Issue with pip install size_constrained_clustering

[HediHargam]

Hello,

First of all, great work and nice repository !

However, I have an issue when i try to install with pip. I have this error message :

ValueError: '/tmp/pip-install-hztjsh5l/size-constrained-clustering_0f0eaa2d194b40909287b3e66a4ceeb5/size_constrained_clustering/k_means_constrained/mincostflowvectorized.pyx' doesn't match any files

I think it come from cython dependencies, and/or with 'pyx' extensions in setup.py

I can however use pip install git+https://github.com/jingw2/size_constrained_clustering (it works) but it's quit difficult then for pip to resolve dependency with other libraries.

Has anyone ever had the same issue before?

[bohanwu424]

I have the same issue.

[jingw2]

I will fix that issue soon

[EricPostMaster]

I'm having the same issue, but I'm not able to get it to work with pip install git+https://github.com/jingw2/size_constrained_clustering like @HediHargam. I added --user and still got errors. Any suggestions?

[jmlarson1]

I am also having this issue with clustering_d464fd0903904d20867af7efe88f177d/size_constrained_clustering/k_means_constrained/mincostflowvectorized.pyx

[jingw2]

Hi, all, I guess the main problem is from version. I used Python 3.6 to develop. Python 3.6 installing still worked but when I applied Python 3.7 to install, the problem appeared.

[cjmateos]

Hi,

I tried to install it on Docker using different versions of python (3.6, 3.7, 3.8 and 3.9) and it fails when I try to install from pip

$ docker run -it python:3.6-buster bash

root@82ff32d4be50:/# python -V
Python 3.6.14

root@82ff32d4be50:/# pip install size-constrained-clustering
Collecting size-constrained-clustering
  Downloading size_constrained_clustering-0.1.1.tar.gz (52 kB)
     |████████████████████████████████| 52 kB 1.1 MB/s
    ERROR: Command errored out with exit status 1:
     command: /usr/local/bin/python -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-install-de6gl_ue/size-constrained-clustering_28478f8ae3d64cca9978330fa5619d95/setup.py'"'"'; __file__='"'"'/tmp/pip-install-de6gl_ue/size-constrained-clustering_28478f8ae3d64cca9978330fa5619d95/setup.py'"'"';f = getattr(tokenize, '"'"'open'"'"', open)(__file__) if os.path.exists(__file__) else io.StringIO('"'"'from setuptools import setup; setup()'"'"');code = f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' egg_info --egg-base /tmp/pip-pip-egg-info-a049ykxt
         cwd: /tmp/pip-install-de6gl_ue/size-constrained-clustering_28478f8ae3d64cca9978330fa5619d95/
    Complete output (11 lines):
    Traceback (most recent call last):
      File "<string>", line 1, in <module>
      File "/tmp/pip-install-de6gl_ue/size-constrained-clustering_28478f8ae3d64cca9978330fa5619d95/setup.py", line 63, in <module>
        extensions = cythonize(extensions, compiler_directives=compiler_directives)
      File "/tmp/pip-install-de6gl_ue/size-constrained-clustering_28478f8ae3d64cca9978330fa5619d95/.eggs/Cython-0.29.24-py3.6-linux-x86_64.egg/Cython/Build/Dependencies.py", line 972, in cythonize
        aliases=aliases)
      File "/tmp/pip-install-de6gl_ue/size-constrained-clustering_28478f8ae3d64cca9978330fa5619d95/.eggs/Cython-0.29.24-py3.6-linux-x86_64.egg/Cython/Build/Dependencies.py", line 815, in create_extension_list
        for file in nonempty(sorted(extended_iglob(filepattern)), "'%s' doesn't match any files" % filepattern):
      File "/tmp/pip-install-de6gl_ue/size-constrained-clustering_28478f8ae3d64cca9978330fa5619d95/.eggs/Cython-0.29.24-py3.6-linux-x86_64.egg/Cython/Build/Dependencies.py", line 114, in nonempty
        raise ValueError(error_msg)
    ValueError: '/tmp/pip-install-de6gl_ue/size-constrained-clustering_28478f8ae3d64cca9978330fa5619d95/size_constrained_clustering/k_means_constrained/mincostflow_vectorized_.pyx' doesn't match any files
    ----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/de/a2/eb43a58139986f3280b378125b850a33d663021426f202027720fd080e6a/size_constrained_clustering-0.1.1.tar.gz#sha256=27acf88ea48ed5b8690f1f0869ecfb28da805bdd86cb3d9b37a9eceaa9b9908a (from https://pypi.org/simple/size-constrained-clustering/) (requires-python:>=3.6). Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.
ERROR: Could not find a version that satisfies the requirement size-constrained-clustering (from versions: 0.1.1)
ERROR: No matching distribution found for size-constrained-clustering

[winston01]

Same error here, works with @HediHargam 's solution (using gitlab as source).

[cjmateos]

The issue seems to be that the package uploaded to PyPI is broken.

Installing the package from the Github repo and using the tag v0.1.1 it works!

pip install git+https://github.com/jingw2/size_constrained_clustering@v0.1.1

[Hassan6678]

In my case when I used pip install size_constrained_clustering not working on the Window and I also try on Ubuntu

after that when I used pip install git+https://github.com/jingw2/size_constrained_clustering@v0.1.1 it working on google Colab and Window with python version 3.6

[danvip10]

I also have this issue, has a workaround been found? Unfortunately I cannot install via github from the machine I'm working on.

[anonymously123456]

I still have this issue and my python version is 3.6. pip install git+https://github.com/jingw2/size_constrained_clustering@v0.1.1 this is not work，could you please tell me the reason？

[AlbertPlaPlanas]

It seems the problem is when installing matplotlib.

I've noticed there's one fork of the repo in which a user ( @knasti ) has removed matplotlib dependencies and then it works: You could install from there using git+https://github.com/knasti/size_constrained_clustering

[varshitha021]

when i use this git+https://github.com/knasti/size_constrained_clustering

[OlegVasilyev4096]

Also problem installing. pip install size-constrained-clustering

Collecting size-constrained-clustering Using cached size_constrained_clustering-0.1.1.tar.gz (52 kB) Preparing metadata (setup.py) ... error error: subprocess-exited-with-error

× python setup.py egg_info did not run successfully. │ exit code: 1 ╰─> [12 lines of output] Traceback (most recent call last): File "", line 2, in File "", line 34, in File "/private/var/folders/xw/nv8rc6nj4vnc4gncwcrs3s1h0000gp/T/pip-install-_63izb/size-constrained-clustering_a0f022cf99a74c0abb8531a512f818b0/setup.py", line 63, in extensions = cythonize(extensions, compiler_directives=compiler_directives) File "/opt/homebrew/lib/python3.9/site-packages/Cython/Build/Dependencies.py", line 973, in cythonize module_list, module_metadata = create_extension_list( File "/opt/homebrew/lib/python3.9/site-packages/Cython/Build/Dependencies.py", line 816, in create_extension_list for file in nonempty(sorted(extended_iglob(filepattern)), "'%s' doesn't match any files" % filepattern): File "/opt/homebrew/lib/python3.9/site-packages/Cython/Build/Dependencies.py", line 114, in nonempty raise ValueError(error_msg) ValueError: '/private/var/folders/xw/nv8rc6nj4vnc4gncwcrs3s1h0000gp/T/pip-install-_63izb/size-constrained-clustering_a0f022cf99a74c0abb8531a512f818b0/size_constrained_clustering/k_means_constrained/mincostflowvectorized.pyx' doesn't match any files [end of output]

note: This error originates from a subprocess, and is likely not a problem with pip. error: metadata-generation-failed

× Encountered error while generating package metadata. ╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.

[AlbertPlaPlanas]

@varshitha021 and @OlegVasilyev4096 As I faced issues with the package and I just needed the Deterministic Annealing Clustering implementation, I forked and released a package that just contained that class & method. Maybe it can help:

https://github.com/AlbertPlaPlanas/size_constrained_clustering https://pypi.org/project/light-size-constrained-clustering/

[varshitha021]

Subject: Thank You for Your Help and an Update on My Progress

Dear Albert Palmaplanas,

I hope this email finds you well. I am writing to express my gratitude for your assistance in my clustering problem. Your support was instrumental in my decision to take matters into my own hands and find a solution.

However, I wanted to share some doubts I encountered during my implementation process. The primary concern was assigning appropriate values to the distribution list for the clustering algorithm. In my case, I have 22,448 data points that I wanted to cluster into 92 equal-sized clusters, each containing 244 points. I initially assigned random values to the distribution list, ensuring their sum was 1. However, this didn't yield the desired equal-sized clusters.

If you have any insights or suggestions on how I can set the distribution values more effectively to achieve equal-sized clusters, I would greatly appreciate your input. I believe your expertise would be invaluable in refining the clustering process.

Furthermore,In my project,I have to cluster buildings into clusters while considering various constraints. Specifically, I aim to take into account constraints such as roads, flyovers, water passages, and other similar elements that may exist between the buildings. By incorporating these constraints into the clustering process, I hope to achieve more meaningful and practical groupings of buildings.

the below image clearly depicts the problem statement for my project

Once again, I sincerely thank you for your assistance, and I look forward to hearing from you soon.

Best regards, Minumula Varshitha

On Fri, 28 Jul 2023 at 13:08, AlbertPlaPlanas @.***> wrote:

@varshitha021 and @OlegVasilyev4096 As I faced issues with the package and I just needed the Deterministic Annealing Clustering implementation, I forked and released a package that just contained that class & method. Maybe it can help:

https://github.com/AlbertPlaPlanas/size_constrained_clustering https://pypi.org/project/light-size-constrained-clustering/

— Reply to this email directly, view it on GitHub, or unsubscribe. You are receiving this because you were mentioned.Message ID: @.***>

[varshitha021]

Dear Albert Palmaplanas,

I hope this email finds you well. I wanted to express my heartfelt appreciation for your prompt and helpful response to my query. Your guidance on installation of the package was truly instrumental in completing my task successfully.

Thanks to your assistance, I was able to implement the required changes in my code and achieve the desired outcome. Your support made a significant difference in my project, and I am extremely grateful for your expertise and willingness to help.

As I continue to work on my project, I find myself facing another intriguing challenge that I believe your expertise could greatly benefit. My current focus is on road constraint clustering, where I aim to cluster buildings while considering constraints such as roads, flyovers, water passages, and other road-related elements that may exist between the buildings.

I would be immensely grateful if you could share your insights on the best approaches, algorithms, or methodologies that can effectively incorporate road constraints into the clustering process. Additionally, any guidance on feature engineering, preprocessing techniques, and relevant research papers or resources would be incredibly valuable.

Once again, thank you for your time and valuable input. Your assistance has been invaluable, and I cannot emphasize enough how much I appreciate your help.

Please do not hesitate to reach out if you ever need any assistance or have any questions. I am more than willing to return the favor and offer my support.

With sincerest gratitude, Minumula Varshitha

On Fri, 28 Jul 2023 at 15:12, 021-varshitha minumula @.***> wrote:

Subject: Thank You for Your Help and an Update on My Progress

Dear Albert Palmaplanas,

I hope this email finds you well. I am writing to express my gratitude for your assistance in my clustering problem. Your support was instrumental in my decision to take matters into my own hands and find a solution.

However, I wanted to share some doubts I encountered during my implementation process. The primary concern was assigning appropriate values to the distribution list for the clustering algorithm. In my case, I have 22,448 data points that I wanted to cluster into 92 equal-sized clusters, each containing 244 points. I initially assigned random values to the distribution list, ensuring their sum was 1. However, this didn't yield the desired equal-sized clusters.

If you have any insights or suggestions on how I can set the distribution values more effectively to achieve equal-sized clusters, I would greatly appreciate your input. I believe your expertise would be invaluable in refining the clustering process.

Furthermore,In my project,I have to cluster buildings into clusters while considering various constraints. Specifically, I aim to take into account constraints such as roads, flyovers, water passages, and other similar elements that may exist between the buildings. By incorporating these constraints into the clustering process, I hope to achieve more meaningful and practical groupings of buildings.

the below image clearly depicts the problem statement for my project

Once again, I sincerely thank you for your assistance, and I look forward to hearing from you soon.

Best regards, Minumula Varshitha

On Fri, 28 Jul 2023 at 13:08, AlbertPlaPlanas @.***> wrote:

@varshitha021 and @OlegVasilyev4096 As I faced issues with the package and I just needed the Deterministic Annealing Clustering implementation, I forked and released a package that just contained that class & method. Maybe it can help:

https://github.com/AlbertPlaPlanas/size_constrained_clustering https://pypi.org/project/light-size-constrained-clustering/

— Reply to this email directly, view it on GitHub, or unsubscribe. You are receiving this because you were mentioned.Message ID: @.***>

[sight007]

It's 2023.08， the same issue hasn't been fixed yet......

[varshitha021]

not yet fixed

On Tue, 15 Aug 2023 at 12:55, Mr.Gung @.***> wrote:

It's 2023.08， the same issue hasn't been fixed yet......

— Reply to this email directly, view it on GitHub https://github.com/jingw2/size_constrained_clustering/issues/2#issuecomment-1678525163, or unsubscribe https://github.com/notifications/unsubscribe-auth/A3DHOV45AICTCUK7RXYGUM3XVMP4ZANCNFSM4WSBSJAQ . You are receiving this because you were mentioned.Message ID: @.***>