

My app subsequently uses the function pointer retrieved by volk to call vkCreateInstance():
if (!VulkanCheckResult(pvkCreateInstance(&instance_info, nullptr, &instance_))) {
  // [...]
}

I did modify volk's function pointer names by adding the prefix 'p' (this is why the function is called as "pvkCreateInstance()" in the snippet above). This is because on the one hand, using the original function names caused issues on another platform (see https://github.com/zeux/volk/issues/1), and on the other hand, the hidden symbol visibility that was used to resolve this first issue in volk caused another issue (https://github.com/zeux/volk/issues/51); prefixing the function pointer names solved both issues.

Thanks for the further details. They are really helpful.
From your code description, I can see that even vkGetInstanceProcAddr() is not statically linked, and I understand now, the need for the used attribute.
But, I'm curious. As an experiment, rather than mark all functions with the used attribute, what happens if you remove it from your MVK_PUBLIC_SYMBOL definition, and add it only to vkGetInstanceProcAddr in vulkan.mm, as follows:
MVK_PUBLIC_VULKAN_SYMBOL __attribute__((used)) PFN_vkVoidFunction vkGetInstanceProcAddr(

or better yet even, only to vk_icdGetInstanceProcAddr (a special loader API function) in vulkan.mm
MVK_PUBLIC_SYMBOL __attribute__((used)) PFN_vkVoidFunction vk_icdGetInstanceProcAddr(

I'm wondering if after marking that as used, then all the other functions will flow from that, and be kept.

PR #1818 fixes this issue by implementing suggestion above.
@puzzlepaint I've implemented your suggested solution. But it would be informative if you could try your app with __attribute__((used)) limited to only one of the functions I mentioned above, to allow us to better understand the linker dependencies between the symbols. Thanks.

I tested your suggestions to only apply the used attribute to one of the two mentioned functions, and my app starts successfully in both cases. Since the app's use of Vulkan is rather basic, this testing probably only covers some of the most common functions, however.
The app also works with the up-to-date main branch, so I will close this issue. Thank you!


renderer: trim trailing newlines from code blocks

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Ranges to filter

does Someone have solution to make Filters with Ranges (>, <, >=, <=) ?

those already work in the filter :)

But I can't put filters on the columns on the grid on execution time (the user will set the Range in my application)

I'm not sure I'm understanding, can you give a few more details please?


[SUPPORT] Incremental read query performance

Describe the problem you faced
I'm running an application that reads from 4 medium-sized (few hundred GB) Hudi MoR tables which are compacted weekly.
When running incremental queries to look over 3~5 commits with hoodie.datasource.read.incr.fallback.fulltablescan.enable -> true, I am seeing a 5 hour gap in my Spark History Server:

Incremental read config:
Scan MergeOnReadIncrementalRelation(
org.apache.spark.sql.SQLContext@3b457d8a,Map(
    hoodie.datasource.read.incr.fallback.fulltablescan.enable -> true,
    path -> s3://lake/names.all_hudi,
    hoodie.write.lock.zookeeper.url -> ip-10-80-36-225.ec2.internal,
    hoodie.write.lock.zookeeper.base_path -> /hudi,
    hoodie.metadata.enable -> true,
    hoodie.datasource.hive_sync.jdbcurl -> jdbc:hive2://ip-10-xx-xx-xxx.ec2.internal:10000,
    hoodie.datasource.read.begin.instanttime -><PHONE_NUMBER>0214000,
    hoodie.datasource.query.type -> incremental,
    hoodie.cleaner.policy.failed.writes -> EAGER,
    hoodie.write.lock.zookeeper.port -> 2181,
    hoodie.write.lock.provider -> org.apache.hudi.client.transaction.lock.ZookeeperBasedLockProvider,
    hoodie.write.concurrency.mode -> single_writer),HoodieTableMetaClient{basePath='s3://lake/names.all_hudi',
    metaPath='s3://lake/names.all_hudi/.hoodie',
    tableType=MERGE_ON_READ},None,None
)
Job time: 2023/12/12 00:47:50
=> 5 commits for incremental read
number of output rows: 19,926,780

During the gap, my driver kills all 40 of my executor instances and I see the following logs on driver: log.txt
When I use snapshot query + filter on _hoodie_commit_time, the gap reduces to ~20mins:

Snapshot read config:
Scan MergeOnReadSnapshotRelation(org.apache.spark.sql.SQLContext@24a4d185,
Map(
    path -> s3://lake/names.all_hudi,
    hoodie.write.lock.zookeeper.url -> ip-xx-xx-xxx.ec2.internal,
    hoodie.write.lock.zookeeper.base_path -> /hudi,
    hoodie.metadata.enable -> true,
    hoodie.datasource.hive_sync.jdbcurl -> jdbc:hive2://ip-10-xx-xx-xxx.ec2.internal:10000,
    hoodie.datasource.query.type -> snapshot,
    hoodie.cleaner.policy.failed.writes -> EAGER,
    hoodie.write.lock.zookeeper.port -> 2181,
    hoodie.write.lock.provider -> org.apache.hudi.client.transaction.lock.ZookeeperBasedLockProvider,
    hoodie.write.concurrency.mode -> single_writer),
    HoodieTableMetaClient{basePath='s3://lake/names.all_hudi',
    metaPath='s3://lake/names.all_hudi/.hoodie',
    tableType=MERGE_ON_READ},
    List(),
    None,
    None
)

When I do incremental read with hoodie.datasource.read.incr.fallback.fulltablescan.enable -> false, I see the incremental query gap go from 5 hours -> 5 mins 😮 :

Incremental read config (no fulltable fallback):
Scan MergeOnReadIncrementalRelation(org.apache.spark.sql.SQLContext@dcb6efd,
Map(
    path -> s3://lake/names.all_hudi,
    hoodie.write.lock.zookeeper.url -> ip-10-xx-xx-xxx.ec2.internal,
    hoodie.write.lock.zookeeper.base_path -> /hudi,
    hoodie.metadata.enable -> true,
    hoodie.datasource.hive_sync.jdbcurl -> jdbc:hive2://ip-10-xx-xx-xxx.ec2.internal:10000,
    hoodie.datasource.read.begin.instanttime -><PHONE_NUMBER>2646000,
    hoodie.datasource.query.type -> incremental,
    hoodie.cleaner.policy.failed.writes -> EAGER,
    hoodie.write.lock.zookeeper.port -> 2181,
    hoodie.write.lock.provider -> org.apache.hudi.client.transaction.lock.ZookeeperBasedLockProvider,
    hoodie.write.concurrency.mode -> single_writer),
    HoodieTableMetaClient{basePath='s3://lake/names.all_hudi',
    metaPath='s3://lake/names.all_hudi/.hoodie',
    tableType=MERGE_ON_READ},
    None,
    None
)
number of output rows: 12,541,221

This leads me to believe the incremental query was degenerating into a full table scan when it shouldn't... (all my commits are active and uncleaned):
https://github.com/apache/hudi/blob/7a6543958368540d221ddc18e0c12b8d526b6859/hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/MergeOnReadIncrementalRelation.scala#L142-L151
Wondering if someone can help me understand the following:

Why is the incremental load degenerating into a full table scan when I can run the same job with the flag disabled and do not run into File Not Found?
Is the full table scan expected to happen on only one instance (the driver?)
Can I safely leave this flag false, and expect to only run into FileNotFound if running cleaner?

Expected behavior
Only fall back to full table scan in incremental load when necessary (file not found issue) and not all the time.
Environment Description

Hudi version : 0.13.1

Spark version : 3.4.0

Hive version : 3.1.3

Hadoop version : 3.3.3

Storage (HDFS/S3/GCS..) : S3

Running on Docker? (yes/no) : no

cc @linliu-code , maybe he could give some investigations of spark inc read.

Thanks @danny0405 for response. @linliu-code let me know if you would share some insight or need details. tks


Security Vulnerability

Pre-requisites

[X] I have double-checked my configuration
[X] I can confirm the issue exists when I tested with :latest
[X] I have searched existing issues and could not find a match for this bug
[X] I'd like to contribute the fix myself (see contributing guide)

What happened/what did you expect to happen?
I have reported the issue via email and HackerOne, in accordance with the security policy, but I have not received any response.
Version
latest
Paste a small workflow that reproduces the issue. We must be able to run the workflow; don't enter a workflows that uses private images.
I have reported the issue via email and HackerOne, in accordance with the security policy, but I have not received any response.

Logs from the workflow controller
kubectl logs -n argo deploy/workflow-controller | grep ${workflow}

Logs from in your workflow's wait container
kubectl logs -n argo -c wait -l workflows.argoproj.io/workflow=${workflow},workflow.argoproj.io/phase!=Succeeded

Hmm I don't have access to either of those (I'm actually not sure who does exactly), but I can check with some SIG Security folks. It's possible it just may not have been triaged yet (KubeCon is next week so some folks are OOO or otherwise busy).
Could you DM me on CNCF Slack with the dates of your email & HackerOne disclosure?

The disclosure has been responded to, so I think this is being handled now

misconfiguration with Secrets in plaintext
I ended up responding to the reporter (in great detail) and after checking with them as well as some SIG Security folks, I wanted to clarify here that this turned out to be a misconfiguration on their side. The misconfiguration has been fixed on their side.
Specifically, there were Secrets in plaintext manifests.
Their users used environment variables correctly, but defined them directly in the manifest -- instead they should use k8s Secrets and can refer to those Secrets by name (no secret contents) in the manifest by using valueFrom.secretKeyRef within their env variable definition.
I referred to the Secrets page in the Argo docs that goes over the proper way of handling Secrets in Argo, which inherits from k8s and links to some of the k8s docs I referred to as well. As such this is also out-of-scope for Argo as it is a more generic k8s Secrets usage misconfiguration that is not specific to Argo.
As some of these kinds of misconfigurations can be fairly common with folks who are less experienced with k8s, IaC, and other Infra/DevOps best practices, I wanted to address that here for more user education on the topic for any other users who run into that (after having confirmed that was ok to do and the misconfigurations were resolved).
UI-only users
For UI-only users of Argo who don't have direct kubectl cluster access, either a cluster-admin / operator could create Secrets for them, or they could be given RBAC to create Secrets in the k8s Dashboard, as two common, generic options.
Other Secrets tools
Other tools like the External Secrets Operator, Sealed Secrets, and more are useful for syncing external secret stores to k8s Secrets or encrypting Secrets in code, respectively.
Existing Argo issues with regards to Secrets
There are some other issues in Argo related to Secrets, such as #8685, #5506, and #11431.
All of those are fairly complicated for the reason that Argo should not access, nor have access to, nor pass Secrets itself and should only rely on k8s Secrets that Pods use directly (without Argo as an intermediary). Argo is not a Secrets Manager and therefore should not itself manage Secrets (otherwise you get into a rabbit hole of secure Secrets Management and such, which is out-of-scope for Argo). Some of those issues are for feature parity with other CI tools, many of which do handle Secrets Management, whereas Argo leaves that to k8s's built-in (and ecosystem) mechanisms as it is k8s native.


opening app store links has a weird modal

Second this. Also, it’d be great if the Yes/No buttons are renamed to Open/Cancel to make the dialog more user friendly.

Hi @superusercode thanks for this.  It's been fixed and will be in an upcoming next release.
@quanganhdo - we're doing a copy review of the entire app, so I'll raise your comment with that team as a point of interest.
Thanks!


I added this library but the is no HttpProxyCacheServer.

Any fix?

I u used  another library for saving the the videos in cache. And now those are working fine.

I u used another library for saving the the videos in cache. And now those are working fine.

哪个版本呢

same dude. I cant find it.


Support customizing shirts

I want to customize shirt colors and enable/disable the text and QR code.

[x] Can select shirt color
[x] Can choose custom shirt text
[ ] Can select if I want a QR code

Disabling the QR code is probably not worth implementing for now


Use new version of lullabot/amp

Latest release contains fix for discovering server url used for amp-img tags generation.

@takeit - can you looks why this test fails on php 7.2?


Authentication windows a lot of times

We have a problem with this extension, every single time that we open a report that includes this extension it "pop-op" a window that is asking for credentials. Can you help us to solve this problem. please?

No se puede reproducir en casa. ¿ Puedes decime lo que dice la consola Javascript del desarrollador ?

hello. thanks for your answer. I look for what I request and I found this error. I hope it helps

From what I can see in above screen, it could be related to background image "background.png" that is shown as a broken link...
Could you try to comment out lines 943 to 949 in graphics-deltaviz-delta.js; and refresh page ?
	/*tile.filter(function(d) { return d.item === null }).append('svg:image')
		.attr('x',cx-iw/2)
		.attr('y',cy-iw/2)
		.attr('width', iw)
		.attr('height', iw)
		.attr('xlink:href','/extensions/graphics-deltaviz-delta/background.png')
	;*/

Note; You should keep dev tools console open on application sheet; and refresh it with "Empty cache and hard reload" to see changes, see :
What's the difference between “Normal Reload”, “Hard Reload”, and “Empty Cache and Hard Reload” in Chrome?

Let's assume silence means ok.


How to avoid the need for copying to obtain a mutable client due to sharing immutable data in a multi-tasking program (or what is the best practice for using this library in a concurrent sharing scenario)?

How to avoid the need for copying to obtain a mutable client due to sharing immutable data in a multi-tasking program (or what is the best practice for using this library in a concurrent sharing scenario)?
In our program we shared a Arc with a client in it. And some api of client is mutable, so we always clone() the client when we need to call the apis which requires &mut self. Is there better solution?

The Client has already implemented Clone, so you are no need to wrap it by Arc.
Besides, you can get KvClient, WatchClient, etc. They are lightweight and can be concurrenly used in different threads.

Thanks.


timeline plugin: fix negative offset rendering

Short description of changes:
when using negative values as timeline.options.offset the timeline is now rendered from start to the very end.
before that change the timeline for those seconds of negative offset had not been rendered at the end of the waveform
Related Issues and other PRs:
fixes #2463

Coverage remained the same at 81.653% when pulling 8979c1dc276e801d62431916f587cae5b7eb2c17 on othmar52:2463-timeline-plugin-negative-offset-rendering-issue into 8d33268ede63e9e38fdde6e5f67e23294d5a35f3 on katspaugh:master.

youre welcome!
sorry for the typo - i will pay more attention next time i contribute to wavesurfer


Add 2024 add a accept year number

Bug/issue #, if applicable:
Summary
Fix #159's bin/test issue
History related PR #105
Dependencies
None
Testing
Update check-source's year number to verify the fix
Checklist
Make sure you check off the following items. If they cannot be completed, provide a reason.

[x] Added tests
[x] Ran the ./bin/test script and it succeeded
[x] Updated documentation if necessary

@swift-ci please test

@swift-ci please test


Feature: Quick install emulators [$100]

Add install chocolatey to the start functions: https://github.com/williamparry/cloudRIG/blob/dev/lib/index.js#L2607
In the UI, where there's the YouTube video playlist, instead have icons that allow the user to click to install an emulator. Use sendMessage to execute.

There is a $100 open bounty on this issue. Add to the bounty at Bountysource.

https://www.bountysource.com/issues/57460988-feature-quick-install-emulators

Ideally this would be done without chocolatey, but it's OK if it is.

@williamparry Ok, but unfortunately I can't understand what emulator do you want to install. Please explain a little :)

The flow would be, once the the instance is ready, it would swap out the YouTube embed with:
"Install an emulator"
It would have a button with the logo for each one (get as high resolution / svg as you can), and when you click it, it will install chocolatey, and the emulator they chose.

N64
choco install mupen64plus
SNES
choco install snes9x
NES
choco install nestopia
Wii U
choco install cemu
Wii and GameCube
choco install dolphin
SEGA
choco install kega-fusion
MAME
choco install mame

@williamparry Ok, thanks for the explanation. I'm starting to work on this.


Blueprint Reader: Unstructured Points case is not correctly handled

Blueprint allows two kinds of point meshes. One is implicit: you set up explicit coordinates and then define an implicit topology of points on top of it. The topology will use all the points in the coordinate set. The other kind of point mesh is an unstructured mesh where the shape type is points. The difference is illustrated by the braid example. You can choose to have an explicit coordset with an explicit topo of points or an explicit coordset with an implicit topo of points. The unstructured (explicit) points case allows us to specify which points from the coordinate set we want to use.
What I have done is created braid and then modified it to make it so that the topology only uses half of the points in the coordinate set:
    Node save_mesh, load_mesh, info;
    blueprint::mesh::examples::braid("points", 2, 2, 2, save_mesh);

    std::vector<int> new_conn;
    std::vector<float> new_field1;
    std::vector<float> new_field2;

    int_accessor conn = save_mesh["topologies"]["mesh"]["elements"]["connectivity"].value();

    float_accessor field1 = save_mesh["fields"]["braid"]["values"].value();
    float_accessor field2 = save_mesh["fields"]["radial"]["values"].value();
    for (int i = 1; i < conn.number_of_elements(); i += 2)
    {
        new_conn.push_back(conn[i]);
        new_field1.push_back(field1[i]);
        new_field2.push_back(field2[i]);
    }
    save_mesh["topologies"]["mesh"]["elements"]["connectivity"].reset();
    save_mesh["topologies"]["mesh"]["elements"]["connectivity"].set(new_conn);

    save_mesh["fields"].remove_child("vel");
    save_mesh["fields"]["braid"]["values"].reset();
    save_mesh["fields"]["braid"]["values"].set(new_field1);
    save_mesh["fields"]["radial"]["values"].reset();
    save_mesh["fields"]["radial"]["values"].set(new_field2);

I have also removed half the field values so that the fields will have the right number of elements; since our topology is half as large.
This is the resulting blueprint mesh:
state:
  time: 3.1415
  cycle: 100
coordsets:
  coords:
    type: "explicit"
    values:
      x: [-10.0, 10.0, -10.0, ..., -10.0, 10.0]
      y: [-10.0, -10.0, 10.0, ..., 10.0, 10.0]
      z: [-10.0, -10.0, -10.0, ..., 10.0, 10.0]
topologies:
  mesh:
    type: "unstructured"
    coordset: "coords"
    elements:
      shape: "point"
      connectivity: [1, 3, 5, 7]
fields:
  braid:
    association: "vertex"
    topology: "mesh"
    values: [0.852493226528168, 0.852490484714508, -1.14750683307648, -1.14750957489014]
  radial:
    association: "element"
    topology: "mesh"
    values: [141.421356201172, 100.0, 100.0, 0.0]

You can see that we have 8 coordinates but only 4 points are used by the topology. The fields each have only 4 values.
If I save this and open it in VisIt, this is what I would expect to see (I created this with an equivalent silo mesh):

Notice that there are only 4 values; the bounding box correctly only contains the 4 values that are all in the same x plane, as all x values for these points are equal to 10. The field values are correct as well.
This is what I actually get:

The bounding box is wrong even though there are only 4 points being shown. VisIt pads my fields with zeroes.
If we do a label plot we can see what happened with the field values:

They are completely wrong.
We can see why this may have happened by exporting the dataset as Blueprint and printing the result:
domain_000000:
  state:
    domain_id: 0
    cycle: 100
    time: 3.1415
  coordsets:
    coords:
      type: "explicit"
      values:
        x: [-10.0, 10.0, -10.0, 10.0, -10.0, 10.0, -10.0, 10.0]
        y: [-10.0, -10.0, 10.0, 10.0, -10.0, -10.0, 10.0, 10.0]
        z: [-10.0, -10.0, -10.0, -10.0, 10.0, 10.0, 10.0, 10.0]
  topologies:
    topo:
      coordset: "coords"
      type: "unstructured"
      elements:
        shape: "point"
        connectivity: [1, 3, 5, 7]
  fields:
    mesh_mesh_braid:
      association: "vertex"
      topology: "topo"
      values: [0.852493226528168, 0.852490484714508, -1.14750683307648, -1.14750957489014, 0.0, 0.0, 0.0, 0.0]

So this is what VisIt created. Notice that it correctly has all of the coordinates, the topology is correct, but the braid field has been padded out with zeroes. My guess is that the Blueprint plugin is using the topology connectivity values to index into the fields, giving us the values 0.852490484714508, -1.14750683307648, 0.0, and 0.0 in the render above.
There are two things that are wrong here:

Just doing a mesh plot yields the large bounding box that we see in the Blueprint renders. This should probably not happen, as I would expect the bounding box to look like how it does in the equivalent silo data.
The plotted field values are totally wrong.

unstructured_points.zip
Here are the files I used to create the renders.

@JustinPrivitera I suspect the problem is actually in the Blueprint plugin itself.
In Silo, we do similar things where for an unstructured mesh, we have a set of coordinates and list of elements. Each element in the element list refers to its nodes by using the coordinates as a zero-indexed address space and then identifying them by their position in that address space (e.g. an index). But, the list of coordinates can contain many nodes that are actually NOT referenced by any element in the mesh.
We wind up instantiating a vtkUnstructuredGrid object which also contains those unused points. I think downstream of the plugin, there are some VTK filters that get applied that remove the unused points from the vtkPoints part of the vtkUnstructuredGrid object...honestly, I can't recall if that is true or not. I just suspect it is.
Well, wait a minute...the only cases where I have actually seen this kind of thing in Silo is where we have higher than zero-dimensional (point) elements comprising the mesh (e.g. edges, surfaces, volumes). If the mesh has only zero-dimensional elements (e.g. points), in Silo we have a wholly separate Pointmesh object which contains only a list of points and not an additional list of elements which identifies those points from the list of points actually comprising the mesh. So, in a Silo point mesh, there is no point in the coordinates that is also NOT an element in the mesh.
I think your case is a bit different from Silo then. But, I think the mapping to vtkUnstructuredGrid should still work. What should happen in the plugin is that the vtkPoints gets all the coordinates but  the vtkCells should be created (all of which are VTK_VERTEX elements) which identies which of the members of vtkPoints actually comprise elements in the mesh.
Have you dug into that aspect of things in the Blueprint plugin for this case?
Also, love the detailed analysis of the data model here 👍🏻

I am curious...I never saw the word cartesian-product used in the initial description of these cases but I think that is kinda sorta key to the implicit points. They are created by taking the cartesian product of each of the coordinate sets. This is a rectilinear grid object in VTK.
Finally, there is an explicit case that is nonetheless still implicit in its topology and that is a warped/deformed coordinates. Does Blueprint support that? That is Silo's NON-COLLINEAR coordinate Quadmesh case.

@markcmiller86
I should clarify a few things.

I suspect the problem is actually in the Blueprint plugin itself.

I think that this in indeed the case. The blueprint plugin should make the right choices for what to hand to VTK for the unstructured points case.

I think your case is a bit different from Silo then.

I am aware of the way silo handles unstructured meshes versus point meshes. The "equivalent" silo data up above is not strictly equivalent; I have used my blueprint to silo converter to create it. My converter has special logic for converting the blueprint unstructured points case to a silo point mesh, since silo does not support unstructured meshes with point elements. I throw out all the points that are unused.
So, yes; the silo data is not analogous. However, it describes the same set of points and field data on those points, albeit in a different way.

Have you dug into that aspect of things in the Blueprint plugin for this case?

I did a bit of digging in the plugin; I don't believe this case is handled properly for either the mesh to vtk and field to vtk submethods. That logic lives inside the conduit blueprint data adaptor library in the avt directory.

I think for Blueprint we have the two kinds of point meshes, explicit and implicit. Implicit will be similar to your typical silo point mesh, while explicit is the unstructured mesh with point elements case. Neither use a cartesian-product. This is because the underlying coordinate sets are of the explicit variety - i.e. not uniform, not rectilinear.
The silo NON_COLLINEAR case is supported in Blueprint as a structured topology, so implicit topo on top of explicit coords, as you said.

Thanks for looking into this.
As Mark said: Ideally it would not matter if we have "too many points" as long as the topology only includes the points needed.  Then down stream filters clean those extra point and update the indexing.
Looking at the data adaptor, we do create the VTK points w/o looking at the topology info.
In any case, the field data should be sized relative to the topology.
Maybe point associated is a poorly implemented case.
I think we need to get at where things diverge from expectations as we create the vtk datasets.

I am aware of the way silo handles unstructured meshes versus point meshes. The "equivalent" silo data up above is not strictly equivalent; I have used my blueprint to silo converter to create it. My converter has special logic for converting the blueprint unstructured points case to a silo point mesh, since silo does not support unstructured meshes with point elements. I throw out all the points that are unused.

I know this is all a bit off topic but its data modeling and something close to my heart...
Honestly, looking at Silo docs, I think Silo is a tad ambiguous on this point. If a regular Silo user who ordinarily uses DBPutUcdmesh()/DBPutZonelist() wanted to output a point mesh and they never happened to run into DBPutPointmesh(), I think their natural inclination would be to do DBPutUcdmesh()/DBPutZonelist() and where the zonelist would be zones all of size 1 and a zonetype of...wait a minute...Silo doesn't define a topological entity for points (e.g. no DB_ZONETYPE_POINT)...but if it did, you get where I am going then. Alternatively, the zonelist in that case could be implicit (it is rather redundant after all). Honestly, I am not at all sure why DBPutPointmesh() was ever introduced to Silo. Its not even needed.
On the topic of implicit topology, my apologies for confusing that with implicit coordinates (which would involve a cartesian product of coordinate 1-tuples on each cartesian axis). This makes me curious about Blueprint data model though...does it assume that in 1D you have lines, in 2D you have quads and in 3D you have hexes?
Reason I ask is that implicit cases always interest me. In the 2D case, I could easily imagine implict quads or implicit triangles where each group of 4 neighboring points is sewen together by bi-secting the quad with a diagonal from north-west to south-east corners...or with diagonal  the opposite way. An even more intriguing case is where the diagonal (a binary choice in this case), actually varies explicitly over the whole mesh. That is a case I used in in dissertation work. There is a similar extension to 3D but with a larger variety of implicit variations using tets to fill (tile) the volume of a hex. Finally, I've always been interested in ways to handle 2D hexagonal sampling...in that case the implicity topological shape is a hexagon.
Just curious but do you know if Blueprint supports implicit coordinate cases for a point mesh...other than maybe uniform, axially aligned?

Implicit typologies , support are limited to points, quads (2d) or hexs (3d)

In recently handling Silo's quadmesh object defining a surface in 3 space (look for curvilinear surfaces in 3D towards end of tests) and looking at revolved volume query for curves, I had thoughts about lower dimensional topologies embedded in higher dimensional geometries...so 2D surfaces in 3D or 1D paths in 2D or 3D. Can you have a bunch of points that define implicit lines of a path too in 2D or 3D? Can you have a bunch of points that define implicit quads of a surface in 3D?

For blueprint:

implicit lines would only be used for a 1D structured case
no implicit quads for a 3D surface


Fix Documenter CI with new NDTensors subdir package

Codecov Report

Merging #782 (4038013) into main (997923e) will decrease coverage by 76.35%.
The diff coverage is n/a.

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@@            Coverage Diff             @@
##             main    #782       +/-   ##
==========================================
- Coverage   76.35%   0.00%   -76.36%
==========================================
  Files          65      64        -1
  Lines        7400    6342     -1058
==========================================
- Hits         5650       0     -5650
- Misses       1750    6342     +4592

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src/not.jl
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Compressing and uncompressing name_split

When using Aliasor() to uncompress/compress aliased/unaliased lineages, there are instances when an unexpected lineage is returned. When running the following:
from pango_aliasor.aliasor import Aliasor

aliasor = Aliasor()
print(aliasor.uncompress("CC"))
print(aliasor.compress("B.1.1.5<IP_ADDRESS>.1.1.2"))

I expected to see:
B.1.1.5<IP_ADDRESS>.1.1.2
CC

But the code above as it's written outputs the following:
CC
BE.1.1.2

Is this the expected behavior and I am misunderstanding the code?
I feel this is the result of the name_split in the compress and uncompress functions. When I added "." at the end of each of my arguments, the code outputted my expected behavior:
from pango_aliasor.aliasor import Aliasor

aliasor = Aliasor()
print(aliasor.uncompress("CC."))
print(aliasor.compress("B.1.1.5<IP_ADDRESS>.1.1.2."))

Output:
B.1.1.5<IP_ADDRESS>.1.1.2.
CC.

Note that these are the aliased/unaliased lineages with "." appended to the ends.

PANGO
Partial PANGO
Unaliased PANGO

BE.1.1.2
BA.<IP_ADDRESS>.1.2
B.1.1.5<IP_ADDRESS>.1.1.2

CC.1
BA.<IP_ADDRESS>.1.2.1
B.1.1.5<IP_ADDRESS>.<IP_ADDRESS>

The value "B.1.1.5<IP_ADDRESS>.1.1.2" will always return BE.1.1.2..There aren't enough subdivisions to re-alias it to CC; there needs to be 4 dots to re-alias.
That is why your additional-dot workaround "works". The additional-dot workaround is split into 5 divisions BE, 1, 1, 2, <empty string>, and that qualifies it to re-alias to CC. (CC, <empty string> divisions).
Inverse Property
The only valid PANGO lineages that don't have dots are...

One of the two original haplotypes (A or B)
Any original recombinant haplotypes (XA, XBB, etc...)

So technically CC isn't a valid PANGO lineage, and as such you can't believe that an invalid PANGO lineage will follow an "Inverse Property". However, all valid PANGO lineages should follow the "Inverse Property"
Valid PANGO Lineage
🟩 CC.1 will uncompress to B.1.1.5<IP_ADDRESS>.<IP_ADDRESS>. By the Inverse Property, B.1.1.5<IP_ADDRESS>.<IP_ADDRESS> will compress to CC.1.
Invalid PANGO Lineage
🟥 However, because CC is an invalid PANGO lineage, it will uncompress to B.1.1.5<IP_ADDRESS>.1.1.2. When compressing B.1.1.5<IP_ADDRESS>.1.1.2, you will get BE.1.1.2 (a valid PANGO lineage)

Thank you @ciscorucinski - I think I understand this and your comment helps enough for me to close this out.


MM-29046 Add unit and e2e tests for autocomplete popover

Summary
This PR adds E2E tests to the autocomplete PR that's already been merged.
Ticket Link
https://mattermost.atlassian.net/browse/MM-29046
Device Information
This PR was tested on:

iPhone 11 (Simulator)
Pixel 3a XL (Simulator)

Notes:

Reviews on test labeling and folder structure would be highly appreciated! (I'm not positive I've organized it well enough)
I still want to add tests for whether tapping an autocomplete item actually produces the intended effect, but I'm not sure whether they should be added on every single screen, or if testing it once (in the post draft) is enough
The E2E docs mention that each test should have a corresponding test case in Test Management for Jira, I'm not so familiar with that so I initially have not added any particular identifiers yet. How should I go about sorting this out properly?

Thanks for the quick response and reviews!
I'm still relatively new to contributing to testing so I'm already learning a bunch :)
I'll be on the lookout for the TM4J test cases then!

@josephbaylon Thank you for the guidance!
Just added the TM4J ticket numbers to each test case

Thank you for the additional feedback!
Just updated all the testIDs

My 2 cents.. there should be no difference with prop='string' and prop={'string'} but I'm 0/5


qasm3 exporter wrong placement of input declaration

Environment

Qiskit Terra version: 0.20.0
Python version: 3.8.13
Operating system: macOS Monterey 12.3.1

What is happening?
When exporting parametrized QuantumCircuits with custom gates to a QASM3 string, the exporter wrongly places the circuit's input declaration after the gate declarations, which is not according to the OpenQASM3.0 grammar - IO declarations should appear in the header.
How can we reproduce the issue?
Run the following:
from qiskit import QuantumCircuit, qasm3
from qiskit.circuit import Parameter

theta = Parameter("theta")
inner_qc = QuantumCircuit(1)
inner_qc.rz(theta, 0)
qc = QuantumCircuit(1)
qc.append(inner_qc.to_gate(), range(1))
print(qasm3.dumps(qc))

The resulting OpenQASM3.0 code is then:
OPENQASM 3;
include "stdgates.inc";
gate circuit_21(theta) _gate_q_0 {
  rz(theta) _gate_q_0;
}
input float[64] theta;
qubit[1] _all_qubits;
let q = _all_qubits[0:0];
circuit_21(theta) q[0];

What should happen?
The expected output according to the grammar is:
OPENQASM 3;
include "stdgates.inc";
input float[64] theta;
gate circuit_21(theta) _gate_q_0 {
  rz(theta) _gate_q_0;
}
qubit[1] _all_qubits;
let q = _all_qubits[0:0];
circuit_21(theta) q[0];

Any suggestions?
No response

Thanks for the report!  I'll fix this in the Terra exporter, though we've just missed the window to get it into Terra 0.20.1 that should release later today.  I'll target it for 0.20.2 in 2-3 weeks' time.
It's a bit questionable why the current reference grammar forbids this ordering of input and gate statements (I'm not sure any actual implementations have the same restriction), but it's a bug that Terra doesn't use the order that currently works in the reference grammar.

Thanks for the quick reply and fix!
Indeed I don't know why the current grammar cares about the ordering.
In any case, the openqasm3 parser also conforms to the current grammar, namely it expects the IO declarations to come before the gate declarations.


feat(tokens): Use new token metadata source/schema

Description
For ACT-909. Updates the wallet to fetch the new format of token metadata from the new REST endpoint on blockchain-api and user balances for all available chains (if multi-chain balances are enabled via statsig). As soon as the new blockchain-api REST endpoint is updated to return non-Celo token metadata, multi-chain balances should work out-of-the-box in-app. In short, there are two functional changes in this PR:

Token balances are fetched for all supported chains, provided an override has been set in Statsig for the fetch_multi_chain_balances feature gate.
We no longer fetch token metadata directly from Firebase, but instead the new blockchain-api endpoint.

Internal (Redux) state has been updated to reflect the schema changes in the token metadata.

The second bullet above required some rejiggering of types throughout the repo, and a lot of mechanical changes to tests throughout the app. Existing places in code that depend on a token's address being available have been updated to use the "new" (but identical to the "old") WithAddress suffixed types. New code which supports multi-chain features should begin using the types that make address optional. Currently, there are no places in code that take advantage of this new format; we'll need to add a selector that returns the "new format" data from Redux, typed correctly.
Note that this change requires a migration; I have specifically opted not to muck about with trying to migrate stored token information in Redux (re: the trouble caused by attempting to do so with transfers), and instead opted to wipe the stored token info. This means that users will need to refresh their balances upon updating.
Test plan
Unit and manual tested.
Related issues

Fixes ACT-909.

Backwards compatibility
Yes.

please don't merge this until the blockchain api endpoint includes prices. I don't want to create a race condition between the completion of Jacob's blockchain-api pricing issue and this PR


the japkowicz book has nice formal defintions for noise of an example, bias and variance of an algorith

wwe should probably use those.
they are in chap2 of the book

added to wishlist


Wheel error when installing stardist on conda (mac)

Hello,
I am getting this error when i try installing stardist on conda mac
Collecting stardist
  Using cached stardist-0.6.0.tar.gz (407 kB)
  Installing build dependencies ... done
  Getting requirements to build wheel ... done
    Preparing wheel metadata ... done
Collecting csbdeep>=0.6.0
  Using cached csbdeep-0.6.0-py2.py3-none-any.whl (67 kB)
Requirement already satisfied: numba in /opt/anaconda3/lib/python3.7/site-packages (from stardist) (0.48.0)
Requirement already satisfied: scikit-image in /opt/anaconda3/lib/python3.7/site-packages (from stardist) (0.16.2)
Requirement already satisfied: six in ./.local/lib/python3.7/site-packages (from csbdeep>=0.6.0->stardist) (1.15.0)
Requirement already satisfied: tifffile in /opt/anaconda3/lib/python3.7/site-packages (from csbdeep>=0.6.0->stardist) (2020.7.4)
Requirement already satisfied: numpy in ./.local/lib/python3.7/site-packages (from csbdeep>=0.6.0->stardist) (1.18.5)
Requirement already satisfied: matplotlib in /opt/anaconda3/lib/python3.7/site-packages (from csbdeep>=0.6.0->stardist) (3.1.3)
Requirement already satisfied: scipy in /opt/anaconda3/lib/python3.7/site-packages (from csbdeep>=0.6.0->stardist) (1.4.1)
Requirement already satisfied: h5py in /opt/anaconda3/lib/python3.7/site-packages (from csbdeep>=0.6.0->stardist) (2.10.0)
Requirement already satisfied: tqdm in /opt/anaconda3/lib/python3.7/site-packages (from csbdeep>=0.6.0->stardist) (4.42.1)
Collecting keras<2.4,>=2.1.2
  Using cached Keras-2.3.1-py2.py3-none-any.whl (377 kB)
Requirement already satisfied: llvmlite<0.32.0,>=0.31.0dev0 in /opt/anaconda3/lib/python3.7/site-packages (from numba->stardist) (0.31.0)
Requirement already satisfied: setuptools in ./.local/lib/python3.7/site-packages (from numba->stardist) (49.2.0)
Requirement already satisfied: PyWavelets>=0.4.0 in /opt/anaconda3/lib/python3.7/site-packages (from scikit-image->stardist) (1.1.1)
Requirement already satisfied: networkx>=2.0 in /opt/anaconda3/lib/python3.7/site-packages (from scikit-image->stardist) (2.4)
Requirement already satisfied: imageio>=2.3.0 in /opt/anaconda3/lib/python3.7/site-packages (from scikit-image->stardist) (2.6.1)
Requirement already satisfied: pillow>=4.3.0 in /opt/anaconda3/lib/python3.7/site-packages (from scikit-image->stardist) (7.0.0)
Requirement already satisfied: cycler>=0.10 in /opt/anaconda3/lib/python3.7/site-packages (from matplotlib->csbdeep>=0.6.0->stardist) (0.10.0)
Requirement already satisfied: python-dateutil>=2.1 in /opt/anaconda3/lib/python3.7/site-packages (from matplotlib->csbdeep>=0.6.0->stardist) (2.8.1)
Requirement already satisfied: kiwisolver>=1.0.1 in /opt/anaconda3/lib/python3.7/site-packages (from matplotlib->csbdeep>=0.6.0->stardist) (1.1.0)
Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /opt/anaconda3/lib/python3.7/site-packages (from matplotlib->csbdeep>=0.6.0->stardist) (2.4.6)
Requirement already satisfied: pyyaml in /opt/anaconda3/lib/python3.7/site-packages (from keras<2.4,>=2.1.2->csbdeep>=0.6.0->stardist) (5.3)
Requirement already satisfied: keras-applications>=1.0.6 in /opt/anaconda3/lib/python3.7/site-packages (from keras<2.4,>=2.1.2->csbdeep>=0.6.0->stardist) (1.0.8)
Requirement already satisfied: keras-preprocessing>=1.0.5 in /opt/anaconda3/lib/python3.7/site-packages (from keras<2.4,>=2.1.2->csbdeep>=0.6.0->stardist) (1.1.2)
Requirement already satisfied: decorator>=4.3.0 in /opt/anaconda3/lib/python3.7/site-packages (from networkx>=2.0->scikit-image->stardist) (4.4.1)
Building wheels for collected packages: stardist
  Building wheel for stardist (PEP 517) ... error
  ERROR: Command errored out with exit status 1:
   command: /opt/anaconda3/bin/python /opt/anaconda3/lib/python3.7/site-packages/pip/_vendor/pep517/_in_process.py build_wheel /var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/tmpzrehihnz
       cwd: /private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-install-klxuv83h/stardist
  Complete output (176 lines):
  running bdist_wheel
  running build
  running build_py
  creating build
  creating build/lib.macosx-10.9-x86_64-3.7
  creating build/lib.macosx-10.9-x86_64-3.7/stardist
  copying stardist/version.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
  copying stardist/rays3d.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
  copying stardist/sample_patches.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
  copying stardist/nms.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
  copying stardist/__init__.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
  copying stardist/matching.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
  copying stardist/utils.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
  copying stardist/big.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
  creating build/lib.macosx-10.9-x86_64-3.7/stardist/plot
  copying stardist/plot/plot.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/plot
  copying stardist/plot/render.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/plot
  copying stardist/plot/__init__.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/plot
  creating build/lib.macosx-10.9-x86_64-3.7/stardist/models
  copying stardist/models/model3d.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/models
  copying stardist/models/model2d.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/models
  copying stardist/models/__init__.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/models
  copying stardist/models/base.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/models
  creating build/lib.macosx-10.9-x86_64-3.7/stardist/geometry
  copying stardist/geometry/__init__.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/geometry
  copying stardist/geometry/geom3d.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/geometry
  copying stardist/geometry/geom2d.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/geometry
  creating build/lib.macosx-10.9-x86_64-3.7/stardist/kernels
  copying stardist/kernels/stardist2d.cl -> build/lib.macosx-10.9-x86_64-3.7/stardist/kernels
  copying stardist/kernels/stardist3d.cl -> build/lib.macosx-10.9-x86_64-3.7/stardist/kernels
  running build_ext
  building 'stardist.lib.stardist2d' extension
  Warning: Can't read registry to find the necessary compiler setting
  Make sure that Python modules winreg, win32api or win32con are installed.
  C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/opt/anaconda3/include -arch x86_64 -I/opt/anaconda3/include -arch x86_64

  creating build/temp.macosx-10.9-x86_64-3.7
  creating build/temp.macosx-10.9-x86_64-3.7/stardist
  creating build/temp.macosx-10.9-x86_64-3.7/stardist/lib
  compile options: '-I/private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-l3x94rr5/overlay/lib/python3.7/site-packages/numpy/core/include -I/opt/anaconda3/include/python3.7m -c'
  extra options: '-std=c++11 -fopenmp'
  gcc: stardist/lib/stardist2d.cpp
  gcc: stardist/lib/utils.cpp
  gcc: stardist/lib/clipper.cpp
  clang: error: unsupported option '-fopenmp'
  clang: error: unsupported option '-fopenmp'
  clang: error: unsupported option '-fopenmp'
  compiling with OpenMP support failed, re-trying without
  building 'stardist.lib.stardist2d' extension
  C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/opt/anaconda3/include -arch x86_64 -I/opt/anaconda3/include -arch x86_64

  compile options: '-I/private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-l3x94rr5/overlay/lib/python3.7/site-packages/numpy/core/include -I/opt/anaconda3/include/python3.7m -c'
  extra options: '-std=c++11'
  gcc: stardist/lib/stardist2d.cpp
  gcc: stardist/lib/clipper.cpp
  gcc: stardist/lib/utils.cpp
  stardist/lib/utils.cpp:4:98: warning: field 'label' will be initialized after field 'eps' [-Wreorder]
  ProgressBar::ProgressBar(const std::string label,const int width, const float eps): width(width),label(label),eps(eps), curr_percentage(0){};
                                                                                ^
  stardist/lib/utils.cpp:4:111: warning: field 'eps' will be initialized after field 'curr_percentage' [-Wreorder]
  ProgressBar::ProgressBar(const std::string label,const int width, const float eps): width(width),label(label),eps(eps), curr_percentage(0){};
                                                                                ^
  2 warnings generated.
  In file included from stardist/lib/stardist2d.cpp:8:
  In file included from /private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-l3x94rr5/overlay/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4:
  In file included from /private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-l3x94rr5/overlay/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12:
  In file included from /private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-l3x94rr5/overlay/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1822:
  /private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-l3x94rr5/overlay/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: "Using deprecated NumPy API, disable it with "          "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-W#warnings]
  #warning "Using deprecated NumPy API, disable it with " \
   ^
  1 warning generated.
  creating build/lib.macosx-10.9-x86_64-3.7/stardist/lib
  g++ -bundle -undefined dynamic_lookup -L/opt/anaconda3/lib -arch x86_64 -L/opt/anaconda3/lib -arch x86_64 -arch x86_64 build/temp.macosx-10.9-x86_64-3.7/stardist/lib/stardist2d.o build/temp.macosx-10.9-x86_64-3.7/stardist/lib/clipper.o build/temp.macosx-10.9-x86_64-3.7/stardist/lib/utils.o -o build/lib.macosx-10.9-x86_64-3.7/stardist/lib/stardist2d.cpython-37m-darwin.so
  building 'stardist.lib.stardist3d' extension
  C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/opt/anaconda3/include -arch x86_64 -I/opt/anaconda3/include -arch x86_64

  creating build/temp.macosx-10.9-x86_64-3.7/stardist/lib/qhull_src
  creating build/temp.macosx-10.9-x86_64-3.7/stardist/lib/qhull_src/src
  creating build/temp.macosx-10.9-x86_64-3.7/stardist/lib/qhull_src/src/libqhullcpp
  creating build/temp.macosx-10.9-x86_64-3.7/stardist/lib/qhull_src/src/libqhull_r
  compile options: '-I/private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-l3x94rr5/overlay/lib/python3.7/site-packages/numpy/core/include -Istardist/lib/qhull_src/src -I/opt/anaconda3/include/python3.7m -c'
  extra options: '-std=c++11 -fopenmp'
  gcc: stardist/lib/qhull_src/src/libqhullcpp/usermem_r-cpp.cpp
  gcc: stardist/lib/stardist3d.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/RboxPoints.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullStat.cpp
  clang: error: unsupported option '-fopenmp'
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullQh.cpp
  clang: error: unsupported option '-fopenmp'
  clang: error: unsupported option '-fopenmp'
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullPoint.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullFacetList.cpp
  clang: error: unsupported option '-fopenmp'
  clang: error: unsupported option '-fopenmp'
  clang: error: unsupported option '-fopenmp'
  gcc: stardist/lib/qhull_src/src/libqhullcpp/PointCoordinates.cpp
  gcc: stardist/lib/qhull_src/src/libqhull_r/stat_r.c
  clang: error: unsupported option '-fopenmp'
  gcc: stardist/lib/qhull_src/src/libqhull_r/qset_r.c
  gcc: stardist/lib/qhull_src/src/libqhull_r/merge_r.c
  clang: error: unsupported option '-fopenmp'
  clang: error: unsupported option '-fopenmp'
  clang: error: unsupported option '-fopenmp'
  gcc: stardist/lib/qhull_src/src/libqhull_r/io_r.c
  gcc: stardist/lib/qhull_src/src/libqhull_r/geom2_r.c
  clang: error: unsupported option '-fopenmp'
  clang: error: unsupported option '-fopenmp'
  clang: error: unsupported option '-fopenmp'
  compiling with OpenMP support failed, re-trying without
  building 'stardist.lib.stardist3d' extension
  C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/opt/anaconda3/include -arch x86_64 -I/opt/anaconda3/include -arch x86_64

  compile options: '-I/private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-l3x94rr5/overlay/lib/python3.7/site-packages/numpy/core/include -Istardist/lib/qhull_src/src -I/opt/anaconda3/include/python3.7m -c'
  extra options: '-std=c++11'
  gcc: stardist/lib/qhull_src/src/libqhullcpp/RboxPoints.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/usermem_r-cpp.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullStat.cpp
  gcc: stardist/lib/stardist3d.cpp
  stardist/lib/qhull_src/src/libqhullcpp/usermem_r-cpp.cpp:42:13: warning: explicitly assigning value of variable of type 'int' to itself [-Wself-assign]
      exitcode= exitcode;
      ~~~~~~~~^ ~~~~~~~~
  1 warning generated.
  gcc: stardist/lib/qhull_src/src/libqhullcpp/RoadLogEvent.cpp
  In file included from stardist/lib/stardist3d.cpp:2:
  In file included from /private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-l3x94rr5/overlay/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4:
  In file included from /private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-l3x94rr5/overlay/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12:
  In file included from /private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-l3x94rr5/overlay/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1822:
  /private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-l3x94rr5/overlay/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: "Using deprecated NumPy API, disable it with "          "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-W#warnings]
  #warning "Using deprecated NumPy API, disable it with " \
   ^
  1 warning generated.
  gcc: stardist/lib/stardist3d_impl.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullSet.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullVertexSet.cpp
  stardist/lib/stardist3d_impl.cpp:917:33: warning: unused variable 'diff' [-Wunused-variable]
    std::chrono::duration<double> diff = stop-start;
                                  ^
  stardist/lib/stardist3d_impl.cpp:1063:9: warning: unused variable 'status_percentage_new' [-Wunused-variable]
      int status_percentage_new = 100*count_total/n_polys;
          ^
  gcc: stardist/lib/qhull_src/src/libqhullcpp/RoadError.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullRidge.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullQh.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullVertex.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullPoint.cpp
  2 warnings generated.
  gcc: stardist/lib/utils.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullPoints.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullFacetList.cpp
  stardist/lib/utils.cpp:4:98: warning: field 'label' will be initialized after field 'eps' [-Wreorder]
  ProgressBar::ProgressBar(const std::string label,const int width, const float eps): width(width),label(label),eps(eps), curr_percentage(0){};
                                                                                ^
  stardist/lib/utils.cpp:4:111: warning: field 'eps' will be initialized after field 'curr_percentage' [-Wreorder]
  ProgressBar::ProgressBar(const std::string label,const int width, const float eps): width(width),label(label),eps(eps), curr_percentage(0){};
                                                                                ^
  2 warnings generated.
  gcc: stardist/lib/qhull_src/src/libqhullcpp/PointCoordinates.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullHyperplane.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullPointSet.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullFacet.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/QhullFacetSet.cpp
  gcc: stardist/lib/qhull_src/src/libqhullcpp/Coordinates.cpp
  gcc: stardist/lib/qhull_src/src/libqhull_r/stat_r.c
  error: invalid argument '-std=c++11' not allowed with 'C'
  gcc: stardist/lib/qhull_src/src/libqhull_r/qset_r.c
  error: invalid argument '-std=c++11' not allowed with 'C'
  gcc: stardist/lib/qhull_src/src/libqhull_r/merge_r.c
  error: invalid argument '-std=c++11' not allowed with 'C'
  gcc: stardist/lib/qhull_src/src/libqhull_r/io_r.c
  error: invalid argument '-std=c++11' not allowed with 'C'
  gcc: stardist/lib/qhull_src/src/libqhull_r/geom2_r.c
  error: invalid argument '-std=c++11' not allowed with 'C'
  gcc: stardist/lib/qhull_src/src/libqhullcpp/Qhull.cpp
  gcc: stardist/lib/qhull_src/src/libqhull_r/user_r.c
  error: invalid argument '-std=c++11' not allowed with 'C'
  error: Command "gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/opt/anaconda3/include -arch x86_64 -I/opt/anaconda3/include -arch x86_64 -I/private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-l3x94rr5/overlay/lib/python3.7/site-packages/numpy/core/include -Istardist/lib/qhull_src/src -I/opt/anaconda3/include/python3.7m -c stardist/lib/qhull_src/src/libqhull_r/stat_r.c -o build/temp.macosx-10.9-x86_64-3.7/stardist/lib/qhull_src/src/libqhull_r/stat_r.o -std=c++11" failed with exit status 1
  ----------------------------------------
  ERROR: Failed building wheel for stardist
Failed to build stardist
ERROR: Could not build wheels for stardist which use PEP 517 and cannot be installed directly
Note: you may need to restart the kernel to use updated packages.
```

Did you follow the Troubleshooting guidelines?

Hello,
Yes, so i install homebrew then i installed gcc then i ran the command CC=gcc-9 CXX=g++-9 pip install stardist
Then i get this error below.
I checked the version of python i have on the terminal and it is
% python3 --version
Python 3.8.4
so im not really sure what to do now
Defaulting to user installation because normal site-packages is not writeable
Collecting stardist
Using cached stardist-0.1.0.tar.gz (46 kB)
Collecting csbdeep
Using cached csbdeep-0.6.0-py2.py3-none-any.whl (67 kB)
Collecting scikit-image
Using cached scikit_image-0.14.5-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl (29.3 MB)
Requirement already satisfied: numpy in /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python (from csbdeep->stardist) (1.8.0rc1)
Collecting tifffile
Using cached tifffile-2<IP_ADDRESS>-py2.py3-none-any.whl (131 kB)
Collecting backports.tempfile; python_version < "3.4"
Using cached backports.tempfile-1.0-py2.py3-none-any.whl (4.4 kB)
Requirement already satisfied: six in /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python (from csbdeep->stardist) (1.12.0)
Collecting h5py
Using cached h5py-2.10.0-cp27-cp27m-macosx_10_6_intel.whl (2.9 MB)
Requirement already satisfied: matplotlib in /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python (from csbdeep->stardist) (1.3.1)
Collecting keras<2.4,>=2.1.2
Using cached Keras-2.3.1-py2.py3-none-any.whl (377 kB)
Requirement already satisfied: scipy in /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python (from csbdeep->stardist) (0.13.0b1)
Collecting tqdm
Using cached tqdm-4.47.0-py2.py3-none-any.whl (66 kB)
Collecting pathlib2; python_version < "3"
Using cached pathlib2-2.3.5-py2.py3-none-any.whl (18 kB)
Collecting imagecodecs-lite<=2020; python_version < "3.6"
Using cached imagecodecs-lite-2019.12.3.tar.gz (1.1 MB)
ERROR: Command errored out with exit status 1:
command: /System/Library/Frameworks/Python.framework/Versions/2.7/Resources/Python.app/Contents/MacOS/Python -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-install-FhuQIv/imagecodecs-lite/setup.py'"'"'; file='"'"'/private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-install-FhuQIv/imagecodecs-lite/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(file);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, file, '"'"'exec'"'"'))' egg_info --egg-base /private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-pip-egg-info-I2_dBJ
cwd: /private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-install-FhuQIv/imagecodecs-lite/
Complete output (51 lines):
Traceback (most recent call last):
File "", line 1, in
File "/private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-install-FhuQIv/imagecodecs-lite/setup.py", line 101, in
'Programming Language :: Python :: Implementation :: CPython',
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/init.py", line 144, in setup
_install_setup_requires(attrs)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/init.py", line 139, in _install_setup_requires
dist.fetch_build_eggs(dist.setup_requires)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/dist.py", line 717, in fetch_build_eggs
replace_conflicting=True,
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/pkg_resources/init.py", line 782, in resolve
replace_conflicting=replace_conflicting
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/pkg_resources/init.py", line 1065, in best_match
return self.obtain(req, installer)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/pkg_resources/init.py", line 1077, in obtain
return installer(requirement)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/dist.py", line 784, in fetch_build_egg
return cmd.easy_install(req)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/command/easy_install.py", line 679, in easy_install
return self.install_item(spec, dist.location, tmpdir, deps)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/command/easy_install.py", line 705, in install_item
dists = self.install_eggs(spec, download, tmpdir)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/command/easy_install.py", line 890, in install_eggs
return self.build_and_install(setup_script, setup_base)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/command/easy_install.py", line 1158, in build_and_install
self.run_setup(setup_script, setup_base, args)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/command/easy_install.py", line 1144, in run_setup
run_setup(setup_script, args)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/sandbox.py", line 253, in run_setup
raise
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/contextlib.py", line 35, in exit
self.gen.throw(type, value, traceback)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/sandbox.py", line 195, in setup_context
yield
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/contextlib.py", line 35, in exit
self.gen.throw(type, value, traceback)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/sandbox.py", line 166, in save_modules
saved_exc.resume()
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/sandbox.py", line 141, in resume
six.reraise(type, exc, self._tb)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/sandbox.py", line 154, in save_modules
yield saved
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/sandbox.py", line 195, in setup_context
yield
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/sandbox.py", line 250, in run_setup
_execfile(setup_script, ns)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/setuptools/sandbox.py", line 45, in _execfile
exec(code, globals, locals)
File "/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/easy_install-d8fAD9/numpy-1.19.0/setup.py", line 30, in
re.MULTILINE | re.DOTALL).groups()[0]
RuntimeError: Python version >= 3.6 required.
----------------------------------------
ERROR: Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.
Thank you

...
Requirement already satisfied: numpy in /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python (from csbdeep->stardist) (1.8.0rc1)
...

It seems to be using the wrong Python, i.e. macOS's built-in Python 2.7.
Try this: CC=gcc-9 CXX=g++-9 python3 -m pip install stardist

ahhh i see !
When i do that i get the same error that i got in conda :
ERROR: Failed building wheel for stardist
Building wheel for pyyaml (setup.py) ... done
Created wheel for pyyaml: filename=PyYAML-5.3.1-cp38-cp38-macosx_10_15_x86_64.whl size=44625 sha256=306b50351a83e67033b6abb385cfae96431a7c28f261a4040ad68e9a16c3e2cf
Stored in directory: /Users/seleit/Library/Caches/pip/wheels/13/90/db/290ab3a34f2ef0b5a0f89235dc2d40fea83e77de84ed2dc05c
Successfully built pyyaml
Failed to build stardist
ERROR: Could not build wheels for stardist which use PEP 517 and cannot be installed directly
full error below:
CC=gcc-9 CXX=g++-9 python3 -m pip install stardist
Collecting stardist
Using cached stardist-0.6.0.tar.gz (407 kB)
Installing build dependencies ... done
Getting requirements to build wheel ... done
Preparing wheel metadata ... done
Collecting csbdeep>=0.6.0
Using cached csbdeep-0.6.0-py2.py3-none-any.whl (67 kB)
Collecting numba
Downloading numba-0.50.1-cp38-cp38-macosx_10_14_x86_64.whl (2.1 MB)
|████████████████████████████████| 2.1 MB 1.5 MB/s
Collecting scikit-image
Downloading scikit_image-0.17.2-cp38-cp38-macosx_10_13_x86_64.whl (12.2 MB)
|████████████████████████████████| 12.2 MB 6.1 MB/s
Collecting h5py
Downloading h5py-2.10.0-cp38-cp38-macosx_10_9_x86_64.whl (3.0 MB)
|████████████████████████████████| 3.0 MB 5.8 MB/s
Collecting keras<2.4,>=2.1.2
Using cached Keras-2.3.1-py2.py3-none-any.whl (377 kB)
Collecting numpy
Using cached numpy-1.19.0-cp38-cp38-macosx_10_9_x86_64.whl (15.3 MB)
Collecting six
Using cached six-1.15.0-py2.py3-none-any.whl (10 kB)
Collecting matplotlib
Downloading matplotlib-3.2.2-cp38-cp38-macosx_10_9_x86_64.whl (12.5 MB)
|████████████████████████████████| 12.5 MB 6.7 MB/s
Collecting tifffile
Using cached tifffile-2020.7.4-py3-none-any.whl (138 kB)
Collecting scipy
Downloading scipy-1.5.1-cp38-cp38-macosx_10_9_x86_64.whl (28.9 MB)
|████████████████████████████████| 28.9 MB 224 kB/s
Collecting tqdm
Using cached tqdm-4.47.0-py2.py3-none-any.whl (66 kB)
Collecting llvmlite<0.34,>=0.33.0.dev0
Downloading llvmlite-0.33.0-cp38-cp38-macosx_10_9_x86_64.whl (17.3 MB)
|████████████████████████████████| 17.3 MB 537 kB/s
Requirement already satisfied: setuptools in /usr/local/lib/python3.8/site-packages (from numba->stardist) (49.2.0)
Collecting pillow!=7.1.0,!=7.1.1,>=4.3.0
Downloading Pillow-7.2.0-cp38-cp38-macosx_10_10_x86_64.whl (2.2 MB)
|████████████████████████████████| 2.2 MB 6.0 MB/s
Collecting imageio>=2.3.0
Downloading imageio-2.9.0-py3-none-any.whl (3.3 MB)
|████████████████████████████████| 3.3 MB 5.6 MB/s
Collecting networkx>=2.0
Downloading networkx-2.4-py3-none-any.whl (1.6 MB)
|████████████████████████████████| 1.6 MB 5.7 MB/s
Collecting PyWavelets>=1.1.1
Downloading PyWavelets-1.1.1-cp38-cp38-macosx_10_9_x86_64.whl (4.3 MB)
|████████████████████████████████| 4.3 MB 5.7 MB/s
Collecting keras-applications>=1.0.6
Using cached Keras_Applications-1.0.8-py3-none-any.whl (50 kB)
Collecting keras-preprocessing>=1.0.5
Using cached Keras_Preprocessing-1.1.2-py2.py3-none-any.whl (42 kB)
Collecting pyyaml
Downloading PyYAML-5.3.1.tar.gz (269 kB)
|████████████████████████████████| 269 kB 5.8 MB/s
Collecting python-dateutil>=2.1
Downloading python_dateutil-2.8.1-py2.py3-none-any.whl (227 kB)
|████████████████████████████████| 227 kB 5.5 MB/s
Collecting cycler>=0.10
Downloading cycler-0.10.0-py2.py3-none-any.whl (6.5 kB)
Collecting kiwisolver>=1.0.1
Downloading kiwisolver-1.2.0-cp38-cp38-macosx_10_9_x86_64.whl (60 kB)
|████████████████████████████████| 60 kB 5.7 MB/s
Collecting pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1
Downloading pyparsing-2.4.7-py2.py3-none-any.whl (67 kB)
|████████████████████████████████| 67 kB 3.4 MB/s
Collecting decorator>=4.3.0
Downloading decorator-4.4.2-py2.py3-none-any.whl (9.2 kB)
Building wheels for collected packages: stardist, pyyaml
Building wheel for stardist (PEP 517) ... error
ERROR: Command errored out with exit status 1:
command<EMAIL_ADDRESS>/usr/local/lib/python3.8/site-packages/pip/_vendor/pep517/_in_process.py build_wheel /var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/tmpiwhytwg1
cwd: /private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-install-_n2chtrp/stardist
Complete output (54 lines):
running bdist_wheel
running build
running build_py
creating build
creating build/lib.macosx-10.15-x86_64-3.8
creating build/lib.macosx-10.15-x86_64-3.8/stardist
copying stardist/version.py -> build/lib.macosx-10.15-x86_64-3.8/stardist
copying stardist/rays3d.py -> build/lib.macosx-10.15-x86_64-3.8/stardist
copying stardist/sample_patches.py -> build/lib.macosx-10.15-x86_64-3.8/stardist
copying stardist/nms.py -> build/lib.macosx-10.15-x86_64-3.8/stardist
copying stardist/init.py -> build/lib.macosx-10.15-x86_64-3.8/stardist
copying stardist/matching.py -> build/lib.macosx-10.15-x86_64-3.8/stardist
copying stardist/utils.py -> build/lib.macosx-10.15-x86_64-3.8/stardist
copying stardist/big.py -> build/lib.macosx-10.15-x86_64-3.8/stardist
creating build/lib.macosx-10.15-x86_64-3.8/stardist/plot
copying stardist/plot/plot.py -> build/lib.macosx-10.15-x86_64-3.8/stardist/plot
copying stardist/plot/render.py -> build/lib.macosx-10.15-x86_64-3.8/stardist/plot
copying stardist/plot/init.py -> build/lib.macosx-10.15-x86_64-3.8/stardist/plot
creating build/lib.macosx-10.15-x86_64-3.8/stardist/models
copying stardist/models/model3d.py -> build/lib.macosx-10.15-x86_64-3.8/stardist/models
copying stardist/models/model2d.py -> build/lib.macosx-10.15-x86_64-3.8/stardist/models
copying stardist/models/init.py -> build/lib.macosx-10.15-x86_64-3.8/stardist/models
copying stardist/models/base.py -> build/lib.macosx-10.15-x86_64-3.8/stardist/models
creating build/lib.macosx-10.15-x86_64-3.8/stardist/geometry
copying stardist/geometry/init.py -> build/lib.macosx-10.15-x86_64-3.8/stardist/geometry
copying stardist/geometry/geom3d.py -> build/lib.macosx-10.15-x86_64-3.8/stardist/geometry
copying stardist/geometry/geom2d.py -> build/lib.macosx-10.15-x86_64-3.8/stardist/geometry
creating build/lib.macosx-10.15-x86_64-3.8/stardist/kernels
copying stardist/kernels/stardist2d.cl -> build/lib.macosx-10.15-x86_64-3.8/stardist/kernels
copying stardist/kernels/stardist3d.cl -> build/lib.macosx-10.15-x86_64-3.8/stardist/kernels
running build_ext
building 'stardist.lib.stardist2d' extension
Warning: Can't read registry to find the necessary compiler setting
Make sure that Python modules winreg, win32api or win32con are installed.
C compiler: gcc-9 -Wno-unused-result -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -fwrapv -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX10.15.sdk -I/Library/Developer/CommandLineTools/SDKs/MacOSX10.15.sdk/usr/include -I/Library/Developer/CommandLineTools/SDKs/MacOSX10.15.sdk/System/Library/Frameworks/Tk.framework/Versions/8.5/Headers
creating build/temp.macosx-10.15-x86_64-3.8
creating build/temp.macosx-10.15-x86_64-3.8/stardist
creating build/temp.macosx-10.15-x86_64-3.8/stardist/lib
compile options: '-I/private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-594ahg06/overlay/lib/python3.8/site-packages/numpy/core/include -I/usr/local/include<EMAIL_ADDRESS>-I/usr/local/opt/sqlite/include<EMAIL_ADDRESS>-c'
extra options: '-std=c++11 -fopenmp'
gcc-9: stardist/lib/clipper.cpp
gcc-9: stardist/lib/stardist2d.cpp
gcc-9: stardist/lib/utils.cpp
compiling with OpenMP support failed, re-trying without
building 'stardist.lib.stardist2d' extension
C compiler: gcc-9 -Wno-unused-result -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -fwrapv -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX10.15.sdk -I/Library/Developer/CommandLineTools/SDKs/MacOSX10.15.sdk/usr/include -I/Library/Developer/CommandLineTools/SDKs/MacOSX10.15.sdk/System/Library/Frameworks/Tk.framework/Versions/8.5/Headers
compile options: '-I/private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-594ahg06/overlay/lib/python3.8/site-packages/numpy/core/include -I/usr/local/include<EMAIL_ADDRESS>-I/usr/local/opt/sqlite/include<EMAIL_ADDRESS>-c'
extra options: '-std=c++11'
gcc-9: stardist/lib/stardist2d.cpp
gcc-9: stardist/lib/utils.cpp
gcc-9: stardist/lib/clipper.cpp
error: Command "gcc-9 -Wno-unused-result -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -fwrapv -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX10.15.sdk -I/Library/Developer/CommandLineTools/SDKs/MacOSX10.15.sdk/usr/include -I/Library/Developer/CommandLineTools/SDKs/MacOSX10.15.sdk/System/Library/Frameworks/Tk.framework/Versions/8.5/Headers -I/private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-594ahg06/overlay/lib/python3.8/site-packages/numpy/core/include -I/usr/local/include<EMAIL_ADDRESS>-I/usr/local/opt/sqlite/include<EMAIL_ADDRESS>-c stardist/lib/clipper.cpp -o build/temp.macosx-10.15-x86_64-3.8/stardist/lib/clipper.o -std=c++11" failed with exit status 127
ERROR: Failed building wheel for stardist
Building wheel for pyyaml (setup.py) ... done
Created wheel for pyyaml: filename=PyYAML-5.3.1-cp38-cp38-macosx_10_15_x86_64.whl size=44625 sha256=306b50351a83e67033b6abb385cfae96431a7c28f261a4040ad68e9a16c3e2cf
Stored in directory: /Users/seleit/Library/Caches/pip/wheels/13/90/db/290ab3a34f2ef0b5a0f89235dc2d40fea83e77de84ed2dc05c
Successfully built pyyaml
Failed to build stardist
ERROR: Could not build wheels for stardist which use PEP 517 and cannot be installed directly

Could you try the following:
1.) Activate your conda environment (assuming you use a base env)
conda activate
2) Make sure the correct python is used (it should output something with 3.8 and your conda path)
python -V
which python
3) CC="gcc-9" CXX="g++-9" pip install stardist

Thank you for your help,
i still get the same error
% conda activate
(base) seleit@alis-macbook ~ % python -V
Python 3.7.6
(base) seleit@alis-macbook ~ % which python
/opt/anaconda3/bin/python
(base) seleit@alis-macbook ~ % CC="gcc-9" CXX="g++-9" pip install stardist
Collecting stardist
Using cached stardist-0.6.0.tar.gz (407 kB)
Installing build dependencies ... done
Getting requirements to build wheel ... done
Preparing wheel metadata ... done
Requirement already satisfied: numba in /opt/anaconda3/lib/python3.7/site-packages (from stardist) (0.48.0)
Requirement already satisfied: scikit-image in /opt/anaconda3/lib/python3.7/site-packages (from stardist) (0.16.2)
Collecting csbdeep>=0.6.0
Using cached csbdeep-0.6.0-py2.py3-none-any.whl (67 kB)
Requirement already satisfied: llvmlite<0.32.0,>=0.31.0dev0 in /opt/anaconda3/lib/python3.7/site-packages (from numba->stardist) (0.31.0)
Requirement already satisfied: numpy>=1.15 in ./.local/lib/python3.7/site-packages (from numba->stardist) (1.18.5)
Requirement already satisfied: setuptools in ./.local/lib/python3.7/site-packages (from numba->stardist) (49.2.0)
Requirement already satisfied: scipy>=0.19.0 in /opt/anaconda3/lib/python3.7/site-packages (from scikit-image->stardist) (1.4.1)
Requirement already satisfied: pillow>=4.3.0 in /opt/anaconda3/lib/python3.7/site-packages (from scikit-image->stardist) (7.0.0)
Requirement already satisfied: imageio>=2.3.0 in /opt/anaconda3/lib/python3.7/site-packages (from scikit-image->stardist) (2.6.1)
Requirement already satisfied: matplotlib!=3.0.0,>=2.0.0 in /opt/anaconda3/lib/python3.7/site-packages (from scikit-image->stardist) (3.1.3)
Requirement already satisfied: PyWavelets>=0.4.0 in /opt/anaconda3/lib/python3.7/site-packages (from scikit-image->stardist) (1.1.1)
Requirement already satisfied: networkx>=2.0 in /opt/anaconda3/lib/python3.7/site-packages (from scikit-image->stardist) (2.4)
Requirement already satisfied: tqdm in /opt/anaconda3/lib/python3.7/site-packages (from csbdeep>=0.6.0->stardist) (4.42.1)
Requirement already satisfied: six in ./.local/lib/python3.7/site-packages (from csbdeep>=0.6.0->stardist) (1.15.0)
Collecting tifffile
Using cached tifffile-2020.7.4-py3-none-any.whl (138 kB)
Collecting keras<2.4,>=2.1.2
Using cached Keras-2.3.1-py2.py3-none-any.whl (377 kB)
Requirement already satisfied: h5py in /opt/anaconda3/lib/python3.7/site-packages (from csbdeep>=0.6.0->stardist) (2.10.0)
Requirement already satisfied: kiwisolver>=1.0.1 in /opt/anaconda3/lib/python3.7/site-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image->stardist) (1.1.0)
Requirement already satisfied: python-dateutil>=2.1 in /opt/anaconda3/lib/python3.7/site-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image->stardist) (2.8.1)
Requirement already satisfied: cycler>=0.10 in /opt/anaconda3/lib/python3.7/site-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image->stardist) (0.10.0)
Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /opt/anaconda3/lib/python3.7/site-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image->stardist) (2.4.6)
Requirement already satisfied: decorator>=4.3.0 in /opt/anaconda3/lib/python3.7/site-packages (from networkx>=2.0->scikit-image->stardist) (4.4.1)
Requirement already satisfied: pyyaml in /opt/anaconda3/lib/python3.7/site-packages (from keras<2.4,>=2.1.2->csbdeep>=0.6.0->stardist) (5.3)
Collecting keras-preprocessing>=1.0.5
Using cached Keras_Preprocessing-1.1.2-py2.py3-none-any.whl (42 kB)
Collecting keras-applications>=1.0.6
Using cached Keras_Applications-1.0.8-py3-none-any.whl (50 kB)
Building wheels for collected packages: stardist
Building wheel for stardist (PEP 517) ... error
ERROR: Command errored out with exit status 1:
command: /opt/anaconda3/bin/python /opt/anaconda3/lib/python3.7/site-packages/pip/_vendor/pep517/_in_process.py build_wheel /var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/tmpljuzjvvv
cwd: /private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-install-o0tgxd89/stardist
Complete output (54 lines):
running bdist_wheel
running build
running build_py
creating build
creating build/lib.macosx-10.9-x86_64-3.7
creating build/lib.macosx-10.9-x86_64-3.7/stardist
copying stardist/version.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
copying stardist/rays3d.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
copying stardist/sample_patches.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
copying stardist/nms.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
copying stardist/init.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
copying stardist/matching.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
copying stardist/utils.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
copying stardist/big.py -> build/lib.macosx-10.9-x86_64-3.7/stardist
creating build/lib.macosx-10.9-x86_64-3.7/stardist/plot
copying stardist/plot/plot.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/plot
copying stardist/plot/render.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/plot
copying stardist/plot/init.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/plot
creating build/lib.macosx-10.9-x86_64-3.7/stardist/models
copying stardist/models/model3d.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/models
copying stardist/models/model2d.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/models
copying stardist/models/init.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/models
copying stardist/models/base.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/models
creating build/lib.macosx-10.9-x86_64-3.7/stardist/geometry
copying stardist/geometry/init.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/geometry
copying stardist/geometry/geom3d.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/geometry
copying stardist/geometry/geom2d.py -> build/lib.macosx-10.9-x86_64-3.7/stardist/geometry
creating build/lib.macosx-10.9-x86_64-3.7/stardist/kernels
copying stardist/kernels/stardist2d.cl -> build/lib.macosx-10.9-x86_64-3.7/stardist/kernels
copying stardist/kernels/stardist3d.cl -> build/lib.macosx-10.9-x86_64-3.7/stardist/kernels
running build_ext
building 'stardist.lib.stardist2d' extension
Warning: Can't read registry to find the necessary compiler setting
Make sure that Python modules winreg, win32api or win32con are installed.
C compiler: gcc-9 -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/opt/anaconda3/include -arch x86_64 -I/opt/anaconda3/include -arch x86_64
creating build/temp.macosx-10.9-x86_64-3.7
creating build/temp.macosx-10.9-x86_64-3.7/stardist
creating build/temp.macosx-10.9-x86_64-3.7/stardist/lib
compile options: '-I/private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-uq_z8z0n/overlay/lib/python3.7/site-packages/numpy/core/include -I/opt/anaconda3/include/python3.7m -c'
extra options: '-std=c++11 -fopenmp'
gcc-9: stardist/lib/stardist2d.cpp
gcc-9: stardist/lib/utils.cpp
gcc-9: stardist/lib/clipper.cpp
compiling with OpenMP support failed, re-trying without
building 'stardist.lib.stardist2d' extension
C compiler: gcc-9 -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/opt/anaconda3/include -arch x86_64 -I/opt/anaconda3/include -arch x86_64
compile options: '-I/private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-uq_z8z0n/overlay/lib/python3.7/site-packages/numpy/core/include -I/opt/anaconda3/include/python3.7m -c'
extra options: '-std=c++11'
gcc-9: stardist/lib/stardist2d.cpp
gcc-9: stardist/lib/clipper.cpp
gcc-9: stardist/lib/utils.cpp
error: Command "gcc-9 -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/opt/anaconda3/include -arch x86_64 -I/opt/anaconda3/include -arch x86_64 -I/private/var/folders/lz/h4nxm8jd64qdhlr57n1y_yx80000gq/T/pip-build-env-uq_z8z0n/overlay/lib/python3.7/site-packages/numpy/core/include -I/opt/anaconda3/include/python3.7m -c stardist/lib/clipper.cpp -o build/temp.macosx-10.9-x86_64-3.7/stardist/lib/clipper.o -std=c++11" failed with exit status 127
ERROR: Failed building wheel for stardist
Failed to build stardist
ERROR: Could not build wheels for stardist which use PEP 517 and cannot be installed directly

What gcc version do you have?
gcc-9 --version

I had gcc-10 installed not 9 ! i reinstalled 9 via brew and the stardist installation worked !
Thank you !
i now run into a similar issue that was raised earlier, i tried your solution but i still get an error message:
(base) seleit@alis-macbook ~ % otool -L  /opt/anaconda3/lib/python3.7/site-packages/stardist/lib/stardist3d.cpython-37m-darwin.so
/opt/anaconda3/lib/python3.7/site-packages/stardist/lib/stardist3d.cpython-37m-darwin.so:
<EMAIL_ADDRESS>(compatibility version 7.0.0, current version 7.28.0)
/usr/local/Cellar/gcc/9.1.0/lib/gcc/9/libgomp.1.dylib (compatibility version 2.0.0, current version 2.0.0)
/usr/lib/libSystem.B.dylib (compatibility version 1.0.0, current version 1281.100.1)
/usr/local/lib/gcc/9/libgcc_s.1.dylib (compatibility version 1.0.0, current version 1.0.0)
(base) seleit@alis-macbook ~ %<EMAIL_ADDRESS>(base) seleit@alis-macbook ~ % dst="/usr/local/Cellar/gcc/9.1.0/lib/gcc/9/libgomp.1.dylib"
(base) seleit@alis-macbook ~ % install_name_tool -change ${src} ${dst} /opt/anaconda3/lib/python3.7/site-packages/stardist/lib/stardist3d.cpython-37m-darwin.so
install_name_tool -change ${src} ${dst} /opt/anaconda3/lib/python3.7/site-packages/stardist/lib/stardist2d.cpython-37m-darwin.so
(base) seleit@alis-macbook ~ % ipython
Python 3.7.6 (default, Jan  8 2020, 13:42:34)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.12.0 -- An enhanced Interactive Python. Type '?' for help.
In [1]: from stardist.models import StarDist2D
...:
...: # prints a list of available models
...: StarDist2D.from_pretrained()
ImportError                               Traceback (most recent call last)
 in
----> 1 from stardist.models import StarDist2D
2
3 # prints a list of available models
4 StarDist2D.from_pretrained()
/opt/anaconda3/lib/python3.7/site-packages/stardist/init.py in
6 from .nms import non_maximum_suppression, non_maximum_suppression_3d, non_maximum_suppression_3d_sparse
7 from .utils import edt_prob, fill_label_holes, sample_points, calculate_extents, export_imagej_rois, gputools_available
----> 8 from .geometry import star_dist,   polygons_to_label,   relabel_image_stardist, ray_angles, dist_to_coord
9 from .geometry import star_dist3D, polyhedron_to_label, relabel_image_stardist3D
10 from .plot.plot import random_label_cmap, draw_polygons, _draw_polygons
/opt/anaconda3/lib/python3.7/site-packages/stardist/geometry/init.py in
3 # TODO: rethink naming for 2D/3D functions
4
----> 5 from .geom2d import star_dist, polygons_to_label, relabel_image_stardist, ray_angles, dist_to_coord
6 from .geom3d import star_dist3D, polyhedron_to_label, relabel_image_stardist3D, dist_to_coord3D, export_to_obj_file3D
7
/opt/anaconda3/lib/python3.7/site-packages/stardist/geometry/geom2d.py in
9 from ..utils import path_absolute, _is_power_of_2, _normalize_grid
10 from ..matching import _check_label_array
---> 11 from ..lib.stardist2d import c_star_dist
12
13
ImportError: dlopen(/opt/anaconda3/lib/python3.7/site-packages/stardist/lib/stardist2d.cpython-37m-darwin.so, 2): Library not loaded: /usr/local/Cellar/gcc/9.1.0/lib/gcc/9/libgomp.1.dylib
Referenced from: /opt/anaconda3/lib/python3.7/site-packages/stardist/lib/stardist2d.cpython-37m-darwin.so
Reason: image not found

Does /usr/local/Cellar/gcc/9.1.0/lib/gcc/9/libgomp.1.dylib exist? (You need to adapt that path to your gcc libgomp path)

Thanks again,
I checked, this is its path<EMAIL_ADDRESS>so i ran :
<EMAIL_ADDRESS><EMAIL_ADDRESS>(base) seleit@alis-macbook ~ % install_name_tool -change ${src} ${dst} /opt/anaconda3/lib/python3.7/site-packages/stardist/lib/stardist3d.cpython-37m-darwin.so
(base) seleit@alis-macbook ~ % install_name_tool -change ${src} ${dst} /opt/anaconda3/lib/python3.7/site-packages/stardist/lib/stardist2d.cpython-37m-darwin.so
(base) seleit@alis-macbook ~ % ipython
Python 3.7.6 (default, Jan  8 2020, 13:42:34)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.12.0 -- An enhanced Interactive Python. Type '?' for help.
In [1]: from stardist.models import StarDist2D
...:
...: # prints a list of available models
...: StarDist2D.from_pretrained()
ImportError                               Traceback (most recent call last)
 in
----> 1 from stardist.models import StarDist2D
2
3 # prints a list of available models
4 StarDist2D.from_pretrained()
/opt/anaconda3/lib/python3.7/site-packages/stardist/init.py in
6 from .nms import non_maximum_suppression, non_maximum_suppression_3d, non_maximum_suppression_3d_sparse
7 from .utils import edt_prob, fill_label_holes, sample_points, calculate_extents, export_imagej_rois, gputools_available
----> 8 from .geometry import star_dist,   polygons_to_label,   relabel_image_stardist, ray_angles, dist_to_coord
9 from .geometry import star_dist3D, polyhedron_to_label, relabel_image_stardist3D
10 from .plot.plot import random_label_cmap, draw_polygons, _draw_polygons
/opt/anaconda3/lib/python3.7/site-packages/stardist/geometry/init.py in
3 # TODO: rethink naming for 2D/3D functions
4
----> 5 from .geom2d import star_dist, polygons_to_label, relabel_image_stardist, ray_angles, dist_to_coord
6 from .geom3d import star_dist3D, polyhedron_to_label, relabel_image_stardist3D, dist_to_coord3D, export_to_obj_file3D
7
/opt/anaconda3/lib/python3.7/site-packages/stardist/geometry/geom2d.py in
9 from ..utils import path_absolute, _is_power_of_2, _normalize_grid
10 from ..matching import _check_label_array
---> 11 from ..lib.stardist2d import c_star_dist
12
13
ImportError: dlopen(/opt/anaconda3/lib/python3.7/site-packages/stardist/lib/stardist2d.cpython-37m-darwin.so, 2): Library not loaded: /usr/local/Cellar/gcc/9.1.0/lib/gcc/9/libgomp.1.dylib
Referenced from: /opt/anaconda3/lib/python3.7/site-packages/stardist/lib/stardist2d.cpython-37m-darwin.so
Reason: image not found

I suspect that running install_name_tool twice with different paths has mixed things up a bit.  I would suggest reinstalling stardist
pip uninstall stardist
CC=gcc-9 CXX=g++-9 pip install stardist

and then trying again renaming the libs with the correct libgomp path (as you just did).

You were right ! it worked :)
Thank you very much !!

Great to hear! :)


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