Multiple platform build/check report for BioC 3.20 - CHECK results for immApex on taishan

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo2	Linux (Ubuntu 24.04.1 LTS)	x86_64	4.4.3 (2025-02-28) -- "Trophy Case"	4670
palomino8	Windows Server 2022 Datacenter	x64	4.4.3 (2025-02-28 ucrt) -- "Trophy Case"	4355
merida1	macOS 12.7.5 Monterey	x86_64	4.4.3 (2025-02-28) -- "Trophy Case"	4446
kjohnson1	macOS 13.6.6 Ventura	arm64	4.4.3 (2025-02-28) -- "Trophy Case"	4439
taishan	Linux (openEuler 24.03 LTS)	aarch64	4.4.3 (2025-02-28) -- "Trophy Case"	4306
Click on any hostname to see more info about the system (e.g. compilers) () as reported by 'uname -p', except on Windows and Mac OS X*

CHECK results for immApex on taishan

To the developers/maintainers of the immApex package:
- Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/immApex.git to reflect on this report. See Troubleshooting Build Report for more information.
- Use the following Renviron settings to reproduce errors and warnings.
- If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information.
- See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host.

raw results

Summary

Package: immApex

Version: 1.0.5

Command: /home/biocbuild/R/R/bin/R CMD check --install=check:immApex.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings immApex_1.0.5.tar.gz

StartedAt: 2025-03-07 07:54:31 -0000 (Fri, 07 Mar 2025)

EndedAt: 2025-03-07 08:02:40 -0000 (Fri, 07 Mar 2025)

EllapsedTime: 489.5 seconds

RetCode: 0

Status: OK

CheckDir: immApex.Rcheck

Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD check --install=check:immApex.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings immApex_1.0.5.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/immApex.Rcheck’
* using R version 4.4.3 (2025-02-28)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘immApex/DESCRIPTION’ ... OK
* this is package ‘immApex’ version ‘1.0.5’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘immApex’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                       user system elapsed
variationalSequences 11.717  1.170  13.024
sequenceDecoder      10.506  1.137  11.768
propertyEncoder       9.622  0.940  10.672
onehotEncoder         8.655  0.912   9.733
getIMGT               0.676  0.008   5.246
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘spelling.R’
  Running ‘testthat.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: OK

Installation output

immApex.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD INSTALL immApex
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-4.4.3/site-library’
* installing *source* package ‘immApex’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (immApex)

Tests output

immApex.Rcheck/tests/spelling.Rout


R version 4.4.3 (2025-02-28) -- "Trophy Case"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> if(requireNamespace('spelling', quietly = TRUE))
+   spelling::spell_check_test(vignettes = TRUE, error = FALSE,
+                              skip_on_cran = TRUE)
NULL
> 
> proc.time()
   user  system elapsed 
  0.191   0.031   0.207

immApex.Rcheck/tests/testthat.Rout


R version 4.4.3 (2025-02-28) -- "Trophy Case"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/tests.html
> # * https://testthat.r-lib.org/reference/test_package.html#special-files
> 
> library(testthat)
> library(immApex)
> 
> test_check("immApex")
  × No solution found when resolving `--with` dependencies:
  ╰─▶ Because only the following versions of tensorflow-cpu are available:
          tensorflow-cpu==1.15.0
          tensorflow-cpu==2.1.0
          tensorflow-cpu==2.1.1
          tensorflow-cpu==2.1.2
          tensorflow-cpu==2.1.3
          tensorflow-cpu==2.1.4
          tensorflow-cpu==2.2.0
          tensorflow-cpu==2.2.1
          tensorflow-cpu==2.2.2
          tensorflow-cpu==2.2.3
          tensorflow-cpu==2.3.0
          tensorflow-cpu==2.3.1
          tensorflow-cpu==2.3.2
          tensorflow-cpu==2.3.3
          tensorflow-cpu==2.3.4
          tensorflow-cpu==2.4.0
          tensorflow-cpu==2.4.1
          tensorflow-cpu==2.4.2
          tensorflow-cpu==2.4.3
          tensorflow-cpu==2.4.4
          tensorflow-cpu==2.5.0
          tensorflow-cpu==2.5.1
          tensorflow-cpu==2.5.2
          tensorflow-cpu==2.5.3
          tensorflow-cpu==2.6.0
          tensorflow-cpu==2.6.1
          tensorflow-cpu==2.6.2
          tensorflow-cpu==2.6.3
          tensorflow-cpu==2.6.4
          tensorflow-cpu==2.6.5
          tensorflow-cpu==2.7.0
          tensorflow-cpu==2.7.1
          tensorflow-cpu==2.7.2
          tensorflow-cpu==2.7.3
          tensorflow-cpu==2.7.4
          tensorflow-cpu==2.8.0
          tensorflow-cpu==2.8.1
          tensorflow-cpu==2.8.2
          tensorflow-cpu==2.8.3
          tensorflow-cpu==2.8.4
          tensorflow-cpu==2.9.0
          tensorflow-cpu==2.9.1
          tensorflow-cpu==2.9.2
          tensorflow-cpu==2.9.3
          tensorflow-cpu==2.10.0
          tensorflow-cpu==2.10.1
          tensorflow-cpu==2.11.0
          tensorflow-cpu==2.11.1
          tensorflow-cpu==2.12.0
          tensorflow-cpu==2.12.1
          tensorflow-cpu==2.13.0
          tensorflow-cpu==2.13.1
          tensorflow-cpu==2.14.0
          tensorflow-cpu==2.14.1
          tensorflow-cpu==2.15.0
          tensorflow-cpu==2.15.0.post1
          tensorflow-cpu==2.15.1
          tensorflow-cpu==2.16.1
          tensorflow-cpu==2.16.2
          tensorflow-cpu==2.17.0
          tensorflow-cpu==2.17.1
          tensorflow-cpu==2.18.0
      and tensorflow-cpu<=2.11.1 has no wheels with a matching Python ABI
      tag (e.g., `cp311`), we can conclude that tensorflow-cpu<=2.11.1 cannot
      be used.
      And because tensorflow-cpu>=2.12.0 has no wheels with a matching
      platform tag (e.g., `manylinux_2_38_aarch64`) and you require
      tensorflow-cpu, we can conclude that your requirements are
      unsatisfiable.

      hint: Pre-releases are available for `tensorflow-cpu` in the requested
      range (e.g., 2.19.0rc0), but pre-releases weren't enabled (try:
      `--prerelease=allow`)

      hint: You require CPython 3.11 (`cp311`), but we only found wheels for
      `tensorflow-cpu` (v2.11.1) with the following Python ABI tags: `cp38`,
      `cp39`, `cp310`

      hint: Wheels are available for `tensorflow-cpu` (v2.18.0) on the
      following platforms: `manylinux_2_17_x86_64`, `manylinux2014_x86_64`,
      `win_amd64`
uv error code: 1
-- Current requirements -------------------------------------------------
 Python:   3.11.11 (reticulate default)
 Packages: numpy, keras, pydot, scipy, pandas, Pillow, ipython,
           tensorflow-cpu
-------------------------------------------------------------------------
Error in uv_get_or_create_env() : 
  Call `py_require()` to remove or replace conflicting requirements.
  × No solution found when resolving `--with` dependencies:
  ╰─▶ Because only the following versions of tensorflow-cpu are available:
          tensorflow-cpu==1.15.0
          tensorflow-cpu==2.1.0
          tensorflow-cpu==2.1.1
          tensorflow-cpu==2.1.2
          tensorflow-cpu==2.1.3
          tensorflow-cpu==2.1.4
          tensorflow-cpu==2.2.0
          tensorflow-cpu==2.2.1
          tensorflow-cpu==2.2.2
          tensorflow-cpu==2.2.3
          tensorflow-cpu==2.3.0
          tensorflow-cpu==2.3.1
          tensorflow-cpu==2.3.2
          tensorflow-cpu==2.3.3
          tensorflow-cpu==2.3.4
          tensorflow-cpu==2.4.0
          tensorflow-cpu==2.4.1
          tensorflow-cpu==2.4.2
          tensorflow-cpu==2.4.3
          tensorflow-cpu==2.4.4
          tensorflow-cpu==2.5.0
          tensorflow-cpu==2.5.1
          tensorflow-cpu==2.5.2
          tensorflow-cpu==2.5.3
          tensorflow-cpu==2.6.0
          tensorflow-cpu==2.6.1
          tensorflow-cpu==2.6.2
          tensorflow-cpu==2.6.3
          tensorflow-cpu==2.6.4
          tensorflow-cpu==2.6.5
          tensorflow-cpu==2.7.0
          tensorflow-cpu==2.7.1
          tensorflow-cpu==2.7.2
          tensorflow-cpu==2.7.3
          tensorflow-cpu==2.7.4
          tensorflow-cpu==2.8.0
          tensorflow-cpu==2.8.1
          tensorflow-cpu==2.8.2
          tensorflow-cpu==2.8.3
          tensorflow-cpu==2.8.4
          tensorflow-cpu==2.9.0
          tensorflow-cpu==2.9.1
          tensorflow-cpu==2.9.2
          tensorflow-cpu==2.9.3
          tensorflow-cpu==2.10.0
          tensorflow-cpu==2.10.1
          tensorflow-cpu==2.11.0
          tensorflow-cpu==2.11.1
          tensorflow-cpu==2.12.0
          tensorflow-cpu==2.12.1
          tensorflow-cpu==2.13.0
          tensorflow-cpu==2.13.1
          tensorflow-cpu==2.14.0
          tensorflow-cpu==2.14.1
          tensorflow-cpu==2.15.0
          tensorflow-cpu==2.15.0.post1
          tensorflow-cpu==2.15.1
          tensorflow-cpu==2.16.1
          tensorflow-cpu==2.16.2
          tensorflow-cpu==2.17.0
          tensorflow-cpu==2.17.1
          tensorflow-cpu==2.18.0
      and tensorflow-cpu<=2.11.1 has no wheels with a matching Python ABI
      tag (e.g., `cp311`), we can conclude that tensorflow-cpu<=2.11.1 cannot
      be used.
      And because tensorflow-cpu>=2.12.0 has no wheels with a matching
      platform tag (e.g., `manylinux_2_38_aarch64`) and you require
      tensorflow-cpu, we can conclude that your requirements are
      unsatisfiable.

      hint: Pre-releases are available for `tensorflow-cpu` in the requested
      range (e.g., 2.19.0rc0), but pre-releases weren't enabled (try:
      `--prerelease=allow`)

      hint: You require CPython 3.11 (`cp311`), but we only found wheels for
      `tensorflow-cpu` (v2.11.1) with the following Python ABI tags: `cp38`,
      `cp39`, `cp310`

      hint: Wheels are available for `tensorflow-cpu` (v2.18.0) on the
      following platforms: `manylinux_2_17_x86_64`, `manylinux2014_x86_64`,
      `win_amd64`
uv error code: 1
-- Current requirements -------------------------------------------------
 Python:   3.11.11 (reticulate default)
 Packages: numpy, keras, pydot, scipy, pandas, Pillow, ipython,
           tensorflow-cpu
-------------------------------------------------------------------------
Error in uv_get_or_create_env() : 
  Call `py_require()` to remove or replace conflicting requirements.
  × No solution found when resolving `--with` dependencies:
  ╰─▶ Because only the following versions of tensorflow-cpu are available:
          tensorflow-cpu==1.15.0
          tensorflow-cpu==2.1.0
          tensorflow-cpu==2.1.1
          tensorflow-cpu==2.1.2
          tensorflow-cpu==2.1.3
          tensorflow-cpu==2.1.4
          tensorflow-cpu==2.2.0
          tensorflow-cpu==2.2.1
          tensorflow-cpu==2.2.2
          tensorflow-cpu==2.2.3
          tensorflow-cpu==2.3.0
          tensorflow-cpu==2.3.1
          tensorflow-cpu==2.3.2
          tensorflow-cpu==2.3.3
          tensorflow-cpu==2.3.4
          tensorflow-cpu==2.4.0
          tensorflow-cpu==2.4.1
          tensorflow-cpu==2.4.2
          tensorflow-cpu==2.4.3
          tensorflow-cpu==2.4.4
          tensorflow-cpu==2.5.0
          tensorflow-cpu==2.5.1
          tensorflow-cpu==2.5.2
          tensorflow-cpu==2.5.3
          tensorflow-cpu==2.6.0
          tensorflow-cpu==2.6.1
          tensorflow-cpu==2.6.2
          tensorflow-cpu==2.6.3
          tensorflow-cpu==2.6.4
          tensorflow-cpu==2.6.5
          tensorflow-cpu==2.7.0
          tensorflow-cpu==2.7.1
          tensorflow-cpu==2.7.2
          tensorflow-cpu==2.7.3
          tensorflow-cpu==2.7.4
          tensorflow-cpu==2.8.0
          tensorflow-cpu==2.8.1
          tensorflow-cpu==2.8.2
          tensorflow-cpu==2.8.3
          tensorflow-cpu==2.8.4
          tensorflow-cpu==2.9.0
          tensorflow-cpu==2.9.1
          tensorflow-cpu==2.9.2
          tensorflow-cpu==2.9.3
          tensorflow-cpu==2.10.0
          tensorflow-cpu==2.10.1
          tensorflow-cpu==2.11.0
          tensorflow-cpu==2.11.1
          tensorflow-cpu==2.12.0
          tensorflow-cpu==2.12.1
          tensorflow-cpu==2.13.0
          tensorflow-cpu==2.13.1
          tensorflow-cpu==2.14.0
          tensorflow-cpu==2.14.1
          tensorflow-cpu==2.15.0
          tensorflow-cpu==2.15.0.post1
          tensorflow-cpu==2.15.1
          tensorflow-cpu==2.16.1
          tensorflow-cpu==2.16.2
          tensorflow-cpu==2.17.0
          tensorflow-cpu==2.17.1
          tensorflow-cpu==2.18.0
      and tensorflow-cpu<=2.11.1 has no wheels with a matching Python ABI
      tag (e.g., `cp311`), we can conclude that tensorflow-cpu<=2.11.1 cannot
      be used.
      And because tensorflow-cpu>=2.12.0 has no wheels with a matching
      platform tag (e.g., `manylinux_2_38_aarch64`) and you require
      tensorflow-cpu, we can conclude that your requirements are
      unsatisfiable.

      hint: Pre-releases are available for `tensorflow-cpu` in the requested
      range (e.g., 2.19.0rc0), but pre-releases weren't enabled (try:
      `--prerelease=allow`)

      hint: You require CPython 3.11 (`cp311`), but we only found wheels for
      `tensorflow-cpu` (v2.11.1) with the following Python ABI tags: `cp38`,
      `cp39`, `cp310`

      hint: Wheels are available for `tensorflow-cpu` (v2.18.0) on the
      following platforms: `manylinux_2_17_x86_64`, `manylinux2014_x86_64`,
      `win_amd64`
uv error code: 1
-- Current requirements -------------------------------------------------
 Python:   3.11.11 (reticulate default)
 Packages: numpy, keras, pydot, scipy, pandas, Pillow, ipython,
           tensorflow-cpu
-------------------------------------------------------------------------
Error in uv_get_or_create_env() : 
  Call `py_require()` to remove or replace conflicting requirements.
  × No solution found when resolving `--with` dependencies:
  ╰─▶ Because only the following versions of tensorflow-cpu are available:
          tensorflow-cpu==1.15.0
          tensorflow-cpu==2.1.0
          tensorflow-cpu==2.1.1
          tensorflow-cpu==2.1.2
          tensorflow-cpu==2.1.3
          tensorflow-cpu==2.1.4
          tensorflow-cpu==2.2.0
          tensorflow-cpu==2.2.1
          tensorflow-cpu==2.2.2
          tensorflow-cpu==2.2.3
          tensorflow-cpu==2.3.0
          tensorflow-cpu==2.3.1
          tensorflow-cpu==2.3.2
          tensorflow-cpu==2.3.3
          tensorflow-cpu==2.3.4
          tensorflow-cpu==2.4.0
          tensorflow-cpu==2.4.1
          tensorflow-cpu==2.4.2
          tensorflow-cpu==2.4.3
          tensorflow-cpu==2.4.4
          tensorflow-cpu==2.5.0
          tensorflow-cpu==2.5.1
          tensorflow-cpu==2.5.2
          tensorflow-cpu==2.5.3
          tensorflow-cpu==2.6.0
          tensorflow-cpu==2.6.1
          tensorflow-cpu==2.6.2
          tensorflow-cpu==2.6.3
          tensorflow-cpu==2.6.4
          tensorflow-cpu==2.6.5
          tensorflow-cpu==2.7.0
          tensorflow-cpu==2.7.1
          tensorflow-cpu==2.7.2
          tensorflow-cpu==2.7.3
          tensorflow-cpu==2.7.4
          tensorflow-cpu==2.8.0
          tensorflow-cpu==2.8.1
          tensorflow-cpu==2.8.2
          tensorflow-cpu==2.8.3
          tensorflow-cpu==2.8.4
          tensorflow-cpu==2.9.0
          tensorflow-cpu==2.9.1
          tensorflow-cpu==2.9.2
          tensorflow-cpu==2.9.3
          tensorflow-cpu==2.10.0
          tensorflow-cpu==2.10.1
          tensorflow-cpu==2.11.0
          tensorflow-cpu==2.11.1
          tensorflow-cpu==2.12.0
          tensorflow-cpu==2.12.1
          tensorflow-cpu==2.13.0
          tensorflow-cpu==2.13.1
          tensorflow-cpu==2.14.0
          tensorflow-cpu==2.14.1
          tensorflow-cpu==2.15.0
          tensorflow-cpu==2.15.0.post1
          tensorflow-cpu==2.15.1
          tensorflow-cpu==2.16.1
          tensorflow-cpu==2.16.2
          tensorflow-cpu==2.17.0
          tensorflow-cpu==2.17.1
          tensorflow-cpu==2.18.0
      and tensorflow-cpu<=2.11.1 has no wheels with a matching Python ABI
      tag (e.g., `cp311`), we can conclude that tensorflow-cpu<=2.11.1 cannot
      be used.
      And because tensorflow-cpu>=2.12.0 has no wheels with a matching
      platform tag (e.g., `manylinux_2_38_aarch64`) and you require
      tensorflow-cpu, we can conclude that your requirements are
      unsatisfiable.

      hint: Pre-releases are available for `tensorflow-cpu` in the requested
      range (e.g., 2.19.0rc0), but pre-releases weren't enabled (try:
      `--prerelease=allow`)

      hint: You require CPython 3.11 (`cp311`), but we only found wheels for
      `tensorflow-cpu` (v2.11.1) with the following Python ABI tags: `cp38`,
      `cp39`, `cp310`

      hint: Wheels are available for `tensorflow-cpu` (v2.18.0) on the
      following platforms: `manylinux_2_17_x86_64`, `manylinux2014_x86_64`,
      `win_amd64`
uv error code: 1
-- Current requirements -------------------------------------------------
 Python:   3.11.11 (reticulate default)
 Packages: numpy, keras, pydot, scipy, pandas, Pillow, ipython,
           tensorflow-cpu
-------------------------------------------------------------------------
Error in uv_get_or_create_env() : 
  Call `py_require()` to remove or replace conflicting requirements.
  × No solution found when resolving `--with` dependencies:
  ╰─▶ Because only the following versions of tensorflow-cpu are available:
          tensorflow-cpu==1.15.0
          tensorflow-cpu==2.1.0
          tensorflow-cpu==2.1.1
          tensorflow-cpu==2.1.2
          tensorflow-cpu==2.1.3
          tensorflow-cpu==2.1.4
          tensorflow-cpu==2.2.0
          tensorflow-cpu==2.2.1
          tensorflow-cpu==2.2.2
          tensorflow-cpu==2.2.3
          tensorflow-cpu==2.3.0
          tensorflow-cpu==2.3.1
          tensorflow-cpu==2.3.2
          tensorflow-cpu==2.3.3
          tensorflow-cpu==2.3.4
          tensorflow-cpu==2.4.0
          tensorflow-cpu==2.4.1
          tensorflow-cpu==2.4.2
          tensorflow-cpu==2.4.3
          tensorflow-cpu==2.4.4
          tensorflow-cpu==2.5.0
          tensorflow-cpu==2.5.1
          tensorflow-cpu==2.5.2
          tensorflow-cpu==2.5.3
          tensorflow-cpu==2.6.0
          tensorflow-cpu==2.6.1
          tensorflow-cpu==2.6.2
          tensorflow-cpu==2.6.3
          tensorflow-cpu==2.6.4
          tensorflow-cpu==2.6.5
          tensorflow-cpu==2.7.0
          tensorflow-cpu==2.7.1
          tensorflow-cpu==2.7.2
          tensorflow-cpu==2.7.3
          tensorflow-cpu==2.7.4
          tensorflow-cpu==2.8.0
          tensorflow-cpu==2.8.1
          tensorflow-cpu==2.8.2
          tensorflow-cpu==2.8.3
          tensorflow-cpu==2.8.4
          tensorflow-cpu==2.9.0
          tensorflow-cpu==2.9.1
          tensorflow-cpu==2.9.2
          tensorflow-cpu==2.9.3
          tensorflow-cpu==2.10.0
          tensorflow-cpu==2.10.1
          tensorflow-cpu==2.11.0
          tensorflow-cpu==2.11.1
          tensorflow-cpu==2.12.0
          tensorflow-cpu==2.12.1
          tensorflow-cpu==2.13.0
          tensorflow-cpu==2.13.1
          tensorflow-cpu==2.14.0
          tensorflow-cpu==2.14.1
          tensorflow-cpu==2.15.0
          tensorflow-cpu==2.15.0.post1
          tensorflow-cpu==2.15.1
          tensorflow-cpu==2.16.1
          tensorflow-cpu==2.16.2
          tensorflow-cpu==2.17.0
          tensorflow-cpu==2.17.1
          tensorflow-cpu==2.18.0
      and tensorflow-cpu<=2.11.1 has no wheels with a matching Python ABI
      tag (e.g., `cp311`), we can conclude that tensorflow-cpu<=2.11.1 cannot
      be used.
      And because tensorflow-cpu>=2.12.0 has no wheels with a matching
      platform tag (e.g., `manylinux_2_38_aarch64`) and you require
      tensorflow-cpu, we can conclude that your requirements are
      unsatisfiable.

      hint: Pre-releases are available for `tensorflow-cpu` in the requested
      range (e.g., 2.19.0rc0), but pre-releases weren't enabled (try:
      `--prerelease=allow`)

      hint: You require CPython 3.11 (`cp311`), but we only found wheels for
      `tensorflow-cpu` (v2.11.1) with the following Python ABI tags: `cp38`,
      `cp39`, `cp310`

      hint: Wheels are available for `tensorflow-cpu` (v2.18.0) on the
      following platforms: `manylinux_2_17_x86_64`, `manylinux2014_x86_64`,
      `win_amd64`
uv error code: 1
-- Current requirements -------------------------------------------------
 Python:   3.11.11 (reticulate default)
 Packages: numpy, keras, pydot, scipy, pandas, Pillow, ipython,
           tensorflow-cpu
-------------------------------------------------------------------------
Error in uv_get_or_create_env() : 
  Call `py_require()` to remove or replace conflicting requirements.
  × No solution found when resolving `--with` dependencies:
  ╰─▶ Because only the following versions of tensorflow-cpu are available:
          tensorflow-cpu==1.15.0
          tensorflow-cpu==2.1.0
          tensorflow-cpu==2.1.1
          tensorflow-cpu==2.1.2
          tensorflow-cpu==2.1.3
          tensorflow-cpu==2.1.4
          tensorflow-cpu==2.2.0
          tensorflow-cpu==2.2.1
          tensorflow-cpu==2.2.2
          tensorflow-cpu==2.2.3
          tensorflow-cpu==2.3.0
          tensorflow-cpu==2.3.1
          tensorflow-cpu==2.3.2
          tensorflow-cpu==2.3.3
          tensorflow-cpu==2.3.4
          tensorflow-cpu==2.4.0
          tensorflow-cpu==2.4.1
          tensorflow-cpu==2.4.2
          tensorflow-cpu==2.4.3
          tensorflow-cpu==2.4.4
          tensorflow-cpu==2.5.0
          tensorflow-cpu==2.5.1
          tensorflow-cpu==2.5.2
          tensorflow-cpu==2.5.3
          tensorflow-cpu==2.6.0
          tensorflow-cpu==2.6.1
          tensorflow-cpu==2.6.2
          tensorflow-cpu==2.6.3
          tensorflow-cpu==2.6.4
          tensorflow-cpu==2.6.5
          tensorflow-cpu==2.7.0
          tensorflow-cpu==2.7.1
          tensorflow-cpu==2.7.2
          tensorflow-cpu==2.7.3
          tensorflow-cpu==2.7.4
          tensorflow-cpu==2.8.0
          tensorflow-cpu==2.8.1
          tensorflow-cpu==2.8.2
          tensorflow-cpu==2.8.3
          tensorflow-cpu==2.8.4
          tensorflow-cpu==2.9.0
          tensorflow-cpu==2.9.1
          tensorflow-cpu==2.9.2
          tensorflow-cpu==2.9.3
          tensorflow-cpu==2.10.0
          tensorflow-cpu==2.10.1
          tensorflow-cpu==2.11.0
          tensorflow-cpu==2.11.1
          tensorflow-cpu==2.12.0
          tensorflow-cpu==2.12.1
          tensorflow-cpu==2.13.0
          tensorflow-cpu==2.13.1
          tensorflow-cpu==2.14.0
          tensorflow-cpu==2.14.1
          tensorflow-cpu==2.15.0
          tensorflow-cpu==2.15.0.post1
          tensorflow-cpu==2.15.1
          tensorflow-cpu==2.16.1
          tensorflow-cpu==2.16.2
          tensorflow-cpu==2.17.0
          tensorflow-cpu==2.17.1
          tensorflow-cpu==2.18.0
      and tensorflow-cpu<=2.11.1 has no wheels with a matching Python ABI
      tag (e.g., `cp311`), we can conclude that tensorflow-cpu<=2.11.1 cannot
      be used.
      And because tensorflow-cpu>=2.12.0 has no wheels with a matching
      platform tag (e.g., `manylinux_2_38_aarch64`) and you require
      tensorflow-cpu, we can conclude that your requirements are
      unsatisfiable.

      hint: Pre-releases are available for `tensorflow-cpu` in the requested
      range (e.g., 2.19.0rc0), but pre-releases weren't enabled (try:
      `--prerelease=allow`)

      hint: You require CPython 3.11 (`cp311`), but we only found wheels for
      `tensorflow-cpu` (v2.11.1) with the following Python ABI tags: `cp38`,
      `cp39`, `cp310`

      hint: Wheels are available for `tensorflow-cpu` (v2.18.0) on the
      following platforms: `manylinux_2_17_x86_64`, `manylinux2014_x86_64`,
      `win_amd64`
uv error code: 1
-- Current requirements -------------------------------------------------
 Python:   3.11.11 (reticulate default)
 Packages: numpy, keras, pydot, scipy, pandas, Pillow, ipython,
           tensorflow-cpu
-------------------------------------------------------------------------
Error in uv_get_or_create_env() : 
  Call `py_require()` to remove or replace conflicting requirements.
  × No solution found when resolving `--with` dependencies:
  ╰─▶ Because only the following versions of tensorflow-cpu are available:
          tensorflow-cpu==1.15.0
          tensorflow-cpu==2.1.0
          tensorflow-cpu==2.1.1
          tensorflow-cpu==2.1.2
          tensorflow-cpu==2.1.3
          tensorflow-cpu==2.1.4
          tensorflow-cpu==2.2.0
          tensorflow-cpu==2.2.1
          tensorflow-cpu==2.2.2
          tensorflow-cpu==2.2.3
          tensorflow-cpu==2.3.0
          tensorflow-cpu==2.3.1
          tensorflow-cpu==2.3.2
          tensorflow-cpu==2.3.3
          tensorflow-cpu==2.3.4
          tensorflow-cpu==2.4.0
          tensorflow-cpu==2.4.1
          tensorflow-cpu==2.4.2
          tensorflow-cpu==2.4.3
          tensorflow-cpu==2.4.4
          tensorflow-cpu==2.5.0
          tensorflow-cpu==2.5.1
          tensorflow-cpu==2.5.2
          tensorflow-cpu==2.5.3
          tensorflow-cpu==2.6.0
          tensorflow-cpu==2.6.1
          tensorflow-cpu==2.6.2
          tensorflow-cpu==2.6.3
          tensorflow-cpu==2.6.4
          tensorflow-cpu==2.6.5
          tensorflow-cpu==2.7.0
          tensorflow-cpu==2.7.1
          tensorflow-cpu==2.7.2
          tensorflow-cpu==2.7.3
          tensorflow-cpu==2.7.4
          tensorflow-cpu==2.8.0
          tensorflow-cpu==2.8.1
          tensorflow-cpu==2.8.2
          tensorflow-cpu==2.8.3
          tensorflow-cpu==2.8.4
          tensorflow-cpu==2.9.0
          tensorflow-cpu==2.9.1
          tensorflow-cpu==2.9.2
          tensorflow-cpu==2.9.3
          tensorflow-cpu==2.10.0
          tensorflow-cpu==2.10.1
          tensorflow-cpu==2.11.0
          tensorflow-cpu==2.11.1
          tensorflow-cpu==2.12.0
          tensorflow-cpu==2.12.1
          tensorflow-cpu==2.13.0
          tensorflow-cpu==2.13.1
          tensorflow-cpu==2.14.0
          tensorflow-cpu==2.14.1
          tensorflow-cpu==2.15.0
          tensorflow-cpu==2.15.0.post1
          tensorflow-cpu==2.15.1
          tensorflow-cpu==2.16.1
          tensorflow-cpu==2.16.2
          tensorflow-cpu==2.17.0
          tensorflow-cpu==2.17.1
          tensorflow-cpu==2.18.0
      and tensorflow-cpu<=2.11.1 has no wheels with a matching Python ABI
      tag (e.g., `cp311`), we can conclude that tensorflow-cpu<=2.11.1 cannot
      be used.
      And because tensorflow-cpu>=2.12.0 has no wheels with a matching
      platform tag (e.g., `manylinux_2_38_aarch64`) and you require
      tensorflow-cpu, we can conclude that your requirements are
      unsatisfiable.

      hint: Pre-releases are available for `tensorflow-cpu` in the requested
      range (e.g., 2.19.0rc0), but pre-releases weren't enabled (try:
      `--prerelease=allow`)

      hint: You require CPython 3.11 (`cp311`), but we only found wheels for
      `tensorflow-cpu` (v2.11.1) with the following Python ABI tags: `cp38`,
      `cp39`, `cp310`

      hint: Wheels are available for `tensorflow-cpu` (v2.18.0) on the
      following platforms: `manylinux_2_17_x86_64`, `manylinux2014_x86_64`,
      `win_amd64`
uv error code: 1
-- Current requirements -------------------------------------------------
 Python:   3.11.11 (reticulate default)
 Packages: numpy, keras, pydot, scipy, pandas, Pillow, ipython,
           tensorflow-cpu
-------------------------------------------------------------------------
Error in uv_get_or_create_env() : 
  Call `py_require()` to remove or replace conflicting requirements.
  × No solution found when resolving `--with` dependencies:
  ╰─▶ Because only the following versions of tensorflow-cpu are available:
          tensorflow-cpu==1.15.0
          tensorflow-cpu==2.1.0
          tensorflow-cpu==2.1.1
          tensorflow-cpu==2.1.2
          tensorflow-cpu==2.1.3
          tensorflow-cpu==2.1.4
          tensorflow-cpu==2.2.0
          tensorflow-cpu==2.2.1
          tensorflow-cpu==2.2.2
          tensorflow-cpu==2.2.3
          tensorflow-cpu==2.3.0
          tensorflow-cpu==2.3.1
          tensorflow-cpu==2.3.2
          tensorflow-cpu==2.3.3
          tensorflow-cpu==2.3.4
          tensorflow-cpu==2.4.0
          tensorflow-cpu==2.4.1
          tensorflow-cpu==2.4.2
          tensorflow-cpu==2.4.3
          tensorflow-cpu==2.4.4
          tensorflow-cpu==2.5.0
          tensorflow-cpu==2.5.1
          tensorflow-cpu==2.5.2
          tensorflow-cpu==2.5.3
          tensorflow-cpu==2.6.0
          tensorflow-cpu==2.6.1
          tensorflow-cpu==2.6.2
          tensorflow-cpu==2.6.3
          tensorflow-cpu==2.6.4
          tensorflow-cpu==2.6.5
          tensorflow-cpu==2.7.0
          tensorflow-cpu==2.7.1
          tensorflow-cpu==2.7.2
          tensorflow-cpu==2.7.3
          tensorflow-cpu==2.7.4
          tensorflow-cpu==2.8.0
          tensorflow-cpu==2.8.1
          tensorflow-cpu==2.8.2
          tensorflow-cpu==2.8.3
          tensorflow-cpu==2.8.4
          tensorflow-cpu==2.9.0
          tensorflow-cpu==2.9.1
          tensorflow-cpu==2.9.2
          tensorflow-cpu==2.9.3
          tensorflow-cpu==2.10.0
          tensorflow-cpu==2.10.1
          tensorflow-cpu==2.11.0
          tensorflow-cpu==2.11.1
          tensorflow-cpu==2.12.0
          tensorflow-cpu==2.12.1
          tensorflow-cpu==2.13.0
          tensorflow-cpu==2.13.1
          tensorflow-cpu==2.14.0
          tensorflow-cpu==2.14.1
          tensorflow-cpu==2.15.0
          tensorflow-cpu==2.15.0.post1
          tensorflow-cpu==2.15.1
          tensorflow-cpu==2.16.1
          tensorflow-cpu==2.16.2
          tensorflow-cpu==2.17.0
          tensorflow-cpu==2.17.1
          tensorflow-cpu==2.18.0
      and tensorflow-cpu<=2.11.1 has no wheels with a matching Python ABI
      tag (e.g., `cp311`), we can conclude that tensorflow-cpu<=2.11.1 cannot
      be used.
      And because tensorflow-cpu>=2.12.0 has no wheels with a matching
      platform tag (e.g., `manylinux_2_38_aarch64`) and you require
      tensorflow-cpu, we can conclude that your requirements are
      unsatisfiable.

      hint: Pre-releases are available for `tensorflow-cpu` in the requested
      range (e.g., 2.19.0rc0), but pre-releases weren't enabled (try:
      `--prerelease=allow`)

      hint: You require CPython 3.11 (`cp311`), but we only found wheels for
      `tensorflow-cpu` (v2.11.1) with the following Python ABI tags: `cp38`,
      `cp39`, `cp310`

      hint: Wheels are available for `tensorflow-cpu` (v2.18.0) on the
      following platforms: `manylinux_2_17_x86_64`, `manylinux2014_x86_64`,
      `win_amd64`
uv error code: 1
-- Current requirements -------------------------------------------------
 Python:   3.11.11 (reticulate default)
 Packages: numpy, keras, pydot, scipy, pandas, Pillow, ipython,
           tensorflow-cpu
-------------------------------------------------------------------------
Error in uv_get_or_create_env() : 
  Call `py_require()` to remove or replace conflicting requirements.
  × No solution found when resolving `--with` dependencies:
  ╰─▶ Because only the following versions of tensorflow-cpu are available:
          tensorflow-cpu==1.15.0
          tensorflow-cpu==2.1.0
          tensorflow-cpu==2.1.1
          tensorflow-cpu==2.1.2
          tensorflow-cpu==2.1.3
          tensorflow-cpu==2.1.4
          tensorflow-cpu==2.2.0
          tensorflow-cpu==2.2.1
          tensorflow-cpu==2.2.2
          tensorflow-cpu==2.2.3
          tensorflow-cpu==2.3.0
          tensorflow-cpu==2.3.1
          tensorflow-cpu==2.3.2
          tensorflow-cpu==2.3.3
          tensorflow-cpu==2.3.4
          tensorflow-cpu==2.4.0
          tensorflow-cpu==2.4.1
          tensorflow-cpu==2.4.2
          tensorflow-cpu==2.4.3
          tensorflow-cpu==2.4.4
          tensorflow-cpu==2.5.0
          tensorflow-cpu==2.5.1
          tensorflow-cpu==2.5.2
          tensorflow-cpu==2.5.3
          tensorflow-cpu==2.6.0
          tensorflow-cpu==2.6.1
          tensorflow-cpu==2.6.2
          tensorflow-cpu==2.6.3
          tensorflow-cpu==2.6.4
          tensorflow-cpu==2.6.5
          tensorflow-cpu==2.7.0
          tensorflow-cpu==2.7.1
          tensorflow-cpu==2.7.2
          tensorflow-cpu==2.7.3
          tensorflow-cpu==2.7.4
          tensorflow-cpu==2.8.0
          tensorflow-cpu==2.8.1
          tensorflow-cpu==2.8.2
          tensorflow-cpu==2.8.3
          tensorflow-cpu==2.8.4
          tensorflow-cpu==2.9.0
          tensorflow-cpu==2.9.1
          tensorflow-cpu==2.9.2
          tensorflow-cpu==2.9.3
          tensorflow-cpu==2.10.0
          tensorflow-cpu==2.10.1
          tensorflow-cpu==2.11.0
          tensorflow-cpu==2.11.1
          tensorflow-cpu==2.12.0
          tensorflow-cpu==2.12.1
          tensorflow-cpu==2.13.0
          tensorflow-cpu==2.13.1
          tensorflow-cpu==2.14.0
          tensorflow-cpu==2.14.1
          tensorflow-cpu==2.15.0
          tensorflow-cpu==2.15.0.post1
          tensorflow-cpu==2.15.1
          tensorflow-cpu==2.16.1
          tensorflow-cpu==2.16.2
          tensorflow-cpu==2.17.0
          tensorflow-cpu==2.17.1
          tensorflow-cpu==2.18.0
      and tensorflow-cpu<=2.11.1 has no wheels with a matching Python ABI
      tag (e.g., `cp311`), we can conclude that tensorflow-cpu<=2.11.1 cannot
      be used.
      And because tensorflow-cpu>=2.12.0 has no wheels with a matching
      platform tag (e.g., `manylinux_2_38_aarch64`) and you require
      tensorflow-cpu, we can conclude that your requirements are
      unsatisfiable.

      hint: Pre-releases are available for `tensorflow-cpu` in the requested
      range (e.g., 2.19.0rc0), but pre-releases weren't enabled (try:
      `--prerelease=allow`)

      hint: You require CPython 3.11 (`cp311`), but we only found wheels for
      `tensorflow-cpu` (v2.11.1) with the following Python ABI tags: `cp38`,
      `cp39`, `cp310`

      hint: Wheels are available for `tensorflow-cpu` (v2.18.0) on the
      following platforms: `manylinux_2_17_x86_64`, `manylinux2014_x86_64`,
      `win_amd64`
uv error code: 1
-- Current requirements -------------------------------------------------
 Python:   3.11.11 (reticulate default)
 Packages: numpy, keras, pydot, scipy, pandas, Pillow, ipython,
           tensorflow-cpu
-------------------------------------------------------------------------
Error in uv_get_or_create_env() : 
  Call `py_require()` to remove or replace conflicting requirements.
  × No solution found when resolving `--with` dependencies:
  ╰─▶ Because only the following versions of tensorflow-cpu are available:
          tensorflow-cpu==1.15.0
          tensorflow-cpu==2.1.0
          tensorflow-cpu==2.1.1
          tensorflow-cpu==2.1.2
          tensorflow-cpu==2.1.3
          tensorflow-cpu==2.1.4
          tensorflow-cpu==2.2.0
          tensorflow-cpu==2.2.1
          tensorflow-cpu==2.2.2
          tensorflow-cpu==2.2.3
          tensorflow-cpu==2.3.0
          tensorflow-cpu==2.3.1
          tensorflow-cpu==2.3.2
          tensorflow-cpu==2.3.3
          tensorflow-cpu==2.3.4
          tensorflow-cpu==2.4.0
          tensorflow-cpu==2.4.1
          tensorflow-cpu==2.4.2
          tensorflow-cpu==2.4.3
          tensorflow-cpu==2.4.4
          tensorflow-cpu==2.5.0
          tensorflow-cpu==2.5.1
          tensorflow-cpu==2.5.2
          tensorflow-cpu==2.5.3
          tensorflow-cpu==2.6.0
          tensorflow-cpu==2.6.1
          tensorflow-cpu==2.6.2
          tensorflow-cpu==2.6.3
          tensorflow-cpu==2.6.4
          tensorflow-cpu==2.6.5
          tensorflow-cpu==2.7.0
          tensorflow-cpu==2.7.1
          tensorflow-cpu==2.7.2
          tensorflow-cpu==2.7.3
          tensorflow-cpu==2.7.4
          tensorflow-cpu==2.8.0
          tensorflow-cpu==2.8.1
          tensorflow-cpu==2.8.2
          tensorflow-cpu==2.8.3
          tensorflow-cpu==2.8.4
          tensorflow-cpu==2.9.0
          tensorflow-cpu==2.9.1
          tensorflow-cpu==2.9.2
          tensorflow-cpu==2.9.3
          tensorflow-cpu==2.10.0
          tensorflow-cpu==2.10.1
          tensorflow-cpu==2.11.0
          tensorflow-cpu==2.11.1
          tensorflow-cpu==2.12.0
          tensorflow-cpu==2.12.1
          tensorflow-cpu==2.13.0
          tensorflow-cpu==2.13.1
          tensorflow-cpu==2.14.0
          tensorflow-cpu==2.14.1
          tensorflow-cpu==2.15.0
          tensorflow-cpu==2.15.0.post1
          tensorflow-cpu==2.15.1
          tensorflow-cpu==2.16.1
          tensorflow-cpu==2.16.2
          tensorflow-cpu==2.17.0
          tensorflow-cpu==2.17.1
          tensorflow-cpu==2.18.0
      and tensorflow-cpu<=2.11.1 has no wheels with a matching Python ABI
      tag (e.g., `cp311`), we can conclude that tensorflow-cpu<=2.11.1 cannot
      be used.
      And because tensorflow-cpu>=2.12.0 has no wheels with a matching
      platform tag (e.g., `manylinux_2_38_aarch64`) and you require
      tensorflow-cpu, we can conclude that your requirements are
      unsatisfiable.

      hint: Pre-releases are available for `tensorflow-cpu` in the requested
      range (e.g., 2.19.0rc0), but pre-releases weren't enabled (try:
      `--prerelease=allow`)

      hint: You require CPython 3.11 (`cp311`), but we only found wheels for
      `tensorflow-cpu` (v2.11.1) with the following Python ABI tags: `cp38`,
      `cp39`, `cp310`

      hint: Wheels are available for `tensorflow-cpu` (v2.18.0) on the
      following platforms: `manylinux_2_17_x86_64`, `manylinux2014_x86_64`,
      `win_amd64`
uv error code: 1
-- Current requirements -------------------------------------------------
 Python:   3.11.11 (reticulate default)
 Packages: numpy, keras, pydot, scipy, pandas, Pillow, ipython,
           tensorflow-cpu
-------------------------------------------------------------------------
Error in uv_get_or_create_env() : 
  Call `py_require()` to remove or replace conflicting requirements.
  × No solution found when resolving `--with` dependencies:
  ╰─▶ Because only the following versions of tensorflow-cpu are available:
          tensorflow-cpu==1.15.0
          tensorflow-cpu==2.1.0
          tensorflow-cpu==2.1.1
          tensorflow-cpu==2.1.2
          tensorflow-cpu==2.1.3
          tensorflow-cpu==2.1.4
          tensorflow-cpu==2.2.0
          tensorflow-cpu==2.2.1
          tensorflow-cpu==2.2.2
          tensorflow-cpu==2.2.3
          tensorflow-cpu==2.3.0
          tensorflow-cpu==2.3.1
          tensorflow-cpu==2.3.2
          tensorflow-cpu==2.3.3
          tensorflow-cpu==2.3.4
          tensorflow-cpu==2.4.0
          tensorflow-cpu==2.4.1
          tensorflow-cpu==2.4.2
          tensorflow-cpu==2.4.3
          tensorflow-cpu==2.4.4
          tensorflow-cpu==2.5.0
          tensorflow-cpu==2.5.1
          tensorflow-cpu==2.5.2
          tensorflow-cpu==2.5.3
          tensorflow-cpu==2.6.0
          tensorflow-cpu==2.6.1
          tensorflow-cpu==2.6.2
          tensorflow-cpu==2.6.3
          tensorflow-cpu==2.6.4
          tensorflow-cpu==2.6.5
          tensorflow-cpu==2.7.0
          tensorflow-cpu==2.7.1
          tensorflow-cpu==2.7.2
          tensorflow-cpu==2.7.3
          tensorflow-cpu==2.7.4
          tensorflow-cpu==2.8.0
          tensorflow-cpu==2.8.1
          tensorflow-cpu==2.8.2
          tensorflow-cpu==2.8.3
          tensorflow-cpu==2.8.4
          tensorflow-cpu==2.9.0
          tensorflow-cpu==2.9.1
          tensorflow-cpu==2.9.2
          tensorflow-cpu==2.9.3
          tensorflow-cpu==2.10.0
          tensorflow-cpu==2.10.1
          tensorflow-cpu==2.11.0
          tensorflow-cpu==2.11.1
          tensorflow-cpu==2.12.0
          tensorflow-cpu==2.12.1
          tensorflow-cpu==2.13.0
          tensorflow-cpu==2.13.1
          tensorflow-cpu==2.14.0
          tensorflow-cpu==2.14.1
          tensorflow-cpu==2.15.0
          tensorflow-cpu==2.15.0.post1
          tensorflow-cpu==2.15.1
          tensorflow-cpu==2.16.1
          tensorflow-cpu==2.16.2
          tensorflow-cpu==2.17.0
          tensorflow-cpu==2.17.1
          tensorflow-cpu==2.18.0
      and tensorflow-cpu<=2.11.1 has no wheels with a matching Python ABI
      tag (e.g., `cp311`), we can conclude that tensorflow-cpu<=2.11.1 cannot
      be used.
      And because tensorflow-cpu>=2.12.0 has no wheels with a matching
      platform tag (e.g., `manylinux_2_38_aarch64`) and you require
      tensorflow-cpu, we can conclude that your requirements are
      unsatisfiable.

      hint: Pre-releases are available for `tensorflow-cpu` in the requested
      range (e.g., 2.19.0rc0), but pre-releases weren't enabled (try:
      `--prerelease=allow`)

      hint: You require CPython 3.11 (`cp311`), but we only found wheels for
      `tensorflow-cpu` (v2.11.1) with the following Python ABI tags: `cp38`,
      `cp39`, `cp310`

      hint: Wheels are available for `tensorflow-cpu` (v2.18.0) on the
      following platforms: `manylinux_2_17_x86_64`, `manylinux2014_x86_64`,
      `win_amd64`
uv error code: 1
-- Current requirements -------------------------------------------------
 Python:   3.11.11 (reticulate default)
 Packages: numpy, keras, pydot, scipy, pandas, Pillow, ipython,
           tensorflow-cpu
-------------------------------------------------------------------------
Error in uv_get_or_create_env() : 
  Call `py_require()` to remove or replace conflicting requirements.
  × No solution found when resolving `--with` dependencies:
  ╰─▶ Because only the following versions of tensorflow-cpu are available:
          tensorflow-cpu==1.15.0
          tensorflow-cpu==2.1.0
          tensorflow-cpu==2.1.1
          tensorflow-cpu==2.1.2
          tensorflow-cpu==2.1.3
          tensorflow-cpu==2.1.4
          tensorflow-cpu==2.2.0
          tensorflow-cpu==2.2.1
          tensorflow-cpu==2.2.2
          tensorflow-cpu==2.2.3
          tensorflow-cpu==2.3.0
          tensorflow-cpu==2.3.1
          tensorflow-cpu==2.3.2
          tensorflow-cpu==2.3.3
          tensorflow-cpu==2.3.4
          tensorflow-cpu==2.4.0
          tensorflow-cpu==2.4.1
          tensorflow-cpu==2.4.2
          tensorflow-cpu==2.4.3
          tensorflow-cpu==2.4.4
          tensorflow-cpu==2.5.0
          tensorflow-cpu==2.5.1
          tensorflow-cpu==2.5.2
          tensorflow-cpu==2.5.3
          tensorflow-cpu==2.6.0
          tensorflow-cpu==2.6.1
          tensorflow-cpu==2.6.2
          tensorflow-cpu==2.6.3
          tensorflow-cpu==2.6.4
          tensorflow-cpu==2.6.5
          tensorflow-cpu==2.7.0
          tensorflow-cpu==2.7.1
          tensorflow-cpu==2.7.2
          tensorflow-cpu==2.7.3
          tensorflow-cpu==2.7.4
          tensorflow-cpu==2.8.0
          tensorflow-cpu==2.8.1
          tensorflow-cpu==2.8.2
          tensorflow-cpu==2.8.3
          tensorflow-cpu==2.8.4
          tensorflow-cpu==2.9.0
          tensorflow-cpu==2.9.1
          tensorflow-cpu==2.9.2
          tensorflow-cpu==2.9.3
          tensorflow-cpu==2.10.0
          tensorflow-cpu==2.10.1
          tensorflow-cpu==2.11.0
          tensorflow-cpu==2.11.1
          tensorflow-cpu==2.12.0
          tensorflow-cpu==2.12.1
          tensorflow-cpu==2.13.0
          tensorflow-cpu==2.13.1
          tensorflow-cpu==2.14.0
          tensorflow-cpu==2.14.1
          tensorflow-cpu==2.15.0
          tensorflow-cpu==2.15.0.post1
          tensorflow-cpu==2.15.1
          tensorflow-cpu==2.16.1
          tensorflow-cpu==2.16.2
          tensorflow-cpu==2.17.0
          tensorflow-cpu==2.17.1
          tensorflow-cpu==2.18.0
      and tensorflow-cpu<=2.11.1 has no wheels with a matching Python ABI
      tag (e.g., `cp311`), we can conclude that tensorflow-cpu<=2.11.1 cannot
      be used.
      And because tensorflow-cpu>=2.12.0 has no wheels with a matching
      platform tag (e.g., `manylinux_2_38_aarch64`) and you require
      tensorflow-cpu, we can conclude that your requirements are
      unsatisfiable.

      hint: Pre-releases are available for `tensorflow-cpu` in the requested
      range (e.g., 2.19.0rc0), but pre-releases weren't enabled (try:
      `--prerelease=allow`)

      hint: You require CPython 3.11 (`cp311`), but we only found wheels for
      `tensorflow-cpu` (v2.11.1) with the following Python ABI tags: `cp38`,
      `cp39`, `cp310`

      hint: Wheels are available for `tensorflow-cpu` (v2.18.0) on the
      following platforms: `manylinux_2_17_x86_64`, `manylinux2014_x86_64`,
      `win_amd64`
uv error code: 1
-- Current requirements -------------------------------------------------
 Python:   3.11.11 (reticulate default)
 Packages: numpy, keras, pydot, scipy, pandas, Pillow, ipython,
           tensorflow-cpu
-------------------------------------------------------------------------
Error in uv_get_or_create_env() : 
  Call `py_require()` to remove or replace conflicting requirements.
[ FAIL 0 | WARN 0 | SKIP 7 | PASS 34 ]

══ Skipped tests (7) ═══════════════════════════════════════════════════════════
• Required Python modules (Keras, NumPy) are not available. (6):
  'test-generateSequences.R:10:5', 'test-onehotEncoder.R:10:5',
  'test-propertyEncoder.R:10:5', 'test-sequenceDecoder.R:10:5',
  'test-tokenizeSequences.R:10:5', 'test-variationalSequences.R:10:5'
• empty test (1): 'test-getIR.R:3:1'

[ FAIL 0 | WARN 0 | SKIP 7 | PASS 34 ]
> 
> proc.time()
   user  system elapsed 
191.462  18.714 230.619

Example timings

immApex.Rcheck/immApex-Ex.timings

name	user	system	elapsed
adjacencyMatrix	0.012	0.000	0.013
formatGenes	0.879	0.144	1.025
generateSequences	0.004	0.000	0.004
geometricEncoder	0.214	0.024	0.237
getIMGT	0.676	0.008	5.246
inferCDR	0.560	0.000	3.573
mutateSequences	0.014	0.008	0.022
onehotEncoder	8.655	0.912	9.733
positionalEncoder	0.015	0.000	0.016
probabilityMatrix	0.007	0.000	0.007
propertyEncoder	9.622	0.940	10.672
sequenceDecoder	10.506	1.137	11.768
tokenizeSequences	0.003	0.003	0.006
variationalSequences	11.717	1.170	13.024