Answers.Body: <p><code>pip</code> and <code>conda</code> don't mix and good advice is don't ever mix them. Thus to avoid this delete your old environment, create a new <code>conda</code> environment, or use a <code>conda</code> environment where <code>pip</code> has not been used ...</p>
  <pre><code>conda install -c anaconda scikit-learn=0.18.2 
  </code></pre>
  <p>If you are using <code>pip</code> it is recommended to use it only with <code>virtualenv</code> <code>venv</code>. If there is a dependency issue delete the environment and start over is much easier.</p>
  <p>The rationale is for not mixing them is:</p>
  <ul>
  <li><code>conda</code> installs lots of stuff not just Python and it gets the <code>env</code> (environment) right for this purpose</li>
  <li><code>pip</code> only installs Python within a Python environment</li>
  </ul>
  <hr />
  <p>The simple answer is</p>
  <pre><code>conda install -c bioconda deepbgc
  </code></pre>
  <p>conda will then install the correct version of scikit-learn automatically. If doing this it important it is in its own (new) <code>conda</code> environment however.</p>
  <p>If the above doesn't work further stuff can be done, but the 'simple answer' should work.</p>
  <hr />
  <p>@Joe_G says its hanging ... on <code>solving environment</code> just leave it ... you will then see why,</p>
  <pre><code>The following NEW packages will be INSTALLED:
  
    _tflow_select      pkgs/main/osx-64::_tflow_select-2.3.0-mkl
    absl-py            pkgs/main/noarch::absl-py-0.15.0-pyhd3eb1b0_0
    appdirs            pkgs/main/noarch::appdirs-1.4.4-pyhd3eb1b0_0
    astor              pkgs/main/osx-64::astor-0.8.1-py37hecd8cb5_0
    biopython          pkgs/main/osx-64::biopython-1.76-py37h1de35cc_0
    blas               pkgs/main/osx-64::blas-1.0-mkl
    bottleneck         pkgs/main/osx-64::bottleneck-1.3.5-py37h67323c0_0
    brotli             pkgs/main/osx-64::brotli-1.0.9-hca72f7f_7
    brotli-bin         pkgs/main/osx-64::brotli-bin-1.0.9-hca72f7f_7
    c-ares             pkgs/main/osx-64::c-ares-1.18.1-hca72f7f_0
    ca-certificates    pkgs/main/osx-64::ca-certificates-2022.07.19-hecd8cb5_0
    certifi            pkgs/main/osx-64::certifi-2022.9.14-py37hecd8cb5_0
    cycler             pkgs/main/noarch::cycler-0.11.0-pyhd3eb1b0_0
    dataclasses        pkgs/main/noarch::dataclasses-0.8-pyh6d0b6a4_7
    deepbgc            bioconda/noarch::deepbgc-0.1.23-py_0
    fftw               pkgs/main/osx-64::fftw-3.3.9-h9ed2024_1
    fonttools          pkgs/main/noarch::fonttools-4.25.0-pyhd3eb1b0_0
    freetype           pkgs/main/osx-64::freetype-2.11.0-hd8bbffd_0
    gast               pkgs/main/noarch::gast-0.5.3-pyhd3eb1b0_0
    giflib             pkgs/main/osx-64::giflib-5.2.1-haf1e3a3_0
    grpcio             pkgs/main/osx-64::grpcio-1.42.0-py37ha29bfda_0
    h5py               pkgs/main/osx-64::h5py-3.7.0-py37h4a1dd59_0
    hdf5               pkgs/main/osx-64::hdf5-1.10.6-h10fe05b_1
    hmmer              bioconda/osx-64::hmmer-3.3.2-h9722bc1_2
    importlib-metadata pkgs/main/osx-64::importlib-metadata-4.11.3-py37hecd8cb5_0
    intel-openmp       pkgs/main/osx-64::intel-openmp-2021.4.0-hecd8cb5_3538
    joblib             pkgs/main/noarch::joblib-1.1.0-pyhd3eb1b0_0
    jpeg               pkgs/main/osx-64::jpeg-9e-hca72f7f_0
    keras              pkgs/main/osx-64::keras-2.2.4-0
    keras-applications pkgs/main/noarch::keras-applications-1.0.8-py_1
    keras-base         pkgs/main/osx-64::keras-base-2.2.4-py37_0
    keras-preprocessi~ pkgs/main/noarch::keras-preprocessing-1.1.2-pyhd3eb1b0_0
    kiwisolver         pkgs/main/osx-64::kiwisolver-1.4.2-py37he9d5cce_0
    lcms2              pkgs/main/osx-64::lcms2-2.12-hf1fd2bf_0
    lerc               pkgs/main/osx-64::lerc-3.0-he9d5cce_0
    libbrotlicommon    pkgs/main/osx-64::libbrotlicommon-1.0.9-hca72f7f_7
    libbrotlidec       pkgs/main/osx-64::libbrotlidec-1.0.9-hca72f7f_7
    libbrotlienc       pkgs/main/osx-64::libbrotlienc-1.0.9-hca72f7f_7
    libcxx             pkgs/main/osx-64::libcxx-14.0.6-h9765a3e_0
    libdeflate         pkgs/main/osx-64::libdeflate-1.8-h9ed2024_5
    libffi             bioconda/osx-64::libffi-3.2.1-1
    libgfortran        pkgs/main/osx-64::libgfortran-5.0.0-11_2_0_h246ff09_26
    libgfortran5       pkgs/main/osx-64::libgfortran5-11.2.0-h246ff09_26
    libpng             pkgs/main/osx-64::libpng-1.6.37-ha441bb4_0
    libprotobuf        pkgs/main/osx-64::libprotobuf-3.20.1-h8346a28_0
    libtiff            pkgs/main/osx-64::libtiff-4.4.0-h2ef1027_0
    libwebp            pkgs/main/osx-64::libwebp-1.2.2-h56c3ce4_0
    libwebp-base       pkgs/main/osx-64::libwebp-base-1.2.2-hca72f7f_0
    llvm-openmp        pkgs/main/osx-64::llvm-openmp-14.0.6-h0dcd299_0
    lz4-c              pkgs/main/osx-64::lz4-c-1.9.3-h23ab428_1
    markdown           pkgs/main/osx-64::markdown-3.3.4-py37hecd8cb5_0
    matplotlib-base    pkgs/main/osx-64::matplotlib-base-3.5.2-py37hfb0c5b7_0
    mkl                pkgs/main/osx-64::mkl-2021.4.0-hecd8cb5_637
    mkl-service        pkgs/main/osx-64::mkl-service-2.4.0-py37h9ed2024_0
    mkl_fft            pkgs/main/osx-64::mkl_fft-1.3.1-py37h4ab4a9b_0
    mkl_random         pkgs/main/osx-64::mkl_random-1.2.2-py37hb2f4e1b_0
    munkres            bioconda/noarch::munkres-1.0.7-py_1
    ncurses            pkgs/main/osx-64::ncurses-6.3-hca72f7f_3
    numexpr            pkgs/main/osx-64::numexpr-2.8.3-py37h2e5f0a9_0
    numpy              pkgs/main/osx-64::numpy-1.21.5-py37h2e5f0a9_3
    numpy-base         pkgs/main/osx-64::numpy-base-1.21.5-py37h3b1a694_3
    openssl            pkgs/main/osx-64::openssl-1.1.1q-hca72f7f_0
    packaging          pkgs/main/noarch::packaging-21.3-pyhd3eb1b0_0
    pandas             pkgs/main/osx-64::pandas-1.3.5-py37h743cdd8_0
    pillow             pkgs/main/osx-64::pillow-9.2.0-py37hde71d04_1
    pip                pkgs/main/osx-64::pip-22.2.2-py37hecd8cb5_0
    prodigal           bioconda/osx-64::prodigal-2.6.3-ha5712d3_4
    protobuf           pkgs/main/osx-64::protobuf-3.20.1-py37he9d5cce_0
    pyparsing          pkgs/main/osx-64::pyparsing-3.0.9-py37hecd8cb5_0
    python             pkgs/main/osx-64::python-3.7.7-hc70fcce_0_cpython
    python-dateutil    pkgs/main/noarch::python-dateutil-2.8.2-pyhd3eb1b0_0
    pytz               pkgs/main/osx-64::pytz-2022.1-py37hecd8cb5_0
    pyyaml             pkgs/main/osx-64::pyyaml-6.0-py37hca72f7f_1
    readline           pkgs/main/osx-64::readline-8.1.2-hca72f7f_1
    scikit-learn       pkgs/main/osx-64::scikit-learn-1.0.2-py37hae1ba45_1
    scipy              pkgs/main/osx-64::scipy-1.7.3-py37h214d14d_2
    setuptools         pkgs/main/osx-64::setuptools-63.4.1-py37hecd8cb5_0
    six                pkgs/main/noarch::six-1.16.0-pyhd3eb1b0_1
    sqlite             pkgs/main/osx-64::sqlite-3.39.3-h707629a_0
    tensorboard        pkgs/main/osx-64::tensorboard-1.14.0-py37h80053f4_0
    tensorflow         pkgs/main/osx-64::tensorflow-1.14.0-mkl_py37h085be34_0
    tensorflow-base    pkgs/main/osx-64::tensorflow-base-1.14.0-mkl_py37h5a24fda_0
    tensorflow-estima~ pkgs/main/noarch::tensorflow-estimator-1.14.0-py_0
    termcolor          pkgs/main/osx-64::termcolor-1.1.0-py37hecd8cb5_1
    threadpoolctl      pkgs/main/noarch::threadpoolctl-2.2.0-pyh0d69192_0
    tk                 pkgs/main/osx-64::tk-8.6.12-h5d9f67b_0
    typing_extensions  pkgs/main/osx-64::typing_extensions-4.3.0-py37hecd8cb5_0
    werkzeug           pkgs/main/noarch::werkzeug-2.0.3-pyhd3eb1b0_0
    wheel              pkgs/main/noarch::wheel-0.37.1-pyhd3eb1b0_0
    wrapt              pkgs/main/osx-64::wrapt-1.14.1-py37hca72f7f_0
    xz                 pkgs/main/osx-64::xz-5.2.6-hca72f7f_0
    yaml               pkgs/main/osx-64::yaml-0.2.5-haf1e3a3_0
    zipp               pkgs/main/osx-64::zipp-3.8.0-py37hecd8cb5_0
    zlib               pkgs/main/osx-64::zlib-1.2.12-h4dc903c_3
    zstd               pkgs/main/osx-64::zstd-1.5.2-hcb37349_0
  
  Proceed ([y]/n)? 
  </code></pre>
  <p>Its an enormous data pipeline. Everything is there, thats why it takes so long.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-09-30T17:27:20.040Z
Answers.Text: Hi, thanks for your response. I went ahead and created a new conda environment and tried to run the deepbgc install on there with conda instead of pip. The problem now is the install is getting stuck at the "Solving Environment" phase. For whatever reason, It doesn't seem to make it past that point.
Answers.UserDisplayName: Joe_G
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-10-01T02:22:46.493Z
Answers.Text: Hi @Joe_G I've updated the post, so did it work?
Answers.UserDisplayName: M__
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-10-01T20:23:34.187Z
Answers.Text: I've found [mamba](https://mamba.readthedocs.io) to be a life-saver for getting around conda's slowness with large sets of packages.  Its `mamba` command can act as a drop-in replacement for `conda` for most purposes and most importantly it solves dependencies *much* faster.
Answers.UserDisplayName: Jesse
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-10-03T14:01:59.017Z
Answers.Text: Unfortunately it never got past the solving environment stage. I was installing it on a remote server and the process took so long that the my user was disconnected from the server before it could finish. I'm going to try again thinking maybe it was an issue with the server. @Jesse I may try Mamba that sounds like it could be helpful. Is that just a package installation? As mentioned before, the warning message wasn't code breaking so I may just be living with it for the time being. I do appreciate the guidance, thanks!
Answers.UserDisplayName: Joe_G
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-10-03T15:18:56.000Z
Answers.Text: Thanks for your feedback @Joe_G . Personally `conda` has been the most stable environment and package management system I've used. Upvotes are always appreciated BTW.
Answers.UserDisplayName: M__
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-10-03T17:06:47.343Z
Answers.Text: Will do @M_ Thanks again!
Answers.UserDisplayName: Joe_G
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-10-03T21:36:45.773Z
Answers.Text: Yes mamba itself is just an anaconda package so it's a simple install.  You have to install it into the base environment though (something like `conda install mamba -n base -c conda-forge` to get the latest one from conda-forge.)
Answers.UserDisplayName: Jesse
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-09-29T19:29:23.737Z
Answers.LastActivityDate: 2022-09-30T17:58:56.480Z
Answers.LastEditDate: 2022-09-30T17:58:56.480Z
Answers.UserDisplayName: M__
Body: <p>I am trying to get the bioinformatics tool <code>deepbgc</code> up and running. Now I have created a <code>conda</code> environment and have currently installed <code>deepbgc</code> onto it. Now when I run the tool, the program works but it outputs the following warning message as a result:</p>
  <pre><code> /EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages/sklearn/base.py:306:
   UserWarning: Trying to unpickle estimator RandomForestClassifier from version 0.18.2 
   when using version 0.21.3. This might lead to breaking code or invalid results. Use at your own risk.  
  </code></pre>
  <p>This led me to believe that the program is trying to utilize an older version of the <code>scikit-learn</code> package (<code>version 0.18.2</code> instead of the currently installed 0.21.3 version) for this <code>RandomForestClassifer</code> estimator. This pointed me to the next logical solution of downgrading my current version of <code>scikit-learn</code>. So, I ran a simple <code>pip</code> install of the older package version:</p>
  <pre><code>pip install scikit-learn==0.18.2
  </code></pre>
  <p>For some reason, the package downgrade failed and outputted the following error:</p>
  <pre><code>    error: Command &quot;g++ -pthread -B /EFS/tools/miniconda/envs/deepbgc2/compiler_compat -
  Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -
  I/EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages/numpy/core/include -
  I/EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages/numpy/core/include -
  I/EFS/tools/miniconda/envs/deepbgc2/include/python3.7m -c 
  sklearn/cluster/_dbscan_inner.cpp -o build/temp.linux-x86_64-cpython-
  37/sklearn/cluster/_dbscan_inner.o -MMD -MF build/temp.linux-x86_64-cpython-
  37/sklearn/cluster/_dbscan_inner.o.d&quot; failed with exit status 1
  
        [end of output]
    
    note: This error originates from a subprocess, and is likely not a problem with pip.
    WARNING: No metadata found in /EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages
    Rolling back uninstall of scikit-learn
    Moving to /EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages/scikit_learn-0.21.3.dist-info/
     from /EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages/~cikit_learn-0.21.3.dist-info
    Moving to /EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages/sklearn/
     from /EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages/~klearn
  error: legacy-install-failure
  
  × Encountered error while trying to install package.
  ╰─&gt; scikit-learn
  
  note: This is an issue with the package mentioned above, not `pip`.
  
  </code></pre>
  <p>Currently, I have <code>Python</code> version <code>3.7</code> installed on the environment and version 22.1.2 of <code>pip</code>. Any guidance appreciated, thanks!</p>
  
Tags: <python><deeptools><conda><scipy>
Title: pip installation within conda env: Error downgrading scikit-learn - WARNING: No metadata
ThreadText: # pip installation within conda env: Error downgrading scikit-learn - WARNING: No metadata
  
  (Asked by: username_0 on 2022-09-29)
  
  I am trying to get the bioinformatics tool `deepbgc` up and running. Now I have created a `conda` environment and have currently installed `deepbgc` onto it. Now when I run the tool, the program works but it outputs the following warning message as a result:
  
  ```
   /EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages/sklearn/base.py:306:
   UserWarning: Trying to unpickle estimator RandomForestClassifier from version 0.18.2 
   when using version 0.21.3. This might lead to breaking code or invalid results. Use at your own risk.  
  
  ```
  
  This led me to believe that the program is trying to utilize an older version of the `scikit-learn` package (`version 0.18.2` instead of the currently installed 0.21.3 version) for this `RandomForestClassifer` estimator. This pointed me to the next logical solution of downgrading my current version of `scikit-learn`. So, I ran a simple `pip` install of the older package version:
  
  ```
  pip install scikit-learn==0.18.2
  
  ```
  
  For some reason, the package downgrade failed and outputted the following error:
  
  ```
      error: Command "g++ -pthread -B /EFS/tools/miniconda/envs/deepbgc2/compiler_compat -
  Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -
  I/EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages/numpy/core/include -
  I/EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages/numpy/core/include -
  I/EFS/tools/miniconda/envs/deepbgc2/include/python3.7m -c 
  sklearn/cluster/_dbscan_inner.cpp -o build/temp.linux-x86_64-cpython-
  37/sklearn/cluster/_dbscan_inner.o -MMD -MF build/temp.linux-x86_64-cpython-
  37/sklearn/cluster/_dbscan_inner.o.d" failed with exit status 1
  
        [end of output]
    
    note: This error originates from a subprocess, and is likely not a problem with pip.
    WARNING: No metadata found in /EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages
    Rolling back uninstall of scikit-learn
    Moving to /EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages/scikit_learn-0.21.3.dist-info/
     from /EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages/~cikit_learn-0.21.3.dist-info
    Moving to /EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages/sklearn/
     from /EFS/tools/miniconda/envs/deepbgc2/lib/python3.7/site-packages/~klearn
  error: legacy-install-failure
  
  × Encountered error while trying to install package.
  ╰─> scikit-learn
  
  note: This is an issue with the package mentioned above, not `pip`.
  
  ```
  
  Currently, I have `Python` version `3.7` installed on the environment and version 22.1.2 of `pip`. Any guidance appreciated, thanks!
  
  **Tags:** python, deeptools, conda, scipy
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2022-09-29. Score: 1
  
  `pip` and `conda` don't mix and good advice is don't ever mix them. Thus to avoid this delete your old environment, create a new `conda` environment, or use a `conda` environment where `pip` has not been used ...
  
  ```
  conda install -c anaconda scikit-learn=0.18.2 
  
  ```
  
  If you are using `pip` it is recommended to use it only with `virtualenv` `venv`. If there is a dependency issue delete the environment and start over is much easier.
  
  The rationale is for not mixing them is:
  
  * `conda` installs lots of stuff not just Python and it gets the `env` (environment) right for this purpose
  * `pip` only installs Python within a Python environment
  
  ---
  
  The simple answer is
  
  ```
  conda install -c bioconda deepbgc
  
  ```
  
  conda will then install the correct version of scikit-learn automatically. If doing this it important it is in its own (new) `conda` environment however.
  
  If the above doesn't work further stuff can be done, but the 'simple answer' should work.
  
  ---
  
  @Joe\_G says its hanging ... on `solving environment` just leave it ... you will then see why,
  
  ```
  The following NEW packages will be INSTALLED:
  
    _tflow_select      pkgs/main/osx-64::_tflow_select-2.3.0-mkl
    absl-py            pkgs/main/noarch::absl-py-0.15.0-pyhd3eb1b0_0
    appdirs            pkgs/main/noarch::appdirs-1.4.4-pyhd3eb1b0_0
    astor              pkgs/main/osx-64::astor-0.8.1-py37hecd8cb5_0
    biopython          pkgs/main/osx-64::biopython-1.76-py37h1de35cc_0
    blas               pkgs/main/osx-64::blas-1.0-mkl
    bottleneck         pkgs/main/osx-64::bottleneck-1.3.5-py37h67323c0_0
    brotli             pkgs/main/osx-64::brotli-1.0.9-hca72f7f_7
    brotli-bin         pkgs/main/osx-64::brotli-bin-1.0.9-hca72f7f_7
    c-ares             pkgs/main/osx-64::c-ares-1.18.1-hca72f7f_0
    ca-certificates    pkgs/main/osx-64::ca-certificates-2022.07.19-hecd8cb5_0
    certifi            pkgs/main/osx-64::certifi-2022.9.14-py37hecd8cb5_0
    cycler             pkgs/main/noarch::cycler-0.11.0-pyhd3eb1b0_0
    dataclasses        pkgs/main/noarch::dataclasses-0.8-pyh6d0b6a4_7
    deepbgc            bioconda/noarch::deepbgc-0.1.23-py_0
    fftw               pkgs/main/osx-64::fftw-3.3.9-h9ed2024_1
    fonttools          pkgs/main/noarch::fonttools-4.25.0-pyhd3eb1b0_0
    freetype           pkgs/main/osx-64::freetype-2.11.0-hd8bbffd_0
    gast               pkgs/main/noarch::gast-0.5.3-pyhd3eb1b0_0
    giflib             pkgs/main/osx-64::giflib-5.2.1-haf1e3a3_0
    grpcio             pkgs/main/osx-64::grpcio-1.42.0-py37ha29bfda_0
    h5py               pkgs/main/osx-64::h5py-3.7.0-py37h4a1dd59_0
    hdf5               pkgs/main/osx-64::hdf5-1.10.6-h10fe05b_1
    hmmer              bioconda/osx-64::hmmer-3.3.2-h9722bc1_2
    importlib-metadata pkgs/main/osx-64::importlib-metadata-4.11.3-py37hecd8cb5_0
    intel-openmp       pkgs/main/osx-64::intel-openmp-2021.4.0-hecd8cb5_3538
    joblib             pkgs/main/noarch::joblib-1.1.0-pyhd3eb1b0_0
    jpeg               pkgs/main/osx-64::jpeg-9e-hca72f7f_0
    keras              pkgs/main/osx-64::keras-2.2.4-0
    keras-applications pkgs/main/noarch::keras-applications-1.0.8-py_1
    keras-base         pkgs/main/osx-64::keras-base-2.2.4-py37_0
    keras-preprocessi~ pkgs/main/noarch::keras-preprocessing-1.1.2-pyhd3eb1b0_0
    kiwisolver         pkgs/main/osx-64::kiwisolver-1.4.2-py37he9d5cce_0
    lcms2              pkgs/main/osx-64::lcms2-2.12-hf1fd2bf_0
    lerc               pkgs/main/osx-64::lerc-3.0-he9d5cce_0
    libbrotlicommon    pkgs/main/osx-64::libbrotlicommon-1.0.9-hca72f7f_7
    libbrotlidec       pkgs/main/osx-64::libbrotlidec-1.0.9-hca72f7f_7
    libbrotlienc       pkgs/main/osx-64::libbrotlienc-1.0.9-hca72f7f_7
    libcxx             pkgs/main/osx-64::libcxx-14.0.6-h9765a3e_0
    libdeflate         pkgs/main/osx-64::libdeflate-1.8-h9ed2024_5
    libffi             bioconda/osx-64::libffi-3.2.1-1
    libgfortran        pkgs/main/osx-64::libgfortran-5.0.0-11_2_0_h246ff09_26
    libgfortran5       pkgs/main/osx-64::libgfortran5-11.2.0-h246ff09_26
    libpng             pkgs/main/osx-64::libpng-1.6.37-ha441bb4_0
    libprotobuf        pkgs/main/osx-64::libprotobuf-3.20.1-h8346a28_0
    libtiff            pkgs/main/osx-64::libtiff-4.4.0-h2ef1027_0
    libwebp            pkgs/main/osx-64::libwebp-1.2.2-h56c3ce4_0
    libwebp-base       pkgs/main/osx-64::libwebp-base-1.2.2-hca72f7f_0
    llvm-openmp        pkgs/main/osx-64::llvm-openmp-14.0.6-h0dcd299_0
    lz4-c              pkgs/main/osx-64::lz4-c-1.9.3-h23ab428_1
    markdown           pkgs/main/osx-64::markdown-3.3.4-py37hecd8cb5_0
    matplotlib-base    pkgs/main/osx-64::matplotlib-base-3.5.2-py37hfb0c5b7_0
    mkl                pkgs/main/osx-64::mkl-2021.4.0-hecd8cb5_637
    mkl-service        pkgs/main/osx-64::mkl-service-2.4.0-py37h9ed2024_0
    mkl_fft            pkgs/main/osx-64::mkl_fft-1.3.1-py37h4ab4a9b_0
    mkl_random         pkgs/main/osx-64::mkl_random-1.2.2-py37hb2f4e1b_0
    munkres            bioconda/noarch::munkres-1.0.7-py_1
    ncurses            pkgs/main/osx-64::ncurses-6.3-hca72f7f_3
    numexpr            pkgs/main/osx-64::numexpr-2.8.3-py37h2e5f0a9_0
    numpy              pkgs/main/osx-64::numpy-1.21.5-py37h2e5f0a9_3
    numpy-base         pkgs/main/osx-64::numpy-base-1.21.5-py37h3b1a694_3
    openssl            pkgs/main/osx-64::openssl-1.1.1q-hca72f7f_0
    packaging          pkgs/main/noarch::packaging-21.3-pyhd3eb1b0_0
    pandas             pkgs/main/osx-64::pandas-1.3.5-py37h743cdd8_0
    pillow             pkgs/main/osx-64::pillow-9.2.0-py37hde71d04_1
    pip                pkgs/main/osx-64::pip-22.2.2-py37hecd8cb5_0
    prodigal           bioconda/osx-64::prodigal-2.6.3-ha5712d3_4
    protobuf           pkgs/main/osx-64::protobuf-3.20.1-py37he9d5cce_0
    pyparsing          pkgs/main/osx-64::pyparsing-3.0.9-py37hecd8cb5_0
    python             pkgs/main/osx-64::python-3.7.7-hc70fcce_0_cpython
    python-dateutil    pkgs/main/noarch::python-dateutil-2.8.2-pyhd3eb1b0_0
    pytz               pkgs/main/osx-64::pytz-2022.1-py37hecd8cb5_0
    pyyaml             pkgs/main/osx-64::pyyaml-6.0-py37hca72f7f_1
    readline           pkgs/main/osx-64::readline-8.1.2-hca72f7f_1
    scikit-learn       pkgs/main/osx-64::scikit-learn-1.0.2-py37hae1ba45_1
    scipy              pkgs/main/osx-64::scipy-1.7.3-py37h214d14d_2
    setuptools         pkgs/main/osx-64::setuptools-63.4.1-py37hecd8cb5_0
    six                pkgs/main/noarch::six-1.16.0-pyhd3eb1b0_1
    sqlite             pkgs/main/osx-64::sqlite-3.39.3-h707629a_0
    tensorboard        pkgs/main/osx-64::tensorboard-1.14.0-py37h80053f4_0
    tensorflow         pkgs/main/osx-64::tensorflow-1.14.0-mkl_py37h085be34_0
    tensorflow-base    pkgs/main/osx-64::tensorflow-base-1.14.0-mkl_py37h5a24fda_0
    tensorflow-estima~ pkgs/main/noarch::tensorflow-estimator-1.14.0-py_0
    termcolor          pkgs/main/osx-64::termcolor-1.1.0-py37hecd8cb5_1
    threadpoolctl      pkgs/main/noarch::threadpoolctl-2.2.0-pyh0d69192_0
    tk                 pkgs/main/osx-64::tk-8.6.12-h5d9f67b_0
    typing_extensions  pkgs/main/osx-64::typing_extensions-4.3.0-py37hecd8cb5_0
    werkzeug           pkgs/main/noarch::werkzeug-2.0.3-pyhd3eb1b0_0
    wheel              pkgs/main/noarch::wheel-0.37.1-pyhd3eb1b0_0
    wrapt              pkgs/main/osx-64::wrapt-1.14.1-py37hca72f7f_0
    xz                 pkgs/main/osx-64::xz-5.2.6-hca72f7f_0
    yaml               pkgs/main/osx-64::yaml-0.2.5-haf1e3a3_0
    zipp               pkgs/main/osx-64::zipp-3.8.0-py37hecd8cb5_0
    zlib               pkgs/main/osx-64::zlib-1.2.12-h4dc903c_3
    zstd               pkgs/main/osx-64::zstd-1.5.2-hcb37349_0
  
  Proceed ([y]/n)? 
  
  ```
  
  Its an enormous data pipeline. Everything is there, thats why it takes so long.
  
  > **Comments:**
  > **username_0**: Hi, thanks for your response. I went ahead and created a new conda environment and tried to run the deepbgc install on there with conda instead of pip. The problem now is the install is getting stuck at the "Solving Environment" phase. For whatever reason, It doesn't seem to make it past that point.  
  > **username_1**: Hi @username_0 I've updated the post, so did it work?  
  > **username_2**: I've found [mamba](https://mamba.readthedocs.io) to be a life-saver for getting around conda's slowness with large sets of packages.  Its `mamba` command can act as a drop-in replacement for `conda` for most purposes and most importantly it solves dependencies *much* faster.  
  > **username_0**: Unfortunately it never got past the solving environment stage. I was installing it on a remote server and the process took so long that the my user was disconnected from the server before it could finish. I'm going to try again thinking maybe it was an issue with the server. @username_2 I may try Mamba that sounds like it could be helpful. Is that just a package installation? As mentioned before, the warning message wasn't code breaking so I may just be living with it for the time being. I do appreciate the guidance, thanks!  
  > **username_1**: Thanks for your feedback @username_0 . Personally `conda` has been the most stable environment and package management system I've used. Upvotes are always appreciated BTW.  
  > **username_0**: Will do @M_ Thanks again!  
  > **username_2**: Yes mamba itself is just an anaconda package so it's a simple install.  You have to install it into the base environment though (something like `conda install mamba -n base -c conda-forge` to get the latest one from conda-forge.)  
  
  ---
  
  