Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

update scvelo for Windows #80

Closed
kevinrue opened this issue Aug 23, 2024 · 15 comments
Closed

update scvelo for Windows #80

kevinrue opened this issue Aug 23, 2024 · 15 comments

Comments

@kevinrue
Copy link
Owner

kevinrue commented Aug 23, 2024 •
edited
Loading

scvelo==0.3.2 not available due to dependency on jaxlib>=0.4.3

PS C:\Users\kevin> micromamba create -c conda-forge -c bioconda -n scvelo scvelo==0.3.2
bioconda/win-64 (check zst)                         Checked  0.3s
bioconda/noarch (check zst)                         Checked  0.3s
bioconda/win-64                                    122.0 B @ 805.0 B/s  0.2s
bioconda/noarch                                      5.3MB @   2.0MB/s  2.6s
conda-forge/noarch                                  16.1MB @   4.4MB/s  3.7s
conda-forge/win-64                                  23.9MB @   4.7MB/s  5.1s
error    libmamba Could not solve for environment specs
    The following package could not be installed
    └─ scvelo 0.3.2  is not installable because it requires
       └─ scvi-tools >=0.20.1  but there are no viable options
          ├─ scvi-tools [0.20.1|0.20.2|0.20.3] would require
          │  └─ jaxlib >=0.3.0 , which does not exist (perhaps a missing channel);
          └─ scvi-tools [0.20.3|1.0.0|...|1.1.6] would require
             └─ jaxlib >=0.4.3 , which does not exist (perhaps a missing channel).
critical libmamba Could not solve for environment specs

scvelo==0.3.1 not available due to dependency on pytorch >=1.8.0

PS C:\Users\kevin> micromamba create -c conda-forge -c bioconda -n scvelo scvelo==0.3.1
conda-forge/win-64                                          Using cache
conda-forge/noarch                                          Using cache
bioconda/win-64                                             Using cache
bioconda/noarch                                             Using cache
error    libmamba Could not solve for environment specs
    The following package could not be installed
    └─ scvelo 0.3.1  is not installable because it requires
       └─ scvi-tools >=0.20.1 , which requires
          └─ pytorch >=1.8.0 , which does not exist (perhaps a missing channel).
critical libmamba Could not solve for environment specs

0.3.0 same

PS C:\Users\kevin> micromamba create -c conda-forge -c bioconda -n scvelo scvelo==0.3.0
conda-forge/win-64                                          Using cache
conda-forge/noarch                                          Using cache
bioconda/win-64                                             Using cache
bioconda/noarch                                             Using cache
error    libmamba Could not solve for environment specs
    The following package could not be installed
    └─ scvelo 0.3.0  is not installable because it requires
       └─ scvi-tools >=0.20.1 , which requires
          └─ pytorch >=1.8.0 , which does not exist (perhaps a missing channel).
critical libmamba Could not solve for environment specs
@kevinrue
Copy link
Owner Author 

PS C:\Users\kevin> micromamba search -c conda-forge -c bioconda scvelo
Getting repodata from channels...

conda-forge/win-64                                          Using cache
conda-forge/noarch                                          Using cache
bioconda/win-64                                             Using cache
bioconda/noarch                                             Using cache


       scvelo 0.3.2 pyhd8ed1ab_1
────────────────────────────────────────

 Name            scvelo
 Version         0.3.2
 Build           pyhd8ed1ab_1
 Size            154 kB
 License         BSD-3-Clause
 Subdir          noarch
 File Name       scvelo-0.3.2-pyhd8ed1ab_1.conda
 URL             https://conda.anaconda.org/conda-forge/noarch/scvelo-0.3.2-pyhd8ed1ab_1.conda
 MD5             3278754ad0ec23639df5d7751d2b885c
 SHA256          6b1ca684a3a2a9734c736e675ef04cd65b44bc20011ddaf852d118141a0a4f1b

 Dependencies:
  - python >=3.8
  - numpy >=1.17
  - scipy >=1.4.1
  - matplotlib-base >=3.3.0
  - anndata >=0.7.5
  - scvi-tools >=0.20.1
  - umap-learn >=0.3.10
  - numba >=0.41.0
  - loompy >=2.0.12
  - pandas >=1.1.1,!=1.4.0
  - scanpy >=1.5
  - scikit-learn >=0.21.2,<1.2.0

 Other Versions (9):

  Version Build
 ------------------------------------------
  0.3.1   pyhd8ed1ab_0        (+ 1 builds)
  0.3.0   pyhd8ed1ab_0
  ...     (5 hidden versions)          ...
  0.1.25  py_0
  0.1.24  py_0

@kevinrue
Copy link
Owner Author 

PS C:\Users\kevin> micromamba search -c bioconda  -c conda-forge --pretty --json scvelo
{
    "query": {
        "query": "scvelo",
        "type": "search"
    },
    "result": {
        "msg": "",
        "pkgs": [
            {
                "build": "pyhd8ed1ab_1",
                "build_number": 1,
                "build_string": "pyhd8ed1ab_1",
                "channel": "conda-forge",
                "constrains": [],
                "depends": [
                    "python >=3.8",
                    "numpy >=1.17",
                    "scipy >=1.4.1",
                    "matplotlib-base >=3.3.0",
                    "anndata >=0.7.5",
                    "scvi-tools >=0.20.1",
                    "umap-learn >=0.3.10",
                    "numba >=0.41.0",
                    "loompy >=2.0.12",
                    "pandas >=1.1.1,!=1.4.0",
                    "scanpy >=1.5",
                    "scikit-learn >=0.21.2,<1.2.0"
                ],
                "fn": "scvelo-0.3.2-pyhd8ed1ab_1.conda",
                "license": "BSD-3-Clause",
                "md5": "3278754ad0ec23639df5d7751d2b885c",
                "name": "scvelo",
                "sha256": "6b1ca684a3a2a9734c736e675ef04cd65b44bc20011ddaf852d118141a0a4f1b",
                "size": 154636,
                "subdir": "noarch",
                "timestamp": 1710771370,
                "track_features": "",
                "url": "https://conda.anaconda.org/conda-forge/noarch/scvelo-0.3.2-pyhd8ed1ab_1.conda",
                "version": "0.3.2"
            },
            {
                "build": "pyhd8ed1ab_0",
                "build_number": 0,
                "build_string": "pyhd8ed1ab_0",
                "channel": "conda-forge",
                "constrains": [],
                "depends": [
                    "python >=3.8",
                    "numpy >=1.17",
                    "scipy >=1.4.1",
                    "matplotlib-base >=3.3.0",
                    "anndata >=0.7.5",
                    "scvi-tools >=0.20.1",
                    "umap-learn >=0.3.10",
                    "numba >=0.41.0",
                    "loompy >=2.0.12",
                    "pandas >=1.1.1,!=1.4.0",
                    "scanpy >=1.5",
                    "scikit-learn >=0.21.2,<1.2.0",
                    "chex <=0.1.8"
                ],
                "fn": "scvelo-0.3.1-pyhd8ed1ab_0.conda",
                "license": "BSD-3-Clause",
                "md5": "ec4f74d6f9acb6d6f725146825a92603",
                "name": "scvelo",
                "sha256": "ec7edefda9fa51629da5eec43f339bade7447c7b4c70cc923112a0e2cb4f3226",
                "size": 154583,
                "subdir": "noarch",
                "timestamp": 1701626077,
                "track_features": "",
                "url": "https://conda.anaconda.org/conda-forge/noarch/scvelo-0.3.1-pyhd8ed1ab_0.conda",
                "version": "0.3.1"
            },
            {
                "build": "pyhd8ed1ab_1",
                "build_number": 1,
                "build_string": "pyhd8ed1ab_1",
                "channel": "conda-forge",
                "constrains": [],
                "depends": [
                    "python >=3.8",
                    "numpy >=1.17",
                    "scipy >=1.4.1",
                    "matplotlib-base >=3.3.0",
                    "anndata >=0.7.5",
                    "scvi-tools >=0.20.1",
                    "umap-learn >=0.3.10",
                    "numba >=0.41.0",
                    "loompy >=2.0.12",
                    "pandas >=1.1.1,!=1.4.0",
                    "scanpy >=1.5",
                    "scikit-learn >=0.21.2,<1.2.0"
                ],
                "fn": "scvelo-0.3.1-pyhd8ed1ab_1.conda",
                "license": "BSD-3-Clause",
                "md5": "159fd94be5c5a7653adce52a7c3c273b",
                "name": "scvelo",
                "sha256": "88719090d99ff3c8e672be6ed6a151a2500ee09c25869ae3d5677617abb4598c",
                "size": 154498,
                "subdir": "noarch",
                "timestamp": 1710768324,
                "track_features": "",
                "url": "https://conda.anaconda.org/conda-forge/noarch/scvelo-0.3.1-pyhd8ed1ab_1.conda",
                "version": "0.3.1"
            },
            {
                "build": "pyhd8ed1ab_0",
                "build_number": 0,
                "build_string": "pyhd8ed1ab_0",
                "channel": "conda-forge",
                "constrains": [],
                "depends": [
                    "python >=3.8",
                    "numpy >=1.17",
                    "scipy >=1.4.1",
                    "matplotlib-base >=3.3.0",
                    "anndata >=0.7.5",
                    "scvi-tools >=0.20.1",
                    "umap-learn >=0.3.10",
                    "numba >=0.41.0",
                    "loompy >=2.0.12",
                    "pandas >=1.1.1,!=1.4.0",
                    "scanpy >=1.5",
                    "scikit-learn >=0.21.2,<1.2.0",
                    "chex <=0.1.8"
                ],
                "fn": "scvelo-0.3.0-pyhd8ed1ab_0.conda",
                "license": "BSD-3-Clause",
                "md5": "71cd06a6a9ab2094b764e8fb381e5949",
                "name": "scvelo",
                "sha256": "ea75000ade4bf211290f60ad9b5110b42561f907d0fb2277b66cc1f1f16574a3",
                "size": 154915,
                "subdir": "noarch",
                "timestamp": 1701599909,
                "track_features": "",
                "url": "https://conda.anaconda.org/conda-forge/noarch/scvelo-0.3.0-pyhd8ed1ab_0.conda",
                "version": "0.3.0"
            },
            {
                "build": "pyhdfd78af_0",
                "build_number": 0,
                "build_string": "pyhdfd78af_0",
                "channel": "bioconda",
                "constrains": [],
                "depends": [
                    "typing_extensions",
                    "python >=3.6",
                    "scipy >=1.4.1",
                    "scikit-learn >=0.21.2",
                    "numpy >=1.17",
                    "matplotlib-base >=3.1.2",
                    "pandas >=0.23",
                    "umap-learn >=0.3.10",
                    "loompy >=2.0.12",
                    "scanpy >=1.5.0",
                    "anndata >=0.7.0"
                ],
                "fn": "scvelo-0.2.5-pyhdfd78af_0.tar.bz2",
                "license": "BSD",
                "md5": "62db1732a293d41dcc30512c0f25c0c9",
                "name": "scvelo",
                "sha256": "5f1d2dbdc9ae07e1521f5df74d19f2b3e42bd095416bbc7a2ad666b2166fd9d6",
                "size": 162719,
                "subdir": "noarch",
                "timestamp": 1668256668,
                "track_features": "",
                "url": "https://conda.anaconda.org/bioconda/noarch/scvelo-0.2.5-pyhdfd78af_0.tar.bz2",
                "version": "0.2.5"
            },
            {
                "build": "pyhd8ed1ab_0",
                "build_number": 0,
                "build_string": "pyhd8ed1ab_0",
                "channel": "conda-forge",
                "constrains": [],
                "depends": [
                    "python >=3.8",
                    "numpy >=1.17",
                    "scipy >=1.4.1",
                    "matplotlib-base >=3.3.0",
                    "scikit-learn >=0.21.2",
                    "anndata >=0.7.5",
                    "scvi-tools >=0.20.1",
                    "umap-learn >=0.3.10",
                    "numba >=0.41.0",
                    "loompy >=2.0.12",
                    "pandas >=1.1.1,!=1.4.0",
                    "scanpy >=1.5"
                ],
                "fn": "scvelo-0.2.5-pyhd8ed1ab_0.conda",
                "license": "BSD-3-Clause",
                "md5": "2c017fb2d3adec3c75a72e1208e657e6",
                "name": "scvelo",
                "sha256": "129d8b4c548ab0fc9a1755d1346dddec9d65b133d020f440190c1071033f1b3f",
                "size": 163065,
                "subdir": "noarch",
                "timestamp": 1687905294,
                "track_features": "",
                "url": "https://conda.anaconda.org/conda-forge/noarch/scvelo-0.2.5-pyhd8ed1ab_0.conda",
                "version": "0.2.5"
            },
            {
                "build": "pyhdfd78af_0",
                "build_number": 0,
                "build_string": "pyhdfd78af_0",
                "channel": "bioconda",
                "constrains": [],
                "depends": [
                    "typing_extensions",
                    "python >=3.6",
                    "scipy >=1.4.1",
                    "scikit-learn >=0.21.2",
                    "numpy >=1.17",
                    "matplotlib-base >=3.1.2",
                    "pandas >=0.23",
                    "umap-learn >=0.3.10",
                    "loompy >=2.0.12",
                    "scanpy >=1.5.0",
                    "anndata >=0.7.0"
                ],
                "fn": "scvelo-0.2.4-pyhdfd78af_0.tar.bz2",
                "license": "BSD",
                "md5": "87a426fa6b96f72e7f1d663b8ad6ef42",
                "name": "scvelo",
                "sha256": "82b6b5a1daa7337d3f3fee60fd73eee1e6c8927efb0b95cd96e486877b6e71bb",
                "size": 142405,
                "subdir": "noarch",
                "timestamp": 1629993199,
                "track_features": "",
                "url": "https://conda.anaconda.org/bioconda/noarch/scvelo-0.2.4-pyhdfd78af_0.tar.bz2",
                "version": "0.2.4"
            },
            {
                "build": "py_0",
                "build_number": 0,
                "build_string": "py_0",
                "channel": "bioconda",
                "constrains": [],
                "depends": [
                    "python >=3.6",
                    "scipy >=1.4.1",
                    "scikit-learn >=0.21.2",
                    "numpy >=1.17",
                    "matplotlib-base >=3.1.2",
                    "pandas >=0.23",
                    "umap-learn >=0.3.10",
                    "loompy >=2.0.12",
                    "scanpy >=1.5.0",
                    "anndata >=0.7.0"
                ],
                "fn": "scvelo-0.2.3-py_0.tar.bz2",
                "license": "BSD",
                "md5": "0140e880b4263f3300860f37606fc651",
                "name": "scvelo",
                "sha256": "1c05eeb5800d717a56374581c81c7731f4d8e57773d5d3ccd97f679f04ade238",
                "size": 131620,
                "subdir": "noarch",
                "timestamp": 1613161090,
                "track_features": "",
                "url": "https://conda.anaconda.org/bioconda/noarch/scvelo-0.2.3-py_0.tar.bz2",
                "version": "0.2.3"
            },
            {
                "build": "py_0",
                "build_number": 0,
                "build_string": "py_0",
                "channel": "bioconda",
                "constrains": [],
                "depends": [
                    "python >=3.6",
                    "scikit-learn >=0.21.2",
                    "numpy >=1.17",
                    "pandas >=0.23",
                    "scipy >=1.0",
                    "scanpy >=1.4",
                    "matplotlib-base >=2.2",
                    "loompy >=2.0.12",
                    "anndata >=0.6.18",
                    "umap-learn >=0.3"
                ],
                "fn": "scvelo-0.2.2-py_0.tar.bz2",
                "license": "BSD",
                "md5": "fab35b6ae67c234c9c71e16231912d51",
                "name": "scvelo",
                "sha256": "22941f52979ded1ca189fe53441f14df38f02a58b0a031edfe86f1db5758eb14",
                "size": 148437,
                "subdir": "noarch",
                "timestamp": 1595431214,
                "track_features": "",
                "url": "https://conda.anaconda.org/bioconda/noarch/scvelo-0.2.2-py_0.tar.bz2",
                "version": "0.2.2"
            },
            {
                "build": "py_1",
                "build_number": 1,
                "build_string": "py_1",
                "channel": "bioconda",
                "constrains": [],
                "depends": [
                    "python >=3.6",
                    "scipy >=1.4.1",
                    "scikit-learn >=0.21.2",
                    "numpy >=1.17",
                    "matplotlib-base >=3.1.2",
                    "pandas >=0.23",
                    "umap-learn >=0.3.10",
                    "loompy >=2.0.12",
                    "scanpy >=1.5.0",
                    "anndata >=0.7.0"
                ],
                "fn": "scvelo-0.2.2-py_1.tar.bz2",
                "license": "BSD",
                "md5": "519a192d15206e3aab84a6a8e704a8f9",
                "name": "scvelo",
                "sha256": "fba2fabeb37c055f87bfbbc241be7f7633116f5c3bcc1ba44fed64cb3b239ab0",
                "size": 148538,
                "subdir": "noarch",
                "timestamp": 1600339831,
                "track_features": "",
                "url": "https://conda.anaconda.org/bioconda/noarch/scvelo-0.2.2-py_1.tar.bz2",
                "version": "0.2.2"
            },
            {
                "build": "py_0",
                "build_number": 0,
                "build_string": "py_0",
                "channel": "bioconda",
                "constrains": [],
                "depends": [
                    "python >=3.6",
                    "scikit-learn >=0.21.2",
                    "numpy >=1.17",
                    "pandas >=0.23",
                    "scipy >=1.0",
                    "scanpy >=1.4",
                    "matplotlib-base >=2.2",
                    "loompy >=2.0.12",
                    "anndata >=0.6.18",
                    "umap-learn >=0.3"
                ],
                "fn": "scvelo-0.2.1-py_0.tar.bz2",
                "license": "BSD",
                "md5": "7a1fc0dd3ca1480ddb5af23f1852cb1a",
                "name": "scvelo",
                "sha256": "624b5ede408a3e5dde8463ec4e03e580504936fc8e68dc7fff47f1e4aff53074",
                "size": 142765,
                "subdir": "noarch",
                "timestamp": 1590941218,
                "track_features": "",
                "url": "https://conda.anaconda.org/bioconda/noarch/scvelo-0.2.1-py_0.tar.bz2",
                "version": "0.2.1"
            },
            {
                "build": "py_0",
                "build_number": 0,
                "build_string": "py_0",
                "channel": "bioconda",
                "constrains": [],
                "depends": [
                    "python >=3.6",
                    "scikit-learn >=0.21.2",
                    "numpy >=1.17",
                    "pandas >=0.23",
                    "scipy >=1.0",
                    "matplotlib >=2.2",
                    "scanpy >=1.4",
                    "loompy >=2.0.12",
                    "anndata >=0.6.18",
                    "umap-learn >=0.3"
                ],
                "fn": "scvelo-0.1.25-py_0.tar.bz2",
                "license": "BSD",
                "md5": "81d56e00882e9319025e8bf961743230",
                "name": "scvelo",
                "sha256": "d33115421226345945e404448b8fbc2887f47702b911311e97b1717f50fef924",
                "size": 116826,
                "subdir": "noarch",
                "timestamp": 1579857218,
                "track_features": "",
                "url": "https://conda.anaconda.org/bioconda/noarch/scvelo-0.1.25-py_0.tar.bz2",
                "version": "0.1.25"
            },
            {
                "build": "py_0",
                "build_number": 0,
                "build_string": "py_0",
                "channel": "bioconda",
                "constrains": [],
                "depends": [
                    "python >=3.6",
                    "scikit-learn >=0.21.2",
                    "numpy >=1.17",
                    "pandas >=0.23",
                    "scipy >=1.0",
                    "matplotlib >=2.2",
                    "scanpy >=1.4",
                    "loompy >=2.0.12",
                    "anndata >=0.6.18",
                    "umap-learn >=0.3"
                ],
                "fn": "scvelo-0.1.24-py_0.tar.bz2",
                "license": "BSD",
                "md5": "f094f57b510cc02e5c043c6cb208475e",
                "name": "scvelo",
                "sha256": "c0a4f855c4f2ebcd34becc57322852b6e3609c0824c628293a54ab8a8ee8fde0",
                "size": 105738,
                "subdir": "noarch",
                "timestamp": 1576221408,
                "track_features": "",
                "url": "https://conda.anaconda.org/bioconda/noarch/scvelo-0.1.24-py_0.tar.bz2",
                "version": "0.1.24"
            }
        ],
        "status": "OK"
    }
}

@kevinrue
Copy link
Owner Author

0.2.5 is resolved in whichever order bioconda and conda-forge channels are placed

However, conda-forge first gets everything but one package from conda-forge, which seems a bit better than 4-5 packages from bioconda if that one is first.

PS C:\Users\kevin> micromamba create -c conda-forge -c bioconda -n scvelo scvelo==0.2.5
conda-forge/win-64                                          Using cache
conda-forge/noarch                                          Using cache
bioconda/win-64                                             Using cache
bioconda/noarch                                             Using cache

Transaction

  Prefix: C:\Users\kevin\micromamba\envs\scvelo

  Updating specs:

   - scvelo==0.2.5


  Package                               Version  Build                    Channel           Size
--------------------------------------------------------------------------------------------------
  Install:
--------------------------------------------------------------------------------------------------

  + libexpat                              2.6.2  h63175ca_0               conda-forge     Cached
  + python_abi                             3.12  5_cp312                  conda-forge     Cached
  + ucrt                           10.0.22621.0  h57928b3_0               conda-forge     Cached
  + ca-certificates                    2024.7.4  h56e8100_0               conda-forge     Cached
  + intel-openmp                       2024.2.1  h57928b3_1083            conda-forge        2MB
  + msys2-conda-epoch                  20160418  1                        conda-forge     Cached
  + vc14_runtime                    14.40.33810  ha82c5b3_20              conda-forge     Cached
  + m2w64-libwinpthread-git  5.0.0.4634.697f757  2                        conda-forge     Cached
  + m2w64-gmp                             6.1.0  2                        conda-forge     Cached
  + vc                                     14.3  h8a93ad2_20              conda-forge     Cached
  + vs2015_runtime                  14.40.33810  h3bf8584_20              conda-forge     Cached
  + m2w64-gcc-libs-core                   5.3.0  7                        conda-forge     Cached
  + libiconv                               1.17  hcfcfb64_2               conda-forge     Cached
  + libbrotlicommon                       1.1.0  hcfcfb64_1               conda-forge     Cached
  + libaec                                1.1.3  h63175ca_0               conda-forge     Cached
  + libdeflate                             1.21  h2466b09_0               conda-forge     Cached
  + libjpeg-turbo                         3.0.0  hcfcfb64_1               conda-forge     Cached
  + pthreads-win32                        2.9.1  hfa6e2cd_3               conda-forge     Cached
  + qhull                                2020.2  hc790b64_5               conda-forge     Cached
  + libwebp-base                          1.4.0  hcfcfb64_0               conda-forge     Cached
  + tk                                   8.6.13  h5226925_1               conda-forge     Cached
  + openssl                               3.3.1  h2466b09_2               conda-forge     Cached
  + libzlib                               1.3.1  h2466b09_1               conda-forge     Cached
  + bzip2                                 1.0.8  h2466b09_7               conda-forge     Cached
  + libsqlite                            3.46.0  h2466b09_0               conda-forge     Cached
  + lerc                                  4.0.0  h63175ca_0               conda-forge     Cached
  + libffi                                3.4.2  h8ffe710_5               conda-forge     Cached
  + xz                                    5.2.6  h8d14728_0               conda-forge     Cached
  + m2w64-gcc-libgfortran                 5.3.0  6                        conda-forge     Cached
  + libbrotlienc                          1.1.0  hcfcfb64_1               conda-forge     Cached
  + libbrotlidec                          1.1.0  hcfcfb64_1               conda-forge     Cached
  + krb5                                 1.21.3  hdf4eb48_0               conda-forge     Cached
  + libssh2                              1.11.0  h7dfc565_0               conda-forge     Cached
  + zstd                                  1.5.6  h0ea2cb4_0               conda-forge     Cached
  + libxml2                              2.12.7  h0f24e4e_4               conda-forge     Cached
  + libpng                               1.6.43  h19919ed_0               conda-forge     Cached
  + m2w64-gcc-libs                        5.3.0  7                        conda-forge     Cached
  + brotli-bin                            1.1.0  hcfcfb64_1               conda-forge     Cached
  + libcurl                               8.9.1  h18fefc2_0               conda-forge     Cached
  + libtiff                               4.6.0  hb151862_4               conda-forge     Cached
  + libhwloc                             2.11.1  default_h8125262_1000    conda-forge     Cached
  + freetype                             2.12.1  hdaf720e_2               conda-forge     Cached
  + xorg-libxdmcp                         1.1.3  hcd874cb_0               conda-forge     Cached
  + pthread-stubs                           0.4  hcd874cb_1001            conda-forge     Cached
  + xorg-libxau                          1.0.11  hcd874cb_0               conda-forge     Cached
  + brotli                                1.1.0  hcfcfb64_1               conda-forge     Cached
  + hdf5                                 1.14.3  nompi_h2b43c12_105       conda-forge     Cached
  + openjpeg                              2.5.2  h3d672ee_0               conda-forge     Cached
  + lcms2                                  2.16  h67d730c_0               conda-forge     Cached
  + tbb                               2021.12.0  hc790b64_3               conda-forge     Cached
  + libxcb                                 1.16  hcd874cb_0               conda-forge     Cached
  + mkl                                2024.1.0  h66d3029_694             conda-forge      109MB
  + libblas                               3.9.0  23_win64_mkl             conda-forge        5MB
  + libcblas                              3.9.0  23_win64_mkl             conda-forge        5MB
  + liblapack                             3.9.0  23_win64_mkl             conda-forge        5MB
  + tzdata                                2024a  h0c530f3_0               conda-forge     Cached
  + python                               3.12.5  h889d299_0_cpython       conda-forge     Cached
  + wheel                                0.44.0  pyhd8ed1ab_0             conda-forge     Cached
  + setuptools                           72.2.0  pyhd8ed1ab_0             conda-forge     Cached
  + pip                                    24.2  pyhd8ed1ab_0             conda-forge     Cached
  + cached_property                       1.5.2  pyha770c72_1             conda-forge     Cached
  + colorama                              0.4.6  pyhd8ed1ab_0             conda-forge     Cached
  + munkres                               1.1.4  pyh9f0ad1d_0             conda-forge       12kB
  + pyparsing                             3.1.2  pyhd8ed1ab_0             conda-forge     Cached
  + cycler                               0.12.1  pyhd8ed1ab_0             conda-forge     Cached
  + certifi                            2024.7.4  pyhd8ed1ab_0             conda-forge     Cached
  + pytz                                 2024.1  pyhd8ed1ab_0             conda-forge     Cached
  + python-tzdata                        2024.1  pyhd8ed1ab_0             conda-forge     Cached
  + threadpoolctl                         3.5.0  pyhc1e730c_0             conda-forge     Cached
  + stdlib-list                          0.10.0  pyhd8ed1ab_0             conda-forge     Cached
  + array-api-compat                        1.8  pyhd8ed1ab_0             conda-forge     Cached
  + exceptiongroup                        1.2.2  pyhd8ed1ab_0             conda-forge     Cached
  + six                                  1.16.0  pyh6c4a22f_0             conda-forge     Cached
  + legacy-api-wrap                         1.4  pyhd8ed1ab_1             conda-forge     Cached
  + packaging                              24.1  pyhd8ed1ab_0             conda-forge     Cached
  + networkx                                3.3  pyhd8ed1ab_1             conda-forge     Cached
  + natsort                               8.4.0  pyhd8ed1ab_0             conda-forge     Cached
  + joblib                                1.4.2  pyhd8ed1ab_0             conda-forge     Cached
  + get-annotations                       0.1.2  pyhd8ed1ab_0             conda-forge       10kB
  + typing_extensions                    4.12.2  pyha770c72_0             conda-forge     Cached
  + cached-property                       1.5.2  hd8ed1ab_1               conda-forge     Cached
  + click                                 8.1.7  win_pyh7428d3b_0         conda-forge       85kB
  + tqdm                                 4.66.5  pyhd8ed1ab_0             conda-forge     Cached
  + session-info                          1.0.0  pyhd8ed1ab_0             conda-forge       12kB
  + python-dateutil                       2.9.0  pyhd8ed1ab_0             conda-forge     Cached
  + pillow                               10.4.0  py312h381445a_0          conda-forge     Cached
  + numpy                                1.26.4  py312h8753938_0          conda-forge        6MB
  + llvmlite                             0.43.0  py312h1f7db74_0          conda-forge     Cached
  + kiwisolver                            1.4.5  py312h0d7def4_1          conda-forge     Cached
  + fonttools                            4.53.1  py312h4389bb4_0          conda-forge     Cached
  + contourpy                             1.2.1  py312h0d7def4_0          conda-forge     Cached
  + pandas                                2.2.2  py312h72972c8_1          conda-forge     Cached
  + h5py                                 3.11.0  nompi_py312ha036244_102  conda-forge     Cached
  + scipy                                1.14.1  py312h1f4e10d_0          conda-forge     Cached
  + numba                                0.60.0  py312hcccf92d_0          conda-forge     Cached
  + matplotlib-base                       3.9.2  py312h90004f6_0          conda-forge     Cached
  + scikit-learn                          1.5.1  py312h816cc57_0          conda-forge     Cached
  + numpy_groupies                       0.11.2  pyhd8ed1ab_0             conda-forge       37kB
  + patsy                                 0.5.6  pyhd8ed1ab_0             conda-forge     Cached
  + anndata                              0.10.8  pyhd8ed1ab_0             conda-forge     Cached
  + seaborn-base                         0.13.2  pyhd8ed1ab_2             conda-forge     Cached
  + pynndescent                          0.5.13  pyhff2d567_0             conda-forge     Cached
  + loompy                                3.0.6  py_0                     conda-forge       41kB
  + statsmodels                          0.14.2  py312h1a27103_0          conda-forge     Cached
  + umap-learn                            0.5.6  py312h2e8e312_1          conda-forge     Cached
  + seaborn                              0.13.2  hd8ed1ab_2               conda-forge     Cached
  + scanpy                               1.10.2  pyhd8ed1ab_0             conda-forge        2MB
  + scvelo                                0.2.5  pyhdfd78af_0             bioconda        Cached

  Summary:

  Install: 108 packages

  Total download: 135MB

--------------------------------------------------------------------------------------------------


Confirm changes: [Y/n]

@kevinrue
Copy link
Owner Author

kevinrue commented Aug 23, 2024 •
edited
Loading

Sad face

The latest environment above leads to the error

Downloading and Extracting Packages: ...working... done
Preparing transaction: ...working... done
Verifying transaction: ...working... done
Executing transaction: ...working... done
Error in py_module_import(module, convert = convert) : 
  AttributeError: module 'matplotlib.cbook' has no attribute 'mplDeprecation'
Run `reticulate::py_last_error()` for details.
Error in .activate_fallback(proc, testload, env = env, envpath = envpath,  : 
  AttributeError: module 'matplotlib.cbook' has no attribute 'mplDeprecation'
Run `reticulate::py_last_error()` for details.

Which seems to occur during the installation of the environment, before scvelo is even run.

Fix seems to be matplotlib <= 3.7.3

https://stackoverflow.com/questions/77128061/ydata-profiling-profilereport-attributeerror-module-matplotlib-cbook-has-no

No luck:

(scvelo) PS C:\Users\kevin> micromamba install -c conda-forge -c bioconda  -n scvelo scvelo==0.2.5 matplotlib==3.7.3
conda-forge/win-64                                          Using cache
conda-forge/noarch                                          Using cache
bioconda/win-64                                             Using cache
bioconda/noarch                                             Using cache

Pinned packages:
  - python 3.12.*

error    libmamba Could not solve for environment specs
    The following packages are incompatible
    ├─ matplotlib 3.7.3  is installable with the potential options
    │  ├─ matplotlib 3.7.3 would require
    │  │  └─ python >=3.10,<3.11.0a0 , which can be installed;
    │  ├─ matplotlib 3.7.3 would require
    │  │  └─ python >=3.11,<3.12.0a0 , which can be installed;
    │  ├─ matplotlib 3.7.3 would require
    │  │  └─ python >=3.8,<3.9.0a0 , which can be installed;
    │  └─ matplotlib 3.7.3 would require
    │     └─ python >=3.9,<3.10.0a0 , which can be installed;
    └─ pin-1 is not installable because it requires
       └─ python 3.12.* , which conflicts with any installable versions previously reported.
critical libmamba Could not solve for environment specs

This seems to help:
theislab/scvelo#1124 (comment)

Namely:

(scvelo) PS C:\Users\kevin> micromamba install -c conda-forge -c bioconda  -n scvelo scvelo==0.2.5 matplotlib==3.7.2 python==3.8
conda-forge/win-64                                          Using cache
conda-forge/noarch                                          Using cache
bioconda/win-64                                             Using cache
bioconda/noarch                                             Using cache

Transaction

  Prefix: C:\Users\kevin\micromamba\envs\scvelo

  Updating specs:

   - scvelo==0.2.5
   - matplotlib==3.7.2
   - python==3.8


  Package                 Version  Build                    Channel           Size
------------------------------------------------------------------------------------
  Install:
------------------------------------------------------------------------------------

  + icu                      70.1  h0e60522_0               conda-forge       18MB
  + sqlite                 3.46.0  h2466b09_0               conda-forge      886kB
  + jpeg                       9e  h8ffe710_2               conda-forge      375kB
  + libintl                0.22.5  h5728263_3               conda-forge       96kB
  + libasprintf            0.22.5  h5728263_3               conda-forge       50kB
  + libogg                  1.3.5  h2466b09_0               conda-forge       35kB
  + libclang13             15.0.7  default_hf64faad_5       conda-forge       22MB
  + pcre2                   10.43  h17e33f8_0               conda-forge      818kB
  + zlib                   1.2.13  h2466b09_6               conda-forge      108kB
  + libgettextpo           0.22.5  h5728263_3               conda-forge      171kB
  + gettext-tools          0.22.5  h5a7288d_3               conda-forge        3MB
  + libintl-devel          0.22.5  h5728263_3               conda-forge       41kB
  + libasprintf-devel      0.22.5  h5728263_3               conda-forge       36kB
  + libvorbis               1.3.7  h0e60522_0               conda-forge      274kB
  + libglib                2.80.2  h0df6a38_0               conda-forge        4MB
  + libclang               15.0.7  default_h3a3e6c3_5       conda-forge      148kB
  + libgettextpo-devel     0.22.5  h5728263_3               conda-forge       40kB
  + glib-tools             2.80.2  h2f9d560_0               conda-forge       95kB
  + gettext                0.22.5  h5728263_3               conda-forge       34kB
  + hyperframe              6.0.1  pyhd8ed1ab_0             conda-forge       15kB
  + hpack                   4.0.0  pyh9f0ad1d_0             conda-forge       25kB
  + pycparser                2.22  pyhd8ed1ab_0             conda-forge      105kB
  + win_inet_pton           1.1.0  pyhd8ed1ab_6             conda-forge        8kB
  + charset-normalizer      3.3.2  pyhd8ed1ab_0             conda-forge       47kB
  + idna                      3.7  pyhd8ed1ab_0             conda-forge       53kB
  + tomli                   2.0.1  pyhd8ed1ab_0             conda-forge     Cached
  + ply                      3.11  pyhd8ed1ab_2             conda-forge       49kB
  + zipp                   3.20.0  pyhd8ed1ab_0             conda-forge     Cached
  + platformdirs            4.2.2  pyhd8ed1ab_0             conda-forge       21kB
  + olefile                  0.47  pyhd8ed1ab_0             conda-forge       39kB
  + toml                   0.10.2  pyhd8ed1ab_0             conda-forge       18kB
  + h2                      4.1.0  pyhd8ed1ab_0             conda-forge       47kB
  + pysocks                 1.7.1  pyh0701188_6             conda-forge       19kB
  + importlib_resources     6.4.4  pyhd8ed1ab_0             conda-forge       32kB
  + importlib-metadata      8.4.0  pyha770c72_0             conda-forge     Cached
  + importlib-resources     6.4.4  pyhd8ed1ab_0             conda-forge        9kB
  + glib                   2.80.2  h0df6a38_0               conda-forge      571kB
  + gstreamer              1.21.3  h6b5321d_1               conda-forge        2MB
  + cffi                   1.17.0  py38h4cb3324_0           conda-forge      236kB
  + brotli-python           1.1.0  py38hd3f51b4_1           conda-forge      322kB
  + unicodedata2           15.1.0  py38h91455d4_0           conda-forge      371kB
  + tornado                 6.4.1  py38h4cb3324_0           conda-forge      645kB
  + sip                    6.7.12  py38hd3f51b4_0           conda-forge      501kB
  + gst-plugins-base       1.21.3  h001b923_1               conda-forge        2MB
  + zstandard              0.23.0  py38hf92978b_0           conda-forge      311kB
  + pyqt5-sip             12.11.0  py38hd3f51b4_3           conda-forge       79kB
  + qt-main                5.15.6  h068e40c_6               conda-forge       62MB
  + pyqt                   5.15.7  py38hd6c051e_3           conda-forge        4MB
  + matplotlib              3.7.2  py38haa244fe_0           conda-forge        9kB
  + urllib3                 2.2.2  pyhd8ed1ab_1             conda-forge       95kB
  + requests               2.32.3  pyhd8ed1ab_0             conda-forge       59kB
  + pooch                   1.8.2  pyhd8ed1ab_0             conda-forge       54kB

  Change:
------------------------------------------------------------------------------------

  - libxml2                2.12.7  h0f24e4e_4               conda-forge     Cached
  + libxml2                2.12.7  h283a6d9_1               conda-forge        2MB
  - kiwisolver              1.4.5  py312h0d7def4_1          conda-forge     Cached
  + kiwisolver              1.4.5  py38hb1fd069_1           conda-forge       56kB
  - fonttools              4.53.1  py312h4389bb4_0          conda-forge     Cached
  + fonttools              4.53.1  py38h4cb3324_0           conda-forge        2MB
  - umap-learn              0.5.6  py312h2e8e312_1          conda-forge     Cached
  + umap-learn              0.5.6  py38haa244fe_1           conda-forge      138kB

  Reinstall:
------------------------------------------------------------------------------------

  o wheel                  0.44.0  pyhd8ed1ab_0             conda-forge     Cached
  o setuptools             72.2.0  pyhd8ed1ab_0             conda-forge     Cached
  o pip                      24.2  pyhd8ed1ab_0             conda-forge     Cached
  o typing_extensions      4.12.2  pyha770c72_0             conda-forge     Cached
  o threadpoolctl           3.5.0  pyhc1e730c_0             conda-forge     Cached
  o stdlib-list            0.10.0  pyhd8ed1ab_0             conda-forge     Cached
  o six                    1.16.0  pyh6c4a22f_0             conda-forge     Cached
  o pytz                   2024.1  pyhd8ed1ab_0             conda-forge     Cached
  o python-tzdata          2024.1  pyhd8ed1ab_0             conda-forge     Cached
  o packaging                24.1  pyhd8ed1ab_0             conda-forge     Cached
  o natsort                 8.4.0  pyhd8ed1ab_0             conda-forge     Cached
  o munkres                 1.1.4  pyh9f0ad1d_0             conda-forge     Cached
  o legacy-api-wrap           1.4  pyhd8ed1ab_1             conda-forge     Cached
  o joblib                  1.4.2  pyhd8ed1ab_0             conda-forge     Cached
  o get-annotations         0.1.2  pyhd8ed1ab_0             conda-forge     Cached
  o exceptiongroup          1.2.2  pyhd8ed1ab_0             conda-forge     Cached
  o cycler                 0.12.1  pyhd8ed1ab_0             conda-forge     Cached
  o colorama                0.4.6  pyhd8ed1ab_0             conda-forge     Cached
  o certifi              2024.7.4  pyhd8ed1ab_0             conda-forge     Cached
  o cached_property         1.5.2  pyha770c72_1             conda-forge     Cached
  o array-api-compat          1.8  pyhd8ed1ab_0             conda-forge     Cached
  o session-info            1.0.0  pyhd8ed1ab_0             conda-forge     Cached
  o python-dateutil         2.9.0  pyhd8ed1ab_0             conda-forge     Cached
  o tqdm                   4.66.5  pyhd8ed1ab_0             conda-forge     Cached
  o click                   8.1.7  win_pyh7428d3b_0         conda-forge     Cached
  o cached-property         1.5.2  hd8ed1ab_1               conda-forge     Cached
  o patsy                   0.5.6  pyhd8ed1ab_0             conda-forge     Cached
  o seaborn-base           0.13.2  pyhd8ed1ab_2             conda-forge     Cached
  o loompy                  3.0.6  py_0                     conda-forge     Cached
  o pynndescent            0.5.13  pyhff2d567_0             conda-forge     Cached
  o seaborn                0.13.2  hd8ed1ab_2               conda-forge     Cached
  o scanpy                 1.10.2  pyhd8ed1ab_0             conda-forge     Cached
  o scvelo                  0.2.5  pyhdfd78af_0             bioconda        Cached

  Downgrade:
------------------------------------------------------------------------------------

  - libzlib                 1.3.1  h2466b09_1               conda-forge     Cached
  + libzlib                1.2.13  h2466b09_6               conda-forge       56kB
  - openssl                 3.3.1  h2466b09_2               conda-forge     Cached
  + openssl                1.1.1w  hcfcfb64_0               conda-forge        5MB
  - libjpeg-turbo           3.0.0  hcfcfb64_1               conda-forge     Cached
  + libjpeg-turbo           2.1.4  hcfcfb64_0               conda-forge        1MB
  - libssh2                1.11.0  h7dfc565_0               conda-forge     Cached
  + libssh2                1.10.0  h680486a_3               conda-forge      233kB
  - krb5                   1.21.3  hdf4eb48_0               conda-forge     Cached
  + krb5                   1.20.1  h6609f42_0               conda-forge      715kB
  - python                 3.12.5  h889d299_0_cpython       conda-forge     Cached
  + python                  3.8.0  hc9e8b01_5               conda-forge       20MB
  - libtiff                 4.6.0  hb151862_4               conda-forge     Cached
  + libtiff                 4.2.0  h0c97f57_3               conda-forge        1MB
  - libcurl                 8.9.1  h18fefc2_0               conda-forge     Cached
  + libcurl                 8.1.2  h68f0423_0               conda-forge      313kB
  - lcms2                    2.16  h67d730c_0               conda-forge     Cached
  + lcms2                    2.12  h2a16943_0               conda-forge      903kB
  - openjpeg                2.5.2  h3d672ee_0               conda-forge     Cached
  + openjpeg                2.4.0  hb211442_1               conda-forge      243kB
  - hdf5                   1.14.3  nompi_h2b43c12_105       conda-forge     Cached
  + hdf5                   1.14.0  nompi_h97a5375_103       conda-forge        2MB
  - pyparsing               3.1.2  pyhd8ed1ab_0             conda-forge     Cached
  + pyparsing               3.0.9  pyhd8ed1ab_0             conda-forge       81kB
  - networkx                  3.3  pyhd8ed1ab_1             conda-forge     Cached
  + networkx                  3.1  pyhd8ed1ab_0             conda-forge        1MB
  - python_abi               3.12  5_cp312                  conda-forge     Cached
  + python_abi                3.8  2_cp38                   conda-forge        5kB
  - pillow                 10.4.0  py312h381445a_0          conda-forge     Cached
  + pillow                  8.2.0  py38h9273828_1           conda-forge      793kB
  - numpy                  1.26.4  py312h8753938_0          conda-forge     Cached
  + numpy                  1.24.4  py38h1d91fd2_0           conda-forge        6MB
  - llvmlite               0.43.0  py312h1f7db74_0          conda-forge     Cached
  + llvmlite               0.41.1  py38h19421c1_0           conda-forge       17MB
  - h5py                   3.11.0  nompi_py312ha036244_102  conda-forge     Cached
  + h5py                    3.9.0  nompi_py38h4f44683_100   conda-forge      889kB
  - contourpy               1.2.1  py312h0d7def4_0          conda-forge     Cached
  + contourpy               1.1.1  py38hb1fd069_1           conda-forge      174kB
  - pandas                  2.2.2  py312h72972c8_1          conda-forge     Cached
  + pandas                  2.0.3  py38hf08cf0d_1           conda-forge       11MB
  - numba                  0.60.0  py312hcccf92d_0          conda-forge     Cached
  + numba                  0.58.1  py38h4a59444_0           conda-forge        4MB
  - matplotlib-base         3.9.2  py312h90004f6_0          conda-forge     Cached
  + matplotlib-base         3.7.2  py38h2d9580e_0           conda-forge        7MB
  - numpy_groupies         0.11.2  pyhd8ed1ab_0             conda-forge     Cached
  + numpy_groupies         0.9.22  pyhd8ed1ab_0             conda-forge       27kB
  - scipy                  1.14.1  py312h1f4e10d_0          conda-forge     Cached
  + scipy                  1.10.1  py38h1aea9ed_3           conda-forge       18MB
  - statsmodels            0.14.2  py312h1a27103_0          conda-forge     Cached
  + statsmodels            0.14.1  py38he7056a7_0           conda-forge       10MB
  - scikit-learn            1.5.1  py312h816cc57_0          conda-forge     Cached
  + scikit-learn            1.3.2  py38h4f736e5_2           conda-forge        7MB
  - anndata                0.10.8  pyhd8ed1ab_0             conda-forge     Cached
  + anndata                 0.9.2  pyhd8ed1ab_0             conda-forge       87kB

  Summary:

  Install: 52 packages
  Change: 4 packages
  Reinstall: 33 packages
  Downgrade: 27 packages

  Total download: 244MB

------------------------------------------------------------------------------------


Confirm changes: [Y/n]

Note: from the current man page of ?scvelo

scVelo v0.2.5 from bioconda is used. Later versions of scVelo depend on jaxlib which is not supported on Windows (jax-ml/jax#438). Note that matplotlib is pinned to v3.6.3 (scverse/scanpy#2411), pandas is pinned to v1.5.2 (https://stackoverflow.com/questions/76234312/importerror-cannot-import-name-is-categorical-from-pandas-api-types), and numpy is pinned to v1.21.1 (theislab/scvelo#1109).

@kevinrue
Copy link
Owner Author

Latest environment seems to have issue with from ._core.anndata import AnnData

> reticulate::py_last_error()

── Python Exception Message ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Traceback (most recent call last):
  File "C:\Users\kevin\AppData\Local\R\cache\R\renv\library\velociraptor-96ea9712\windows\R-4.4\x86_64-w64-mingw32\reticulate\python\rpytools\loader.py", line 122, in _find_and_load_hook
    return _run_hook(name, _hook)
  File "C:\Users\kevin\AppData\Local\R\cache\R\renv\library\velociraptor-96ea9712\windows\R-4.4\x86_64-w64-mingw32\reticulate\python\rpytools\loader.py", line 96, in _run_hook
    module = hook()
  File "C:\Users\kevin\AppData\Local\R\cache\R\renv\library\velociraptor-96ea9712\windows\R-4.4\x86_64-w64-mingw32\reticulate\python\rpytools\loader.py", line 120, in _hook
    return _find_and_load(name, import_)
  File "C:\Users\kevin\BASILI~1\117~1.2\VELOCI~1\115~1.6\env\lib\site-packages\scvelo\__init__.py", line 2, in <module>
    from anndata import AnnData
  File "C:\Users\kevin\AppData\Local\R\cache\R\renv\library\velociraptor-96ea9712\windows\R-4.4\x86_64-w64-mingw32\reticulate\python\rpytools\loader.py", line 122, in _find_and_load_hook
    return _run_hook(name, _hook)
  File "C:\Users\kevin\AppData\Local\R\cache\R\renv\library\velociraptor-96ea9712\windows\R-4.4\x86_64-w64-mingw32\reticulate\python\rpytools\loader.py", line 96, in _run_hook
    module = hook()
  File "C:\Users\kevin\AppData\Local\R\cache\R\renv\library\velociraptor-96ea9712\windows\R-4.4\x86_64-w64-mingw32\reticulate\python\rpytools\loader.py", line 120, in _hook
    return _find_and_load(name, import_)
  File "C:\Users\kevin\BASILI~1\117~1.2\VELOCI~1\115~1.6\env\lib\site-packages\anndata\__init__.py", line 7, in <module>
    from ._core.anndata import AnnData
  File "C:\Users\kevin\AppData\Local\R\cache\R\renv\library\velociraptor-96ea9712\windows\R-4.4\x86_64-w64-mingw32\reticulate\python\rpytools\loader.py", line 122, in _find_and_load_hook
    return _run_hook(name, _hook)
  File "C:\Users\kevin\AppData\Local\R\cache\R\renv\library\velociraptor-96ea9712\windows\R-4.4\x86_64-w64-mingw32\reticulate\python\rpytools\loader.py", line 96, in _run_hook
    module = hook()
  File "C:\Users\kevin\AppData\Local\R\cache\R\renv\library\velociraptor-96ea9712\windows\R-4.4\x86_64-w64-mingw32\reticulate\python\rpytools\loader.py", line 120, in _hook
    return _find_and_load(name, import_)
  File "C:\Users\kevin\BASILI~1\117~1.2\VELOCI~1\115~1.6\env\lib\site-packages\anndata\_core\anndata.py", line 17, in <module>
    import h5py
  File "C:\Users\kevin\AppData\Local\R\cache\R\renv\library\velociraptor-96ea9712\windows\R-4.4\x86_64-w64-mingw32\reticulate\python\rpytools\loader.py", line 122, in _find_and_load_hook
    return _run_hook(name, _hook)
  File "C:\Users\kevin\AppData\Local\R\cache\R\renv\library\velociraptor-96ea9712\windows\R-4.4\x86_64-w64-mingw32\reticulate\python\rpytools\loader.py", line 96, in _run_hook
    module = hook()
  File "C:\Users\kevin\AppData\Local\R\cache\R\renv\library\velociraptor-96ea9712\windows\R-4.4\x86_64-w64-mingw32\reticulate\python\rpytools\loader.py", line 120, in _hook
    return _find_and_load(name, import_)
  File "C:\Users\kevin\BASILI~1\117~1.2\VELOCI~1\115~1.6\env\lib\site-packages\h5py\__init__.py", line 25, in <module>
    from . import _errors
  File "C:\Users\kevin\AppData\Local\R\cache\R\renv\library\velociraptor-96ea9712\windows\R-4.4\x86_64-w64-mingw32\reticulate\python\rpytools\loader.py", line 122, in _find_and_load_hook
    return _run_hook(name, _hook)
  File "C:\Users\kevin\AppData\Local\R\cache\R\renv\library\velociraptor-96ea9712\windows\R-4.4\x86_64-w64-mingw32\reticulate\python\rpytools\loader.py", line 96, in _run_hook
    module = hook()
  File "C:\Users\kevin\AppData\Local\R\cache\R\renv\library\velociraptor-96ea9712\windows\R-4.4\x86_64-w64-mingw32\reticulate\python\rpytools\loader.py", line 120, in _hook
    return _find_and_load(name, import_)
ImportError: DLL load failed while importing _errors: The specified module could not be found.

── R Traceback ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
     ▆
  1. ├─velociraptor::scvelo(list(X = spliced, spliced = spliced, unspliced = unspliced))
  2. └─velociraptor::scvelo(list(X = spliced, spliced = spliced, unspliced = unspliced)) at velociraptor/R/scvelo.R:286:22
  3.   └─velociraptor (local) .local(x, ...)
  4.     └─basilisk::basiliskRun(...) at velociraptor/R/scvelo.R:200:5
  5.       └─basilisk::basiliskStart(...)
  6.         └─basilisk:::.activate_fallback(...)
  7.           ├─base::try(...)
  8.           │ └─base::tryCatch(...)
  9.           │   └─base (local) tryCatchList(expr, classes, parentenv, handlers)
 10.           │     └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
 11.           │       └─base (local) doTryCatch(return(expr), name, parentenv, handler)
 12.           └─basilisk::basiliskRun(...)
 13.             └─basilisk (local) fun(...)
 14.               └─reticulate::import(pkg)
 15.                 └─reticulate:::py_module_import(module, convert = convert)
See `reticulate::py_last_error()$r_trace$full_call` for more details.

@kevinrue
Copy link
Owner Author

Did I run into this one yet?

 micromamba.bat env create -n scvelo_condaforge -c conda-forge -c bioconda scvelo==0.3.2
conda-forge/win-64                                          Using cache
conda-forge/noarch                                          Using cache
bioconda/win-64                                             Using cache
bioconda/noarch                                             Using cache
error    libmamba Could not solve for environment specs
    The following package could not be installed
    └─ scvelo 0.3.2  is not installable because it requires
       └─ scvi-tools >=0.20.1 , which requires
          └─ pytorch >=1.8.0 , which does not exist (perhaps a missing channel).

@kevinrue
Copy link
Owner Author

kevinrue commented Aug 30, 2024 •
edited
Loading

This seems to install properly

micromamba env create -n scvelo -c conda-forge -c bioconda scvelo==0.2.5 matplotlib==3.7.3

EDIT: Ran into error

Quitting from lines 76-82 [unnamed-chunk-5] (velociraptor.Rmd)
Error: processing vignette 'velociraptor.Rmd' failed with diagnostics:
argument is of length zero
--- failed re-building 'velociraptor.Rmd'

Seems related to theislab/scvelo#811

@kevinrue
Copy link
Owner Author

Trying

micromamba env create -n scvelo -c conda-forge -c bioconda scvelo==0.2.5 matplotlib==3.7.3 pandas==1.3.5

@kevinrue
Copy link
Owner Author

kevinrue commented Aug 30, 2024 •
edited
Loading

Trying

micromamba env create -n scvelo -c bioconda -c conda-forge scvelo==0.2.5 matplotlib==3.6.3 pandas==1.5.2 numpy==1.21.1 scipy==1.13.1

Impossible

error    libmamba Could not solve for environment specs
    The following packages are incompatible
    ├─ numpy 1.21.1  is requested and can be installed;
    └─ scipy 1.13.1  is not installable because it requires
       └─ numpy >=1.22.4,<2.3  but there are no viable options
          ├─ numpy [1.22.4|1.23.0|...|2.1.0] conflicts with any installable versions previously reported;
          └─ numpy [2.0.0rc1|2.0.0rc2|2.1.0rc1] would require
             └─ _numpy_rc, which does not exist (perhaps a missing channel).
critical libmamba Could not solve for environment specs

@kevinrue
Copy link
Owner Author

kevinrue commented Aug 30, 2024 •
edited
Loading

Trying

micromamba env create -n scvelo -c bioconda -c conda-forge scvelo==0.2.5 matplotlib==3.6.3 pandas==1.5.2 scipy==1.13.1

(removed numpy requirement)

EDIT: Ran back into error above

kevinrue added a commit that referenced this issue Aug 30, 2024
@kevinrue
https://github.com/kevinrue/velociraptor/issues/80#issuecomment-23204…
17afe4f 
…54366
@kevinrue
Copy link
Owner Author

Trying

micromamba env create -n scvelo -c bioconda -c conda-forge scvelo==0.2.5 python=3.8 matplotlib=3.7.2 jinja2=3.0.3

Source: theislab/scvelo#1124 (comment)

@kevinrue
Copy link
Owner Author

Back to error

TypeError: metaclass conflict: the metaclass of a derived class must be a (non-strict) subclass of the metaclasses of all its bases

Meaning back to matplotlib 3.6.3

micromamba env create -n scvelo -c bioconda -c conda-forge scvelo==0.2.5 python=3.8 matplotlib=3.6.3 jinja2=3.0.3

@kevinrue
Copy link
Owner Author

Back to error

ImportError: cannot import name 'is_categorical' from 'pandas.api.types' (C:\Users\kevin\BASILI1\1171.2\VELOCI1\1151.13\env\lib\site-packages\pandas\api\types_init_.py)

Meaning back to pandas 1.5.2

micromamba env create -n scvelo -c bioconda -c conda-forge scvelo==0.2.5 python=3.8 matplotlib=3.6.3  pandas==1.5.2 jinja2=3.0.3

@kevinrue
Copy link
Owner Author

Back to error

Error in py_call_impl(callable, call_args$unnamed, call_args$named) :
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 2 dimensions. The detected shape was (1, 4) + inhomogeneous part.

Back to numpy 1.21.1

micromamba env create -n scvelo -c bioconda -c conda-forge scvelo==0.2.5 python=3.8 matplotlib=3.6.3  pandas==1.5.2 numpy==1.21.1 jinja2=3.0.3

kevinrue added a commit that referenced this issue Aug 30, 2024
@kevinrue
Fix conda environment using micromamba for windows (#82)
71cca08 
* update environment for windows using micromamba

* try Windows environment resolved using micromamba

* add pip dependencies

* downgrade matplotlib to 3.7.3 (https://stackoverflow.com/questions/77128061/ydata-profiling-profilereport-attributeerror-module-matplotlib-cbook-has-no)

* downgrade pandas (theislab/scvelo#811 (comment))

* remove pip section

* #80 (comment)

* woops updated env in R code too

* downgrade python (theislab/scvelo#1124 (comment))

* matplotlib 3.6.3

* pandas 1.5.2

* numpy 1.21.1

* fix version bump

* remove useless pip

---------

Co-authored-by: Kevin Rue <kevinrue@users.noreply.github.com>
@kevinrue
Copy link
Owner Author

Hurray! Fixed by #82

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
None yet
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
1 participant
@kevinrue