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Create Conda Environment with YAML File

Hello, I'm trying to follow these instructions to create a conda environment with this YAML file but the environment keeps getting stuck on solving.

name: p2b1
dependencies:
- python=3.7.5
- scipy=1.5.3
- keras=2.4.3
- h5py=2.10.0
- numpy=1.19.5
- tensorflow-gpu=2.2.0
- pandas=1.2.0
- scikit-learn=0.24.0
- tqdm=4.56.0
- matplotlib=3.3.3
- numba=0.52.0
- astropy=4.2
- patsy=0.5.1
- statsmodels=0.12.1.

It works when I only include numpy in the list of packages and add conda forge and defaults into the YAML file. I am using conda version 23.3.1 Any way to resolve this?

python
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updated by dthorbur dthorbur • written by cthangav • cthangav

Please also provide the error messages and command line used, otherwise we can't see what is going wrong.

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written by dthorbur dthorbur

I used this command: conda env create -f python_environment.yml -n P2B1

And there's no error message, just that it gets stuck on solving the environment for hours until my terminal times out.

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written by cthangav • cthangav

You can also try using mamba, I find it can often solve environments that base conda struggles with.

EDIT, only just noticed that it was micromamba that was suggested below as an answer, I originally misread that as miniconda.

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written by dthorbur dthorbur

Which system are you on? I also noticed that base conda is hardly usable anymore on our systems. In contrast, solving your environment with micromamba took 30 seconds.

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written by Michael Dondrup Michael Dondrup

1 answer

It worked for me. It may just take a long time because there are a lot of dependencies to resolve. Try micromamba instead for a faster solve. And once you have the environment, export it completely into a yaml file. This should also help to speed the solving up the next time you install it.

Here is the solved environment:

name: p2b1
channels:
- conda-forge
- pkgs/main
dependencies:
- _libgcc_mutex=0.1=conda_forge
- _openmp_mutex=4.5=2_gnu
- _tflow_select=2.1.0=gpu
- absl-py=2.1.0=pyhd8ed1ab_0
- aiohttp=3.7.4.post0=py37h5e8e339_1
- astor=0.8.1=pyh9f0ad1d_0
- astropy=4.2.1=py37h5e8e339_0
- astunparse=1.6.3=pyhd8ed1ab_0
- async-timeout=3.0.1=py_1000
- attrs=23.2.0=pyh71513ae_0
- blinker=1.6.3=pyhd8ed1ab_0
- brotli-python=1.0.9=py37hd23a5d3_7
- c-ares=1.27.0=hd590300_0
- ca-certificates=2024.2.2=hbcca054_0
- cachetools=5.3.3=pyhd8ed1ab_0
- certifi=2024.2.2=pyhd8ed1ab_0
- cffi=1.14.6=py37hc58025e_0
- chardet=4.0.0=py37h89c1867_3
- charset-normalizer=3.3.2=pyhd8ed1ab_0
- click=8.1.3=py37h89c1867_0
- cryptography=39.0.1=py37h9ce1e76_0
- cudatoolkit=10.1.243=h6d9799a_13
- cudnn=7.6.5.32=hc0a50b0_1
- cupti=10.1.168=0
- cycler=0.11.0=pyhd8ed1ab_0
- dbus=1.13.18=hb2f20db_0
- expat=2.6.2=h59595ed_0
- fontconfig=2.14.2=h14ed4e7_0
- freetype=2.12.1=h267a509_2
- gast=0.3.3=py_0
- glib=2.69.1=h4ff587b_1
- google-auth=2.28.2=pyhca7485f_0
- google-auth-oauthlib=0.4.6=pyhd8ed1ab_0
- google-pasta=0.2.0=pyh8c360ce_0
- grpc-cpp=1.48.1=h05bd8bd_1
- grpcio=1.48.1=py37h3fae8ff_1
- gst-plugins-base=1.14.1=h6a678d5_1
- gstreamer=1.14.1=h5eee18b_1
- h5py=2.10.0=nompi_py37ha3df211_106
- hdf5=1.10.6=nompi_h6a2412b_1114
- icu=73.2=h59595ed_0
- idna=3.6=pyhd8ed1ab_0
- importlib-metadata=4.11.4=py37h89c1867_0
- joblib=1.3.2=pyhd8ed1ab_0
- jpeg=9e=h0b41bf4_3
- keras=2.4.3=pyhd8ed1ab_0
- keras-preprocessing=1.1.2=pyhd8ed1ab_0
- keyutils=1.6.1=h166bdaf_0
- kiwisolver=1.4.4=py37h7cecad7_0
- krb5=1.20.1=hf9c8cef_0
- lcms2=2.12=hddcbb42_0
- ld_impl_linux-64=2.40=h41732ed_0
- lerc=3.0=h9c3ff4c_0
- libabseil=20220623.0=cxx17_h05df665_6
- libblas=3.9.0=20_linux64_openblas
- libcblas=3.9.0=20_linux64_openblas
- libclang=14.0.6=default_h7634d5b_1
- libclang13=14.0.6=default_h9986a30_1
- libcups=2.3.3=h36d4200_3
- libcurl=7.87.0=h6312ad2_0
- libdeflate=1.10=h7f98852_0
- libedit=3.1.20191231=he28a2e2_2
- libev=4.33=hd590300_2
- libexpat=2.6.2=h59595ed_0
- libffi=3.3=h58526e2_2
- libgcc-ng=13.2.0=h807b86a_5
- libgfortran-ng=13.2.0=h69a702a_5
- libgfortran5=13.2.0=ha4646dd_5
- libgomp=13.2.0=h807b86a_5
- libiconv=1.17=hd590300_2
- liblapack=3.9.0=20_linux64_openblas
- libllvm10=10.0.1=he513fc3_3
- libllvm14=14.0.6=hcd5def8_4
- libnghttp2=1.51.0=hdcd2b5c_0
- libopenblas=0.3.25=pthreads_h413a1c8_0
- libpng=1.6.43=h2797004_0
- libpq=12.15=h37d81fd_1
- libprotobuf=3.21.8=h6239696_0
- libsqlite=3.45.2=h2797004_0
- libssh2=1.10.0=haa6b8db_3
- libstdcxx-ng=13.2.0=h7e041cc_5
- libtiff=4.3.0=h0fcbabc_4
- libuuid=2.38.1=h0b41bf4_0
- libwebp-base=1.3.2=hd590300_0
- libxcb=1.15=h0b41bf4_0
- libxkbcommon=1.6.0=hd429924_1
- libxml2=2.12.5=h232c23b_0
- libzlib=1.2.13=hd590300_5
- llvmlite=0.35.0=py37h9d7f4d0_1
- markdown=3.5.2=pyhd8ed1ab_0
- markupsafe=2.1.1=py37h540881e_1
- matplotlib=3.3.3=py37h89c1867_0
- matplotlib-base=3.3.3=py37h0c9df89_0
- multidict=6.0.2=py37h540881e_1
- mysql=5.7.20=hf484d3e_1001
- ncurses=6.4=h59595ed_2
- numba=0.52.0=py37hdc94413_0
- numpy=1.19.5=py37h3e96413_3
- oauthlib=3.2.2=pyhd8ed1ab_0
- olefile=0.47=pyhd8ed1ab_0
- openjpeg=2.5.0=h7d73246_0
- openssl=1.1.1w=hd590300_0
- opt_einsum=3.3.0=pyhc1e730c_2
- packaging=23.2=pyhd8ed1ab_0
- pandas=1.2.0=py37hdc94413_1
- patsy=0.5.1=py_0
- pcre=8.45=h9c3ff4c_0
- pillow=8.4.0=py37h0f21c89_0
- pip=24.0=pyhd8ed1ab_0
- protobuf=4.21.8=py37hd23a5d3_0
- pthread-stubs=0.4=h36c2ea0_1001
- pyasn1=0.5.1=pyhd8ed1ab_0
- pyasn1-modules=0.3.0=pyhd8ed1ab_0
- pycparser=2.21=pyhd8ed1ab_0
- pyerfa=2.0.0.1=py37hda87dfa_2
- pyjwt=2.8.0=pyhd8ed1ab_1
- pyopenssl=23.2.0=pyhd8ed1ab_1
- pyparsing=3.1.2=pyhd8ed1ab_0
- pyqt=5.15.4=py37hd23a5d3_0
- pyqt5-sip=12.9.0=py37hd23a5d3_0
- pysocks=1.7.1=py37h89c1867_5
- python=3.7.5=hffdb5ce_0_cpython
- python-dateutil=2.9.0=pyhd8ed1ab_0
- python_abi=3.7=4_cp37m
- pytz=2024.1=pyhd8ed1ab_0
- pyu2f=0.1.5=pyhd8ed1ab_0
- pyyaml=6.0=py37h540881e_4
- qt-main=5.15.2=h110a718_10
- re2=2022.06.01=h27087fc_1
- readline=8.2=h8228510_1
- requests=2.31.0=pyhd8ed1ab_0
- requests-oauthlib=1.4.0=pyhd8ed1ab_0
- rsa=4.9=pyhd8ed1ab_0
- scikit-learn=0.24.0=py37h69acf81_0
- scipy=1.5.3=py37h14a347d_0
- setuptools=59.8.0=py37h89c1867_1
- sip=6.5.1=py37hcd2ae1e_2
- six=1.16.0=pyh6c4a22f_0
- sqlite=3.45.2=h2c6b66d_0
- statsmodels=0.12.1=py37h902c9e0_2
- tensorboard=2.11.2=pyhd8ed1ab_0
- tensorboard-data-server=0.6.0=py37h38fbfac_2
- tensorboard-plugin-wit=1.8.1=pyhd8ed1ab_0
- tensorflow=2.2.0=gpu_py37h1a511ff_0
- tensorflow-base=2.2.0=gpu_py37h8a81be8_0
- tensorflow-estimator=2.6.0=py37hcd2ae1e_0
- tensorflow-gpu=2.2.0=h0d30ee6_0
- termcolor=2.3.0=pyhd8ed1ab_0
- threadpoolctl=3.1.0=pyh8a188c0_0
- tk=8.6.13=noxft_h4845f30_101
- toml=0.10.2=pyhd8ed1ab_0
- tornado=6.2=py37h540881e_0
- tqdm=4.56.0=pyhd8ed1ab_0
- typing-extensions=4.7.1=hd8ed1ab_0
- typing_extensions=4.7.1=pyha770c72_0
- urllib3=2.2.1=pyhd8ed1ab_0
- werkzeug=2.2.3=pyhd8ed1ab_0
- wheel=0.42.0=pyhd8ed1ab_0
- wrapt=1.14.1=py37h540881e_0
- xkeyboard-config=2.41=hd590300_0
- xorg-kbproto=1.0.7=h7f98852_1002
- xorg-libx11=1.8.7=h8ee46fc_0
- xorg-libxau=1.0.11=hd590300_0
- xorg-libxdmcp=1.1.3=h7f98852_0
- xorg-xextproto=7.3.0=h0b41bf4_1003
- xorg-xproto=7.0.31=h7f98852_1007
- xz=5.2.6=h166bdaf_0
- yaml=0.2.5=h7f98852_2
- yarl=1.7.2=py37h540881e_2
- zipp=3.15.0=pyhd8ed1ab_0
- zlib=1.2.13=hd590300_5
- zstd=1.5.5=hfc55251_0
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written by Michael Dondrup Michael Dondrup

To tack on this suggestion to make the solving faster, pixi is another faster way to work with conda.

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written by Wayne Wayne

Good to know, which version of conda are you using? And which channels did you use to create the environment? I may be missing a needed channel.

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written by cthangav • cthangav 
(p2b1) ubuntu@ubuntu-compute:~$ micromamba --version
1.5.3

I have tested this in a Ubuntu 22 LTS VM that is using the BioStar handbook bioinfo setup (insecure connection). Additional channels enabled are bioconda, R, and conda-forge, however there doesn't seem to be a package from bioconda:

 libmamba version : 1.5.3
 micromamba version : 1.5.3


 channels : https://conda.anaconda.org/conda-forge/linux-64
                          https://conda.anaconda.org/conda-forge/noarch
                          https://conda.anaconda.org/bioconda/linux-64
                          https://conda.anaconda.org/bioconda/noarch
                          https://repo.anaconda.com/pkgs/main/linux-64
                          https://repo.anaconda.com/pkgs/main/noarch
                          https://repo.anaconda.com/pkgs/r/linux-64
                          https://repo.anaconda.com/pkgs/r/noarch 
  platform : linux-64

I will post the full environment.

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written by Michael Dondrup Michael Dondrup

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