Closed willright28 closed 10 months ago
bodkan
commented
10 months ago Hi, can you please open a fresh terminal, start R there, type in (in sequence):
library(slendr)Then
init_env()And then
check_env()And paste all the contents that you get from each of those commands one after another?
bodkan
commented
10 months ago Also, I'm not sure what "running slim" means here. It's important for me to know where are you running it (RStudio, R, operating system, version of R -- you can get that from Sys.info()), what version of slendr (get that from help(package = "slendr") and running what -- without having a minimum necessary slendr R script which still gets you error, I have nothing to work with, I'm afraid.
This is a great guide on what I'm asking that applies to submitting R bugs regardless of the package: http://adv-r.had.co.nz/Reproducibility.html
Thanks!
willright28
commented
10 months ago Thanks for your attention! I will try my best to present the question as clearly as possible.
I run slendr v 0.8.1.9000 by R on centos 7. Sys.info() returns:
> Sys.info()
sysname release
"Linux" "3.10.0-1160.102.1.el7.x86_64"
version nodename
"#1 SMP Tue Oct 17 15:42:21 UTC 2023" "localhost.localdomain"
machine login
"x86_64" "song"
user effective_user
"song" "song"The content is too long, to be short, library(slendr) worked fine but init_env() reported an error message: "No module named 'numpy'" and all requirements could not be deteced this time by check_env().
> library(slendr)
> init_env()
Error in py_run_file_impl(file, local, convert) :
ModuleNotFoundError: No module named 'numpy'
Run `reticulate::py_last_error()` for details.
> check_env()
# >>>>>>>>>>>>>>>>>>>>>> ERROR REPORT <<<<<<<<<<<<<<<<<<<<<<
Traceback (most recent call last):
File "/home/sparrow/.local/share/r-miniconda/lib/python3.11/site-packages/ conda/exception_handler.py", line 17, in __call__
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/home/sparrow/.local/share/r-miniconda/lib/python3.11/site-packages/ conda/cli/main.py", line 110, in main_sourced
print(activator.execute(), end="")
^^^^^^^^^^^^^^^^^^^
File "/home/sparrow/.local/share/r-miniconda/lib/python3.11/site-packages/ conda/activate.py", line 203, in execute
return getattr(self, self.command)()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/sparrow/.local/share/r-miniconda/lib/python3.11/site-packages/ conda/activate.py", line 168, in activate
builder_result = self.build_activate(self.env_name_or_prefix)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/sparrow/.local/share/r-miniconda/lib/python3.11/site-packages/ conda/activate.py", line 347, in build_activate
return self._build_activate_stack(env_name_or_prefix, False)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/sparrow/.local/share/r-miniconda/lib/python3.11/site-packages/ conda/activate.py", line 426, in _build_activate_stack
self._replace_prefix_in_path(old_conda_prefix, prefix)
File "/home/sparrow/.local/share/r-miniconda/lib/python3.11/site-packages/ conda/activate.py", line 681, in _replace_prefix_in_path
if path_list[last_idx + 1] == library_bin_dir:
~~~~~~~~~^^^^^^^^^^^^^^
IndexError: list index out of range
`$ /home/sparrow/.local/share/r-miniconda/bin/conda shell.posix activate`
environment variables:
CIO_TEST=<not set>
CLASSPATH=/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.345.b01-
1.el7_9.x86_64//lib/tools.jar:/usr/lib/jvm/java-1.8.0- openjdk-
1.8.0.345.b01-1.el7_9.x86_64//lib/dt.jar:/usr/lib/jvm/ java-1.8.0-
openjdk-1.8.0.345.b01-1.el7_9.x86_64//lib
CMAKE_PREFIX_PATH=/home/sparrow/.conda/envs/rgdal:/home/sparrow/.conda/e nvs/rgdal/x86_64
-conda-linux-gnu/sysroot/usr
CONDA_BUILD_SYSROOT=/home/sparrow/.conda/envs/rgdal/x86_64-conda-linux-gnu /sysroot
CONDA_DEFAULT_ENV=rgdal
CONDA_EXE=/home/sparrow/.local/share/r-miniconda/bin/conda
CONDA_PREFIX=/home/sparrow/.conda/envs/rgdal
CONDA_PREFIX_1=/home/share/Anaconda/Anaconda_install
CONDA_PROMPT_MODIFIER=(rgdal)
CONDA_PYTHON_EXE=/home/sparrow/.local/share/r-miniconda/bin/python
CONDA_ROOT=/home/sparrow/.local/share/r-miniconda
CONDA_SHLVL=2
CONDA_TOOLCHAIN_BUILD=x86_64-conda-linux-gnu
CONDA_TOOLCHAIN_HOST=x86_64-conda-linux-gnu
CURL_CA_BUNDLE=<not set>
C_INCLUDE_PATH=/usr/include
GDAL_DRIVER_PATH=/home/sparrow/.conda/envs/rgdal/lib/gdalplugins
JAVA_LD_LIBRARY_PATH=/home/sparrow/.conda/envs/rgdal/jre/lib/amd64/server
LD_LIBRARY_PATH=/home/sparrow/.conda/envs/new/jre/lib/amd64/server/:/h ome/sparrow/.con
da/envs/new/jre/lib/amd64/server
LD_PRELOAD=<not set>
PATH=/home/sparrow/.local/share/r-
miniconda/condabin:/home/sparrow/.local/share/r-
miniconda/bin:/home/sparrow/.local/share/r-
miniconda/condabin:/home/sparrow/.local/share/r-minico nda/envs/Python-
3.11_msprime-1.2.0_tskit-0.5.6_pyslim-1.0.4_tspop-
0.0.2/bin:/home/sparrow/.local/share/r-
miniconda/condabin:/home/sparrow/.local/share/r-
miniconda/bin:/home/sparrow/.local/share/r-
miniconda/condabin:/home/sparrow/.local/share/r-
miniconda/bin:/home/sparrow/.jenv/shims:/home/sparrow/ .jenv/bin:/home/
sparrow/.aspera/connect/bin:/home/sparrow/.local/share /r-
miniconda/bin:/home/share/Anaconda/Anaconda_install/co ndabin:/disk3/hk
qm/badmixture/code:/disk3/hkqm/volcanofinder/SF2:/disk 3/hkqm/volcanofi
nder/volcanofinder_v1.0:/disk3/hkqm/baypass/baypass_pu blic-master/sour
ces:/home/xueboning/software/paml4.9j/bin:/home/xuebon ing/software/Par
aAT2.0:/home/xueboning/software/KaKs_Calculator2.0/src :/home/sparrow/s
oftware/Dsuite/Build:/home/zhangshuai/download:/home/s hare/EMBOSS-
6.6.0/ajax/pcre:/usr/lib/jvm/java-1.8.0-openjdk-1.8.0. 345.b01-
1.el7_9.x86_64/bin:/usr/java/jre1.8.0_151/bin:/usr/jav a/jre1.8.0_151/b
in:/opt/tsce4/maui/sbin:/opt/tsce4/maui/bin:/opt/tsce4 /torque6/bin:/op
t/tsce4/torque6/sbin:/home/share/rmblast-
2.10.0/bin:/home/share/bedtools:/home/share/AdmixTools /bin:/home/share
/beast/bin:/home/share/Anaconda/Anaconda_install/bin:/ home/sparrow/.as
pera/connect/bin:/home/sparrow/software/bedops/bin:/ho me/share/delly/s
rc:/home/share/ncbi-blast-
2.12.0+/bin:/home/share/lastz/src:/home/share/bowtie2- 2.4.4-linux-
x86_64:/home/share/paup:/var/lib/snapd/snap/dmd/102/bi n:/home/sparrow/
software/msmc2-2.1.3/build/release:/home/cyl_temp/soft ware/sambada-
0.8.3-ubuntu/binaries:/home/share/proj-
8.1.0/build/bin:/disk2/prunella/software/discoal:/usr/ local/bin:/usr/l
ocal/bin:/usr/bin:/usr/local/sbin:/usr/sbin:/var/lib/s napd/snap/bin:/h
ome/sparrow:/home/share/bcftools-1.9:/home/share/bwa-
0.7.17:/home/share/samtools-1.9:/home/share/gatk-
4.1.8.1:/home/share/plink_1.9:/home/share/plink_2.0:/h ome/share/vcftoo
ls_0.1.13/bin:/home/zhangshuai/bin/sratoolkit.3.0.0-
centos_linux64/bin:/home/caoqiansheng/.aspera/connect/ bin:/home/sparro
w/.local/bin:/home/sparrow/bin:/home/sparrow/.conda/en vs/rgdal/bin/x86
_64-conda-linux-gnu-c++:/home/sparrow/.conda/envs/rgda l/bin
PYTHONPATH=:/home/sparrow/software/kobas-3.0/src
QT_PLUGIN_PATH=/usr/lib64/kde4/plugins:/usr/lib/kde4/plugins
REQUESTS_CA_BUNDLE=<not set>
SSL_CERT_FILE=<not set>
UDUNITS2_XML_PATH=/home/sparrow/.conda/envs/rgdal/share/udunits/udunits2 .xml
active environment : rgdal
active env location : /home/sparrow/.conda/envs/rgdal
shell level : 2
user config file : /home/sparrow/.condarc
populated config files : /home/sparrow/.condarc
conda version : 23.11.0
conda-build version : not installed
python version : 3.11.5.final.0
solver : libmamba (default)
virtual packages : __archspec=1=cascadelake
__conda=23.11.0=0
__glibc=2.17=0
__linux=3.10.0=0
__unix=0=0
base environment : /home/sparrow/.local/share/r-miniconda (writable)
conda av data dir : /home/sparrow/.local/share/r-miniconda/etc/conda
conda av metadata url : None
channel URLs : https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/bi oconda/linux-64
https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/bi oconda/noarch
https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/co nda-forge/linux-64
https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/co nda-forge/noarch
https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/mai n/linux-64
https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/mai n/noarch
https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/fre e/linux-64
https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/fre e/noarch
package cache : /home/sparrow/.local/share/r-miniconda/pkgs
/home/sparrow/.conda/pkgs
envs directories : /home/sparrow/.local/share/r-miniconda/envs
/home/sparrow/.conda/envs
platform : linux-64
user-agent : conda/23.11.0 requests/2.31.0 CPython/3.11.5 Linux/3.1 0.0-1160.11.1.el7.x86_64 centos/7.9.2009 glibc/2.17 solver/libmamba conda-libmam ba-solver/23.12.0 libmambapy/1.5.3
UID:GID : 1000:1000
netrc file : None
offline mode : False
An unexpected error has occurred. Conda has prepared the above report.
If you suspect this error is being caused by a malfunctioning plugin,
consider using the --no-plugins option to turn off plugins.
Example: conda --no-plugins install <package>
Alternatively, you can set the CONDA_NO_PLUGINS environment variable on
the command line to run the command without plugins enabled.
Example: CONDA_NO_PLUGINS=true conda install <package>
Timeout reached. No report sent.
# >>>>>>>>>>>>>>>>>>>>>> ERROR REPORT <<<<<<<<<<<<<<<<<<<<<<
Traceback (most recent call last):
File "/home/sparrow/.local/share/r-miniconda/lib/python3.11/site-packages/ conda/exception_handler.py", line 17, in __call__
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/home/sparrow/.local/share/r-miniconda/lib/python3.11/site-packages/ conda/cli/main.py", line 110, in main_sourced
print(activator.execute(), end="")
^^^^^^^^^^^^^^^^^^^
File "/home/sparrow/.local/share/r-miniconda/lib/python3.11/site-packages/ conda/activate.py", line 203, in execute
return getattr(self, self.command)()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/sparrow/.local/share/r-miniconda/lib/python3.11/site-packages/ conda/activate.py", line 168, in activate
builder_result = self.build_activate(self.env_name_or_prefix)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/sparrow/.local/share/r-miniconda/lib/python3.11/site-packages/ conda/activate.py", line 347, in build_activate
return self._build_activate_stack(env_name_or_prefix, False)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/sparrow/.local/share/r-miniconda/lib/python3.11/site-packages/ conda/activate.py", line 426, in _build_activate_stack
self._replace_prefix_in_path(old_conda_prefix, prefix)
File "/home/sparrow/.local/share/r-miniconda/lib/python3.11/site-packages/ conda/activate.py", line 681, in _replace_prefix_in_path
if path_list[last_idx + 1] == library_bin_dir:
~~~~~~~~~^^^^^^^^^^^^^^
IndexError: list index out of range
`$ /home/sparrow/.local/share/r-miniconda/bin/conda shell.posix activate /home/s parrow/.local/share/r-miniconda/envs/Python-3.11_msprime-1.2.0_tskit-0.5.6_pysli m-1.0.4_tspop-0.0.2`
environment variables:
CIO_TEST=<not set>
CLASSPATH=/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.345.b01-
1.el7_9.x86_64//lib/tools.jar:/usr/lib/jvm/java-1.8.0- openjdk-
1.8.0.345.b01-1.el7_9.x86_64//lib/dt.jar:/usr/lib/jvm/ java-1.8.0-
openjdk-1.8.0.345.b01-1.el7_9.x86_64//lib
CMAKE_PREFIX_PATH=/home/sparrow/.conda/envs/rgdal:/home/sparrow/.conda/e nvs/rgdal/x86_64
-conda-linux-gnu/sysroot/usr
CONDA_BUILD_SYSROOT=/home/sparrow/.conda/envs/rgdal/x86_64-conda-linux-gnu /sysroot
CONDA_DEFAULT_ENV=rgdal
CONDA_EXE=/home/sparrow/.local/share/r-miniconda/bin/conda
CONDA_PREFIX=/home/sparrow/.conda/envs/rgdal
CONDA_PREFIX_1=/home/share/Anaconda/Anaconda_install
CONDA_PROMPT_MODIFIER=(rgdal)
CONDA_PYTHON_EXE=/home/sparrow/.local/share/r-miniconda/bin/python
CONDA_ROOT=/home/sparrow/.local/share/r-miniconda
CONDA_SHLVL=2
CONDA_TOOLCHAIN_BUILD=x86_64-conda-linux-gnu
CONDA_TOOLCHAIN_HOST=x86_64-conda-linux-gnu
CURL_CA_BUNDLE=<not set>
C_INCLUDE_PATH=/usr/include
GDAL_DRIVER_PATH=/home/sparrow/.conda/envs/rgdal/lib/gdalplugins
JAVA_LD_LIBRARY_PATH=/home/sparrow/.conda/envs/rgdal/jre/lib/amd64/server
LD_LIBRARY_PATH=/home/sparrow/.conda/envs/new/jre/lib/amd64/server/:/h ome/sparrow/.con
da/envs/new/jre/lib/amd64/server
LD_PRELOAD=<not set>
PATH=/home/sparrow/.local/share/r-
miniconda/condabin:/home/sparrow/.local/share/r-
miniconda/bin:/home/sparrow/.local/share/r-
miniconda/condabin:/home/sparrow/.local/share/r-minico nda/envs/Python-
3.11_msprime-1.2.0_tskit-0.5.6_pyslim-1.0.4_tspop-
0.0.2/bin:/home/sparrow/.local/share/r-
miniconda/condabin:/home/sparrow/.local/share/r-
miniconda/bin:/home/sparrow/.local/share/r-
miniconda/condabin:/home/sparrow/.local/share/r-
miniconda/bin:/home/sparrow/.jenv/shims:/home/sparrow/ .jenv/bin:/home/
sparrow/.aspera/connect/bin:/home/sparrow/.local/share /r-
miniconda/bin:/home/share/Anaconda/Anaconda_install/co ndabin:/disk3/hk
qm/badmixture/code:/disk3/hkqm/volcanofinder/SF2:/disk 3/hkqm/volcanofi
nder/volcanofinder_v1.0:/disk3/hkqm/baypass/baypass_pu blic-master/sour
ces:/home/xueboning/software/paml4.9j/bin:/home/xuebon ing/software/Par
aAT2.0:/home/xueboning/software/KaKs_Calculator2.0/src :/home/sparrow/s
oftware/Dsuite/Build:/home/zhangshuai/download:/home/s hare/EMBOSS-
6.6.0/ajax/pcre:/usr/lib/jvm/java-1.8.0-openjdk-1.8.0. 345.b01-
1.el7_9.x86_64/bin:/usr/java/jre1.8.0_151/bin:/usr/jav a/jre1.8.0_151/b
in:/opt/tsce4/maui/sbin:/opt/tsce4/maui/bin:/opt/tsce4 /torque6/bin:/op
t/tsce4/torque6/sbin:/home/share/rmblast-
2.10.0/bin:/home/share/bedtools:/home/share/AdmixTools /bin:/home/share
/beast/bin:/home/share/Anaconda/Anaconda_install/bin:/ home/sparrow/.as
pera/connect/bin:/home/sparrow/software/bedops/bin:/ho me/share/delly/s
rc:/home/share/ncbi-blast-
2.12.0+/bin:/home/share/lastz/src:/home/share/bowtie2- 2.4.4-linux-
x86_64:/home/share/paup:/var/lib/snapd/snap/dmd/102/bi n:/home/sparrow/
software/msmc2-2.1.3/build/release:/home/cyl_temp/soft ware/sambada-
0.8.3-ubuntu/binaries:/home/share/proj-
8.1.0/build/bin:/disk2/prunella/software/discoal:/usr/ local/bin:/usr/l
ocal/bin:/usr/bin:/usr/local/sbin:/usr/sbin:/var/lib/s napd/snap/bin:/h
ome/sparrow:/home/share/bcftools-1.9:/home/share/bwa-
0.7.17:/home/share/samtools-1.9:/home/share/gatk-
4.1.8.1:/home/share/plink_1.9:/home/share/plink_2.0:/h ome/share/vcftoo
ls_0.1.13/bin:/home/zhangshuai/bin/sratoolkit.3.0.0-
centos_linux64/bin:/home/caoqiansheng/.aspera/connect/ bin:/home/sparro
w/.local/bin:/home/sparrow/bin:/home/sparrow/.conda/en vs/rgdal/bin/x86
_64-conda-linux-gnu-c++:/home/sparrow/.conda/envs/rgda l/bin
PYTHONPATH=:/home/sparrow/software/kobas-3.0/src
QT_PLUGIN_PATH=/usr/lib64/kde4/plugins:/usr/lib/kde4/plugins
REQUESTS_CA_BUNDLE=<not set>
SSL_CERT_FILE=<not set>
UDUNITS2_XML_PATH=/home/sparrow/.conda/envs/rgdal/share/udunits/udunits2 .xml
active environment : rgdal
active env location : /home/sparrow/.conda/envs/rgdal
shell level : 2
user config file : /home/sparrow/.condarc
populated config files : /home/sparrow/.condarc
conda version : 23.11.0
conda-build version : not installed
python version : 3.11.5.final.0
solver : libmamba (default)
virtual packages : __archspec=1=cascadelake
__conda=23.11.0=0
__glibc=2.17=0
__linux=3.10.0=0
__unix=0=0
base environment : /home/sparrow/.local/share/r-miniconda (writable)
conda av data dir : /home/sparrow/.local/share/r-miniconda/etc/conda
conda av metadata url : None
channel URLs : https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/bi oconda/linux-64
https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/bi oconda/noarch
https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/co nda-forge/linux-64
https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/co nda-forge/noarch
https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/mai n/linux-64
https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/mai n/noarch
https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/fre e/linux-64
https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/fre e/noarch
package cache : /home/sparrow/.local/share/r-miniconda/pkgs
/home/sparrow/.conda/pkgs
envs directories : /home/sparrow/.local/share/r-miniconda/envs
/home/sparrow/.conda/envs
platform : linux-64
user-agent : conda/23.11.0 requests/2.31.0 CPython/3.11.5 Linux/3.1 0.0-1160.11.1.el7.x86_64 centos/7.9.2009 glibc/2.17 solver/libmamba conda-libmam ba-solver/23.12.0 libmambapy/1.5.3
UID:GID : 1000:1000
netrc file : None
offline mode : False
An unexpected error has occurred. Conda has prepared the above report.
If you suspect this error is being caused by a malfunctioning plugin,
consider using the --no-plugins option to turn off plugins.
Example: conda --no-plugins install <package>
Alternatively, you can set the CONDA_NO_PLUGINS environment variable on
the command line to run the command without plugins enabled.
Example: CONDA_NO_PLUGINS=true conda install <package>
Timeout reached. No report sent.
Summary of the currently active Python environment:
Python binary: /home/sparrow/.local/share/r-miniconda/envs/Python-3.11_msprime-1.2.0_tskit-0.5.6_pyslim-1.0.4_tspop-0.0.2/bin/python
Python version: 3.11.7 | packaged by conda-forge | (main, Dec 23 2023, 14:43:09) [GCC 12.3.0]
slendr requirements:
- tskit: MISSING ❌
- msprime: MISSING ❌
- pyslim: MISSING ❌
- tspop: MISSING ❌
Note that due to the technical limitations of embedded Python, if you
want to switch to another Python environment you will need to restart
your R session first.
> setup_env()
A required slendr Python environment is already present. You can activate
it by calling init_env().
Then I clear the env and reinstall it:
> clear_env()
Are you sure you want to delete the automatically created slendr Python
environment? It is located in:
/home/song/miniconda3/envs/Python-3.11_msprime-1.2.0_tskit-0.5.6_pyslim-1.0.4_tspop-0.0.2/
If you remove it, you can create it again by running`setup_env()`
without any arguments in a new R session.
1: No
2: Yes
Selection: 2
+ /home/song/miniconda3/bin/conda 'remove' '--yes' '--name' 'Python-3.11_msprime-1.2.0_tskit-0.5.6_pyslim-1.0.4_tspop-0.0.2' '--all'
Remove all packages in environment /home/song/miniconda3/envs/Python-3.11_msprime-1.2.0_tskit-0.5.6_pyslim-1.0.4_tspop-0.0.2:
## Package Plan ##
environment location: /home/song/miniconda3/envs/Python-3.11_msprime-1.2.0_tskit-0.5.6_pyslim-1.0.4_tspop-0.0.2
The following packages will be REMOVED:
_libgcc_mutex-0.1-conda_forge
_openmp_mutex-4.5-2_gnu
bzip2-1.0.8-hd590300_5
ca-certificates-2023.11.17-hbcca054_0
ld_impl_linux-64-2.40-h41732ed_0
libexpat-2.5.0-hcb278e6_1
libffi-3.4.2-h7f98852_5
libgcc-ng-13.2.0-h807b86a_3
libgomp-13.2.0-h807b86a_3
libnsl-2.0.1-hd590300_0
libsqlite-3.44.2-h2797004_0
libuuid-2.38.1-h0b41bf4_0
libxcrypt-4.4.36-hd590300_1
libzlib-1.2.13-hd590300_5
ncurses-6.4-h59595ed_2
openssl-3.2.0-hd590300_1
pip-23.3.2-pyhd8ed1ab_0
python-3.11.7-hab00c5b_1_cpython
readline-8.2-h8228510_1
setuptools-69.0.3-pyhd8ed1ab_0
tk-8.6.13-noxft_h4845f30_101
tzdata-2023d-h0c530f3_0
wheel-0.42.0-pyhd8ed1ab_0
xz-5.2.6-h166bdaf_0
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
The slendr Python environment has been sucessfully removed.
> setup_env()
This function will install a completely isolated Miniconda Python distribution
just for slendr and create an environment with all required Python modules.
Everything will be installed into a completely separate location into an
isolated environment in an R library directory. This won't affect your other
Python installations at all. You can always wipe out the automatically created
environment by running clear_env().
Do you wish to proceed with the automated Python environment setup?
1: No
2: Yes
Selection: 2
=======================================================================
Installing slendr's Python environment. Please wait until
the installation procedure finishes. Do NOT interrupt the
process while the installation is still running.
======================================================================
+ /home/song/miniconda3/bin/conda 'create' '--yes' '--name' 'Python-3.11_msprime -1.2.0_tskit-0.5.6_pyslim-1.0.4_tspop-0.0.2' 'python=3.11' '--quiet' '-c' 'conda -forge'
Retrieving notices: ...working... done
Collecting package metadata (current_repodata.json): ...working... done
Solving environment: ...working... done
## Package Plan ##
environment location: /home/song/miniconda3/envs/Python-3.11_msprime-1.2.0_tsk it-0.5.6_pyslim-1.0.4_tspop-0.0.2
added / updated specs:
- python=3.11
The following NEW packages will be INSTALLED:
_libgcc_mutex conda-forge/linux-64::_libgcc_mutex-0.1-conda_forge
_openmp_mutex conda-forge/linux-64::_openmp_mutex-4.5-2_gnu
bzip2 conda-forge/linux-64::bzip2-1.0.8-hd590300_5
ca-certificates conda-forge/linux-64::ca-certificates-2023.11.17-hbcca054_0
ld_impl_linux-64 conda-forge/linux-64::ld_impl_linux-64-2.40-h41732ed_0
libexpat conda-forge/linux-64::libexpat-2.5.0-hcb278e6_1
libffi conda-forge/linux-64::libffi-3.4.2-h7f98852_5
libgcc-ng conda-forge/linux-64::libgcc-ng-13.2.0-h807b86a_3
libgomp conda-forge/linux-64::libgomp-13.2.0-h807b86a_3
libnsl conda-forge/linux-64::libnsl-2.0.1-hd590300_0
libsqlite conda-forge/linux-64::libsqlite-3.44.2-h2797004_0
libuuid conda-forge/linux-64::libuuid-2.38.1-h0b41bf4_0
libxcrypt conda-forge/linux-64::libxcrypt-4.4.36-hd590300_1
libzlib conda-forge/linux-64::libzlib-1.2.13-hd590300_5
ncurses conda-forge/linux-64::ncurses-6.4-h59595ed_2
openssl conda-forge/linux-64::openssl-3.2.0-hd590300_1
pip conda-forge/noarch::pip-23.3.2-pyhd8ed1ab_0
python conda-forge/linux-64::python-3.11.7-hab00c5b_1_cpython
readline conda-forge/linux-64::readline-8.2-h8228510_1
setuptools conda-forge/noarch::setuptools-69.0.3-pyhd8ed1ab_0
tk conda-forge/linux-64::tk-8.6.13-noxft_h4845f30_101
tzdata conda-forge/noarch::tzdata-2023d-h0c530f3_0
wheel conda-forge/noarch::wheel-0.42.0-pyhd8ed1ab_0
xz conda-forge/linux-64::xz-5.2.6-h166bdaf_0
Preparing transaction: ...working... done
Verifying transaction: ...working... done
Executing transaction: ...working... done
+ /home/song/miniconda3/bin/conda 'install' '--yes' '--name' 'Python-3.11_msprim e-1.2.0_tskit-0.5.6_pyslim-1.0.4_tspop-0.0.2' '-c' 'conda-forge' 'msprime==1.2.0 ' 'tskit==0.5.6' 'pyslim==1.0.4'
Collecting package metadata (current_repodata.json): done
Solving environment: unsuccessful initial attempt using frozen solve. Retrying w ith flexible solve.
Collecting package metadata (repodata.json): done
Solving environment: done
==> WARNING: A newer version of conda exists. <==
current version: 23.7.4
latest version: 23.11.0
Please update conda by running
$ conda update -n base -c conda-forge conda
Or to minimize the number of packages updated during conda update use
conda install conda=23.11.0
## Package Plan ##
environment location: /home/song/miniconda3/envs/Python-3.11_msprime-1.2.0_tsk it-0.5.6_pyslim-1.0.4_tspop-0.0.2
added / updated specs:
- msprime==1.2.0
- pyslim==1.0.4
- tskit==0.5.6
The following packages will be downloaded:
package | build
---------------------------|-----------------
humanize-4.9.0 | pyhd8ed1ab_0 64 KB conda-forge
importlib-metadata-7.0.1 | pyha770c72_0 26 KB conda-forge
importlib_metadata-7.0.1 | hd8ed1ab_0 9 KB conda-forge
libblas-3.9.0 |21_linux64_openblas 14 KB conda-forge
libcblas-3.9.0 |21_linux64_openblas 14 KB conda-forge
liblapack-3.9.0 |21_linux64_openblas 14 KB conda-forge
libopenblas-0.3.26 |pthreads_h413a1c8_0 5.3 MB conda-forge
msprime-1.2.0 | py311hf9c4b16_3 434 KB conda-forge
numpy-1.26.3 | py311h64a7726_0 7.8 MB conda-forge
python_abi-3.11 | 4_cp311 6 KB conda-forge
------------------------------------------------------------
Total: 13.7 MB
The following NEW packages will be INSTALLED:
attrs conda-forge/noarch::attrs-23.2.0-pyh71513ae_0
demes conda-forge/noarch::demes-0.2.3-pyhd8ed1ab_0
gsl conda-forge/linux-64::gsl-2.7-he838d99_0
humanize conda-forge/noarch::humanize-4.9.0-pyhd8ed1ab_0
importlib-metadata conda-forge/noarch::importlib-metadata-7.0.1-pyha770c72_0
importlib_metadata conda-forge/noarch::importlib_metadata-7.0.1-hd8ed1ab_0
importlib_resourc~ conda-forge/noarch::importlib_resources-6.1.1-pyhd8ed1ab_0
jsonschema conda-forge/noarch::jsonschema-4.21.1-pyhd8ed1ab_0
jsonschema-specif~ conda-forge/noarch::jsonschema-specifications-2023.12.1-pyh d8ed1ab_0
kastore conda-forge/linux-64::kastore-0.3.2-py311h1f0f07a_2
libblas conda-forge/linux-64::libblas-3.9.0-21_linux64_openblas
libcblas conda-forge/linux-64::libcblas-3.9.0-21_linux64_openblas
libgfortran-ng conda-forge/linux-64::libgfortran-ng-13.2.0-h69a702a_3
libgfortran5 conda-forge/linux-64::libgfortran5-13.2.0-ha4646dd_3
liblapack conda-forge/linux-64::liblapack-3.9.0-21_linux64_openblas
libopenblas conda-forge/linux-64::libopenblas-0.3.26-pthreads_h413a1c8_ 0
libstdcxx-ng conda-forge/linux-64::libstdcxx-ng-13.2.0-h7e041cc_3
msprime conda-forge/linux-64::msprime-1.2.0-py311hf9c4b16_3
numpy conda-forge/linux-64::numpy-1.26.3-py311h64a7726_0
pkgutil-resolve-n~ conda-forge/noarch::pkgutil-resolve-name-1.3.10-pyhd8ed1ab_ 1
pyparsing conda-forge/noarch::pyparsing-3.1.1-pyhd8ed1ab_0
pyslim conda-forge/noarch::pyslim-1.0.4-pyhd8ed1ab_0
python_abi conda-forge/linux-64::python_abi-3.11-4_cp311
referencing conda-forge/noarch::referencing-0.32.1-pyhd8ed1ab_0
rpds-py conda-forge/linux-64::rpds-py-0.17.1-py311h46250e7_0
ruamel.yaml conda-forge/linux-64::ruamel.yaml-0.18.5-py311h459d7ec_0
ruamel.yaml.clib conda-forge/linux-64::ruamel.yaml.clib-0.2.7-py311h459d7ec_ 2
six conda-forge/noarch::six-1.16.0-pyh6c4a22f_0
svgwrite conda-forge/noarch::svgwrite-1.4.3-pyhd8ed1ab_0
tskit conda-forge/linux-64::tskit-0.5.6-py311h1f0f07a_0
zipp conda-forge/noarch::zipp-3.17.0-pyhd8ed1ab_0
Downloading and Extracting Packages
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
+ . /home/song/miniconda3/bin/activate
+ conda activate 'Python-3.11_msprime-1.2.0_tskit-0.5.6_pyslim-1.0.4_tspop-0.0.2 '
+ '/home/song/miniconda3/envs/Python-3.11_msprime-1.2.0_tskit-0.5.6_pyslim-1.0.4 _tspop-0.0.2/bin/python' -m pip install --upgrade --no-user 'tspop==0.0.2'
Requirement already satisfied: tspop==0.0.2 in ./.local/lib/python3.11/site-pack ages (0.0.2)
Requirement already satisfied: tskit>=0.2.3 in ./.local/lib/python3.11/site-pack ages (from tspop==0.0.2) (0.5.6)
Requirement already satisfied: pandas>=1.2.0 in ./.local/lib/python3.11/site-pac kages (from tspop==0.0.2) (2.2.0)
Requirement already satisfied: numpy>=1.21.0 in ./miniconda3/envs/Python-3.11_ms prime-1.2.0_tskit-0.5.6_pyslim-1.0.4_tspop-0.0.2/lib/python3.11/site-packages (f rom tspop==0.0.2) (1.26.3)
Requirement already satisfied: matplotlib>=3.4.0 in ./.local/lib/python3.11/site -packages (from tspop==0.0.2) (3.8.2)
Requirement already satisfied: contourpy>=1.0.1 in ./.local/lib/python3.11/site- packages (from matplotlib>=3.4.0->tspop==0.0.2) (1.2.0)
Requirement already satisfied: cycler>=0.10 in ./.local/lib/python3.11/site-pack ages (from matplotlib>=3.4.0->tspop==0.0.2) (0.12.1)
Requirement already satisfied: fonttools>=4.22.0 in ./.local/lib/python3.11/site -packages (from matplotlib>=3.4.0->tspop==0.0.2) (4.47.2)
Requirement already satisfied: kiwisolver>=1.3.1 in ./.local/lib/python3.11/site -packages (from matplotlib>=3.4.0->tspop==0.0.2) (1.4.5)
Requirement already satisfied: packaging>=20.0 in ./.local/lib/python3.11/site-p ackages (from matplotlib>=3.4.0->tspop==0.0.2) (23.2)
Requirement already satisfied: pillow>=8 in ./.local/lib/python3.11/site-package s (from matplotlib>=3.4.0->tspop==0.0.2) (10.2.0)
Requirement already satisfied: pyparsing>=2.3.1 in ./.local/lib/python3.11/site- packages (from matplotlib>=3.4.0->tspop==0.0.2) (3.1.1)
Requirement already satisfied: python-dateutil>=2.7 in ./.local/lib/python3.11/s ite-packages (from matplotlib>=3.4.0->tspop==0.0.2) (2.8.2)
Requirement already satisfied: pytz>=2020.1 in ./.local/lib/python3.11/site-pack ages (from pandas>=1.2.0->tspop==0.0.2) (2023.3.post1)
Requirement already satisfied: tzdata>=2022.7 in ./.local/lib/python3.11/site-pa ckages (from pandas>=1.2.0->tspop==0.0.2) (2023.4)
Requirement already satisfied: jsonschema>=3.0.0 in ./.local/lib/python3.11/site -packages (from tskit>=0.2.3->tspop==0.0.2) (4.21.1)
Requirement already satisfied: svgwrite>=1.1.10 in ./.local/lib/python3.11/site- packages (from tskit>=0.2.3->tspop==0.0.2) (1.4.3)
Requirement already satisfied: attrs>=22.2.0 in ./.local/lib/python3.11/site-pac kages (from jsonschema>=3.0.0->tskit>=0.2.3->tspop==0.0.2) (23.2.0)
Requirement already satisfied: jsonschema-specifications>=2023.03.6 in ./.local/ lib/python3.11/site-packages (from jsonschema>=3.0.0->tskit>=0.2.3->tspop==0.0.2 ) (2023.12.1)
Requirement already satisfied: referencing>=0.28.4 in ./.local/lib/python3.11/si te-packages (from jsonschema>=3.0.0->tskit>=0.2.3->tspop==0.0.2) (0.32.1)
Requirement already satisfied: rpds-py>=0.7.1 in ./.local/lib/python3.11/site-pa ckages (from jsonschema>=3.0.0->tskit>=0.2.3->tspop==0.0.2) (0.17.1)
Requirement already satisfied: six>=1.5 in ./.local/lib/python3.11/site-packages (from python-dateutil>=2.7->matplotlib>=3.4.0->tspop==0.0.2) (1.16.0)
======================================================================
Python environment for slendr has been successfuly created, and the R
interface to msprime, tskit, and pyslim modules has been activated.
In future sessions, activate this environment by calling init_env().
=======================================================================
> check_env()
Summary of the currently active Python environment:
Python binary: /home/song/miniconda3/envs/Python-3.11_msprime-1.2.0_tskit-0.5.6_pyslim-1.0.4_tspop-0.0.2/bin/python
Python version: 3.11.7 | packaged by conda-forge | (main, Dec 23 2023, 14:43:09) [GCC 12.3.0]
slendr requirements:
- tskit: version 0.5.6 ✓
- msprime: version 1.3.0 ✓
- pyslim: version 1.0.4 ✓
- tspop: present ✓Everything looked good until I run the example:
> #running the example
model <- read_model(path = system.file("extdata/models/introgression", package = "slendr"))
afr <- model$populations[["AFR"]]
eur <- model$populations[["EUR"]]
chimp <- model$populations[["CH"]]
modern_samples <- schedule_sampling(model, times = 0, list(afr, 5), list(eur, 5), list(chimp, 1))
ancient_samples <- schedule_sampling(model, times = c(30000, 20000, 10000), list(eur, 1))
samples <- rbind(modern_samples, ancient_samples)
> ts <- slim(model, sequence_length = 1e4, recombination_rate = 0, samples = samples)
Error in as.logical(test) :
cannot coerce type 'environment' to vector of type 'logical'
> ts_msprime <- msprime(model, sequence_length = 10e4, recombination_rate = 1e-8)
/home/song/miniconda3/envs/sf/lib/R/library/slendr/extdata/models/introgression/script.py:19: DeprecationWarning:
Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),
(to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)
but was not found to be installed on your system.
If this would cause problems for you,
please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466
import pandas
Error in if (attr(ts, "spatial")) check_spatial_pkgs() :
Missing values cannot be used where TRUE/FALSE values are requiredI had no idea about how to solve the error prodeced by slim(), so I tried to deal with the second one by
pip install pandas Pyarrow, and the slendr worked smoothly finally!
I will close this issue for now. Many thanks to your instructions!
bodkan
commented
10 months ago Wait. How did you run pip install ... and where? This to me sounds all wrong (apples and oranges type of situation). :D Also, just BTW, the pyarrow message is a pandas warning (not error!), and had nothing to do with your error which came from R, not Python.
I still have no idea what's going on. I don't think any of this would fix the issues you were getting and if it looks like it did, then I suspect the problem was with something different then slendr. But I am not going to argue, if you're happy, then I'm happy :D but again -- the issues you were describing appear to be unrelated and somehow involve a deeper issue with Python environment, not with R/slendr itself.
If you want to close this, go ahead. 👍
bodkan
commented
10 months ago Also, for next time (in case there's next time -- I really do hope you fixed your problems!): please try not to add new messages one after the other with further errors, or with further updates. It's better to work together, one issue at a time.
Debugging involves doing investigation step by step, first checking one thing, making sure it works, then proceeding with another thing, etc., until we hit the root of a problem. This is especially important with remote troubleshooting -- if I had direct access to your computer, things would be very easy. But because I don't, it's important to lockstep and test one thing at a time. This is frustratingly slow for all parties, but it's the only way to figure out what's the problem because otherwise it's impossible for me to know what's the exact status of your system.
For instance, with the environment problems you started with, I quickly lost track with what's going on -- how you could have a dysfunctional environment at one point, and then suddenly (presumably running the same setup_env(), init_env(), etc.) have a working environment.
Anyway, just a recommendation which I think applies for reporting bugs on GitHub in general, not just slendr. :)
Good luck with your modelling!
willright28
commented
10 months ago I think the key is to open a fresh terminal and reinstall the env. But I'm afraid I have even less idea of how this problem was resolved.
Your suggestions and recommendations are vey sincere and useful, I will keep that in mind! :D
janxkoci
commented
8 months ago I already noticed that in some situations the slendr environment works the first time it's installed, but stops working in subsequent sessions. One such situation was with the radian console, which is written in Python and locks a Python version and path before slendr gets a chance to activate its own tools (curiously, the jupyter-console works fine). I think I've read somewhere in the docs or issues that RStudio may have similar problems too (I don't use it, so I cannot confirm that).
bodkan
commented
8 months ago Hmmm, yes. I remember running into this issue back when I first started developing slendr (before it was even called slendr).
I used to be a radian user and I seem to remember that the fact that it's opinionated about enforcing a Python interpreter pulled a rug from under R packages which wanted to use their own Python virtual environments... I think it might be even the reason why I stopped using radian back then, even though it otherwise provided a very pleasant user experience.
curiously, the jupyter-console works fine
Do you mean that running R/slendr inside something like jupyter console --kernel=ir (or whatever it is that starts an R REPL in a Jupyter console) works OK? Interesting. Maybe it's because radian-the-Python-software communicates with the R process at a lower level by embedding it, whereas Jupyter employs a client-server architecture, so the R kernel and console are two separate processes which exchange messages via the Jupyter protocol. In the latter case, R and Python processes wouldn't actually be linked in that case, avoiding the problem?
Anyway, sorry this has been annoying for you! As I said, I ran into the same issues ~3 years ago and gave up on radian because of this. 😬
However, let me note this issue down and check whether there's been some progress about this and maybe even a possible solution.
(It is VERY weird that you say that things work on the first try with radian... but break on subsequent runs. This is surprising to me.)
bodkan
commented
8 months ago OK, so I just tried this hack and it works. Basically, I can take the Python interpreter installed in slendr's own Python virtual environment, install radian there and when I run radian, it's running under from that isolated slendr environment (it's basically installed alongside tskit, msprime, and other slendr dependencies):
[Ignore the fact that the stuff below is run under root -- I do all my work in isolated Docker containers.]
> slendr::check_env()
Summary of the currently active Python environment:
Python binary: /root/.local/share/r-miniconda/envs/Python-3.12_msprime-1.3.1_tskit-0.5.6_pyslim-1.0.4_tspop-0.0.2/bin/python
Python version: 3.12.2 | packaged by conda-forge | (main, Feb 16 2024, 20:50:58) [GCC 12.3.0]
slendr requirements:
- tskit: version 0.5.6 ✓
- msprime: version 1.3.1 ✓
- pyslim: version 1.0.4 ✓
- tspop: present ✓ /root/.local/share/r-miniconda/envs/Python-3.12_msprime-1.3.1_tskit-0.5.6_pyslim-1.0.4_tspop-0.0.2/bin/pip install radian/root/.local/share/r-miniconda/envs/Python-3.12_msprime-1.3.1_tskit-0.5.6_pyslim-1.0.4_tspop-0.0.2/bin/radian
r$> library(slendr)
r$> init_env()
The interface to all required Python modules has been activated.
r$> check_env()
Summary of the currently active Python environment:
Python binary: /root/.local/share/r-miniconda/envs/Python-3.12_msprime-1.3.1_tskit-0.5.6_pyslim-1.0.4_tspop-0.0.2/bin/python3.12
Python version: 3.12.2 | packaged by conda-forge | (main, Feb 16 2024, 20:50:58) [GCC 12.3.0]
slendr requirements:
- tskit: version 0.5.6 ✓
- msprime: version 1.3.1 ✓
- pyslim: version 1.0.4 ✓
- tspop: present ✓No idea how sensible or scalable it is though. To arrive at a perfect solution will probably require digging in radian and its documentation, because this must be related to the fact that -- as you pointed out -- it enforces its own Python before other R packages (like slendr) can activate their own environments.
Also, this is not just slendr -- tensorflow, keras, and other fancy reticulated-Python interfaces made by RStudio and others will have the same problem. So looking at how people work with those libraries under radian might give some hints.
janxkoci
commented
8 months ago Hi @bodkan, you are probably right about the jupyter-console doing a better job at keeping Python away from its kernels, likely leveraging the jupyter protocol.
It is VERY weird that you say that things work on the first try with radian... but break on subsequent runs. This is surprising to me.
A word on my setup - I use conda to install most of my science software. For R, I often have some general working environment plus a few special environments for complex packages, like admixtools2 or slendr.
So my slendr is installed in it's own environment (called slendr), along with radian (and now jupyter-console + r-irkernel). So the first time I run radian from the new environment and install slendr, it works because the Python version is the same the whole session. But when I exit radian and try to run it again, slendr no longer works, because this time there is the conflict between the Python versions of radian vs the Python slendr wants to load. Something like that.
From the above it's clear I cannot install radian in the other environment (with tskit) because that environment doesn't even have R in it.
One more question - is there a reason why slendr creates 3 different conda environments, each with different Python version? Is it a limitation of the reticulate package perhaps?
bodkan
commented
8 months ago OK, I see. Yes, that is a bit of a pain. I'm not entirely sure how to help here though because the issue appears to be caused by design of radian itself. I see that it's even explicitly specified here. Unfortunately, I don't see a way around this that wouldn't be a complete hack. :( The bottom line is, it shouldn't be radian's business to enforce which Python environment does a user use. Perhaps bringing up the issue with radian's devs is the way to go here.
One more question - is there a reason why slendr creates 3 different conda environments, each with different Python version? Is it a limitation of the reticulate package perhaps?
Can you elaborate on what you mean by this? slendr always has only one Python virtual environment active at a time. Of course, when some Python dependencies are updated, running setup_env() creates a new environment just for them (that's why the environment has such a long name with version numbers given directly in the name), for reproducibility.
That said, leftover Python environments can be selectively cleared by running clear_env(all = TRUE).
Or do you mean something else?
janxkoci
commented
8 months ago Hi, radian is not a priority for me at the moment, as I can use jupyter-console in its place. Maybe at some point I will let the author know.
About conda environments - I mean slendr will create 3 distinct conda envs after fresh install. I tried this on multiple machines, with the same effect. I even tried CRAN vs Github version on different machines at some point, and I always get 3 envs, like this (here is a list from my laptop):
$ mamba env list
# conda environments:
#
/home/jena/.local/share/r-miniconda
/home/jena/.local/share/r-miniconda/envs/Python-3.11_msprime-1.2.0_tskit-0.5.6_pyslim-1.0.4
/home/jena/.local/share/r-miniconda/envs/r-reticulate
base * /home/jena/mambaforge
admix /home/jena/mambaforge/envs/admix
admix-lgo /home/jena/mambaforge/envs/admix-lgo
julia /home/jena/mambaforge/envs/julia
noradian /home/jena/mambaforge/envs/noradian
radian /home/jena/mambaforge/envs/radian
rbio /home/jena/mambaforge/envs/rbio
rpak /home/jena/mambaforge/envs/rpak
rplot /home/jena/mambaforge/envs/rplot
slendr /home/jena/mambaforge/envs/slendr
testslendr /home/jena/mambaforge/envs/testslendrApparently, one is just for conda, another for reticulate, and the last one for tskit and friends.
You can even see this (partially) above in a comment by OP - the logs posted show how the installation progresses through several environments.
And here is the list of python versions:
$ for e in /home/jena/.local/share/r-miniconda /home/jena/.local/share/r-miniconda/envs/Python-3.11_msprime-1.2.0_tskit-0.5.6_pyslim-1.0.4 /home/jena/.local/share/r-miniconda/envs/r-reticulate /home/jena/mambaforge/envs/slendr; do echo $e; mamba list -p $e | awk '$1=="python"'; done
/home/jena/.local/share/r-miniconda
python 3.11.5 h955ad1f_0
/home/jena/.local/share/r-miniconda/envs/Python-3.11_msprime-1.2.0_tskit-0.5.6_pyslim-1.0.4
python 3.11.6 hab00c5b_0_cpython conda-forge
/home/jena/.local/share/r-miniconda/envs/r-reticulate
python 3.9.18 h0755675_0_cpython conda-forge
/home/jena/mambaforge/envs/slendr
python 3.12.0 hab00c5b_0_cpython conda-forgeActually, I have a few other issues with conda envs, so I should probably open a new issue, rather than spamming here...
bodkan
commented
8 months ago About conda environments - I mean slendr will create 3 distinct conda envs after fresh install. I tried this on multiple machines, with the same effect. I even tried CRAN vs Github version on different machines at some point, and I always get 3 envs, like this (here is a list from my laptop):
$ mamba env list # conda environments: # /home/jena/.local/share/r-miniconda /home/jena/.local/share/r-miniconda/envs/Python-3.11_msprime-1.2.0_tskit-0.5.6_pyslim-1.0.4 /home/jena/.local/share/r-miniconda/envs/r-reticulate
Ah, yes! I see what you mean now. So the first two are not actually slendr environments or even created by slendr -- whenever you use reticulate in R, it downloads its own miniconda (unless it already downloaded it before) separately from any other Python on a user’s machine in order not to mess with anything else on the system. And, I suppose while it’s at it, it also creates a dedicated r-reticulate environment specifically for reticulate. That’s why they are unnamed? Not actually to be used from the shell I guess?
I honestly don’t know why they create this r-reticulate environment. My suspicion is that reticulate wants to make it possible to install Python modules for R users who don't really know how Python works or what even is a virtual environment, to have some environment as a default with the first being something like conda’s “base”?
In all honesty, I’m actually a well-known and loud conda hater. :D The only reason I use it inside slendr is to have a cross-platform way to download python.exe or python binaries from within R (many of my users don’t even have Python installed on their computers and have never run Python). So I don’t really know much about the details, I’m afraid.
Actually, I have a few other issues with conda envs, so I should probably open a new issue, rather than spamming here...
I agree. As I said, I can’t really support conda specific stuff but if you ran into errors which I can do something about, I’m happy to try.
janxkoci
commented
8 months ago I think your speculation about reticulate makes sense. I've opened a new issue to continue our discussion of conda environments and my specific problems.
I’m actually a well-known and loud conda hater. :D
I already noticed your hating ;) I know conda is not perfect, but then I remember the old ways and I could never go back!
bhaller
commented
8 months ago @bodkan One of many conversation topics for us when I visit Copenhagen is to hear about why you're a conda hater; I'm very curious. I don't use it, and am kind of suspicious of it, but mostly it's the suspicion of a caveman who sees other cavemen using sticks as tools, and says "Ugh, me no like sticks." I have no real basis for my suspicion, just a fear of change and of things I don't understand. :->
Hi @bodkan ,
A small question, running slim get error message:"Error in py_get_attr_impl(x, name, silent) : AttributeError: module 'main' has no attribute 'get_pedigree_ids'".
check_env looks all right: slendr requirements:
Thanks for your time!