Python 如果conda软件包最初安装在Windows上，如何在Linux上安装它们？

我在Windows PC上本地安装了conda，也在Linux服务器上远程安装了conda。我已经在Windows PC上本地安装了conda软件包，我想在Linux服务器上安装相同的软件包。我已经尝试了以下步骤：

使用命令

conda list-e>requirements.txt

在我的Windows PC上使用Anaconda提示符创建一个

requirements.txt

文件，其中包含当前安装的软件包及其版本

将此

requirements.txt

文件传输到我的Linux服务器

使用命令

conda Install--yes--file requirements.txt在我的
conda
base
环境中安装这些软件包

但是，当我尝试完成步骤3时，我在Linux服务器上收到以下错误消息：

Solving environment: failed

PackagesNotFoundError: The following packages are not available from current channels:

  - ca-certificates==2020.12.8=haa95532_0
  - m2w64-gcc-libs-core==5.3.0=7
  - audioread==2.1.8=pypi_0
  - pywin32-ctypes==0.2.0=py38_1000
  - notebook==6.1.5=py38haa95532_0
  - librosa==0.8.0=pypi_0
  - numpy-base==1.19.2=py38ha3acd2a_0
  - psutil==5.7.2=py38he774522_0
  - numpy==1.19.2=py38hadc3359_0
  - regex==2020.11.13=py38h2bbff1b_0
  - spyder-kernels==1.10.0=py38haa95532_0
  - appdirs==1.4.4=pypi_0
  - ujson==4.0.1=py38ha925a31_0
  - setuptools==51.0.0=py38haa95532_2
  - sklearn-crfsuite==0.3.6=pypi_0
  - pywinpty==0.5.7=py38_0
  - m2w64-gmp==6.1.0=2
  - pyyaml==5.3.1=py38he774522_1
  - bzip2==1.0.8=he774522_0
  - sounddevice==0.4.1=pypi_0
  - certifi==2020.12.5=py38haa95532_0
  - gpytorch==1.3.0=pypi_0
  - winpty==0.4.3=4
  - pyzmq==20.0.0=py38hd77b12b_1
  - pytorch==1.7.1=py3.8_cpu_0
  - lazy-object-proxy==1.4.3=py38h2bbff1b_2
  - zeromq==4.3.3=ha925a31_3
  - ipython==7.19.0=py38hd4e2768_0
  - mkl_fft==1.2.0=py38h45dec08_0
  - conda-package-handling==1.7.2=py38h76e460a_0
  - vc==14.2=h21ff451_1
  - cpuonly==1.0=0
  - pip==20.3.1=py38haa95532_0
  - tornado==6.1=py38h2bbff1b_0
  - libarchive==3.4.2=h5e25573_0
  - msys2-conda-epoch==20160418=1
  - pandocfilters==1.4.3=py38haa95532_1
  - scikit-learn==0.23.2=pypi_0
  - torchaudio==0.7.2=py38
  - soundfile==0.10.3.post1=pypi_0
  - gsl==2.4=hfa6e2cd_4
  - kiwisolver==1.3.0=py38hd77b12b_0
  - argon2-cffi==20.1.0=py38he774522_1
  - dataclasses==0.6=pypi_0
  - libtiff==4.1.0=h56a325e_1
  - torchvision==0.8.2=py38_cpu
  - m2w64-libwinpthread-git==5.0.0.4634.697f757=2
  - numba==0.51.2=pypi_0
  - pooch==1.2.0=pypi_0
  - cvxopt==1.2.0=py38hdc3235a_0
  - tabulate==0.8.7=pypi_0
  - pillow==8.0.1=py38h4fa10fc_0
  - libpng==1.6.37=h2a8f88b_0
  - libiconv==1.15=h1df5818_7
  - rtree==0.9.4=py38h21ff451_1
  - qt==5.9.7=vc14h73c81de_0
  - ruamel_yaml==0.15.87=py38he774522_1
  - libsodium==1.0.18=h62dcd97_0
  - yaml==0.2.5=he774522_0
  - m2w64-gcc-libs==5.3.0=7
  - libspatialindex==1.9.3=h33f27b4_0
  - jedi==0.17.2=py38haa95532_1
  - tk==8.6.10=he774522_0
  - six==1.15.0=py38haa95532_0
  - python-crfsuite==0.9.7=pypi_0
  - spyder==4.2.0=py38haa95532_0
  - cffi==1.14.4=py38hcd4344a_0
  - xz==5.2.5=h62dcd97_0
  - console_shortcut==0.1.1=4
  - sqlite==3.33.0=h2a8f88b_0
  - pycosat==0.6.3=py38h2bbff1b_0
  - pyrsistent==0.17.3=py38he774522_0
  - markupsafe==1.1.1=py38he774522_0
  - bcrypt==3.2.0=py38he774522_0
  - libuv==1.40.0=he774522_0
  - brotlipy==0.7.0=py38h2bbff1b_1003
  - mistune==0.8.4=py38he774522_1000
  - wrapt==1.11.2=py38he774522_0
  - powershell_shortcut==0.0.1=3
  - mkl-service==2.3.0=py38h196d8e1_0
  - pysocks==1.7.1=py38haa95532_0
  - typeguard==2.10.0=pypi_0
  - jpeg==9b=hb83a4c4_2
  - libxml2==2.9.10=hb89e7f3_3
  - freetype==2.10.4=hd328e21_0
  - python==3.8.5=h5fd99cc_1
  - liblief==0.10.1=ha925a31_0
  - sip==4.19.13=py38ha925a31_0
  - scipy==1.5.4=pypi_0
  - pywin32==227=py38he774522_1
  - nltk==3.5=pypi_0
  - py-lief==0.10.1=py38ha925a31_0
  - threadpoolctl==2.1.0=pypi_0
  - zlib==1.2.11=h62dcd97_4
  - cudatoolkit==10.2.89=h74a9793_1
  - zstd==1.4.5=h04227a9_0
  - mkl_random==1.1.1=py38h47e9c7a_0
  - glpk==4.65=hdc00fd2_2
  - ninja==1.10.2=py38h6d14046_0
  - joblib==0.17.0=pypi_0
  - typed-ast==1.4.1=py38he774522_0
  - pandas==1.1.3=py38ha925a31_0
  - llvmlite==0.34.0=pypi_0
  - resampy==0.2.2=pypi_0
  - pynacl==1.4.0=py38h62dcd97_1
  - vs2015_runtime==14.27.29016=h5e58377_2
  - icu==58.2=ha925a31_3
  - matplotlib-base==3.3.2=py38hba9282a_0
  - menuinst==1.4.16=py38he774522_1
  - pyqt==5.9.2=py38ha925a31_4
  - cryptography==3.3.1=py38hcd4344a_0
  - jupyter_core==4.7.0=py38haa95532_0
  - ax-platform==0.1.19=pypi_0
  - botorch==0.3.3=pypi_0
  - win_inet_pton==1.1.0=py38haa95532_0
  - pkginfo==1.6.1=py38haa95532_0
  - openssl==1.1.1i=h2bbff1b_0
  - wincertstore==0.2=py38_0
  - matplotlib==3.3.2=pypi_0
  - lz4-c==1.9.2=hf4a77e7_3
  - pandoc==2.11=h9490d1a_0
  - conda==4.9.2=py38haa95532_0
  - ad3==2.3.dev0=pypi_0
  - retrying==1.3.3=pypi_0
  - plotly==4.14.1=pypi_0
  - m2w64-gcc-libgfortran==5.3.0=6
  - watchdog==0.10.4=py38haa95532_0
  - chardet==3.0.4=py38haa95532_1003

Current channels:

  - https://repo.anaconda.com/pkgs/main/linux-64
  - https://repo.anaconda.com/pkgs/main/noarch
  - https://repo.anaconda.com/pkgs/free/linux-64
  - https://repo.anaconda.com/pkgs/free/noarch
  - https://repo.anaconda.com/pkgs/r/linux-64
  - https://repo.anaconda.com/pkgs/r/noarch
  - https://repo.anaconda.com/pkgs/pro/linux-64
  - https://repo.anaconda.com/pkgs/pro/noarch

To search for alternate channels that may provide the conda package you're
looking for, navigate to

    https://anaconda.org

and use the search bar at the top of the page.

我知道问题在于我没有按照错误消息所示查看正确的

conda

通道，但我不确定如何解决此问题

---

感谢您的帮助。

官方文档中有一些额外的步骤，可以让环境跨平台工作。是与此相关的链接

但是，如果您不使用仅在anaconda频道中可用的软件包，则可以执行以下操作

在您的conda环境（windows和linux服务器）上都有pip

使用

pip freeze

而不是conda的文件创建requirements.txt文件。从windows计算机

$pip freeze>requirements.txt

通常使用pip在linux服务器上安装软件包

$pip安装-r requirements.txt

我并不是说这是最好的选择。但这种方法通常更容易支持其他环境管理包，如pyenv