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Jupyter筆記本和Anaconda-Navigator中內核數量的差異

[英]discrepancy in numbers of kernels in Jupyter notebook and Anaconda-Navigator

我正在用Ananconda運行python,並且在加載jupyter筆記本時,我看到有6個可用的內核(見圖片):

Last login: Sun Sep 17 12:42:58 on ttys001
MacBook:~ user1$ jupyter notebook
[I 14:53:55.642 NotebookApp] [nb_conda_kernels] enabled, 6 kernels found
[I 14:53:56.470 NotebookApp] JupyterLab alpha preview extension loaded from /Users/user/anaconda/lib/python2.7/site-packages/jupyterlab
[I 14:53:56.471 NotebookApp] Running the core application with no additional extensions or settings
[I 14:53:57.374 NotebookApp] [nb_anacondacloud] enabled
[I 14:53:57.379 NotebookApp] [nb_conda] enabled
[I 14:53:57.451 NotebookApp] ✓ nbpresent HTML export ENABLED
[W 14:53:57.452 NotebookApp] ✗ nbpresent PDF export DISABLED: No module named nbbrowserpdf.exporters.pdf
[I 14:53:57.457 NotebookApp] Serving notebooks from local directory: /Users/user

具有6個內核,Python和R的Jupyter筆記本

但是conda和anaconda-navigator顯示了三種環境:

conda info --envs
# conda environments:
#
P34                      /Users/user/anaconda/envs/P34
R                        /Users/user/anaconda/envs/R
root                  *  /Users/user/anaconda

具有3個內核的Anaconda Navigator,Python和R

此外,

conda info --json

返回此:

{
  "GID": 20, 
  "UID": 503, 
  "channels": [
    "https://conda.anaconda.org/anaconda-fusion/osx-64", 
    "https://conda.anaconda.org/anaconda-fusion/noarch", 
    "https://conda.anaconda.org/r/osx-64", 
    "https://conda.anaconda.org/r/noarch", 
    "https://repo.continuum.io/pkgs/free/osx-64", 
    "https://repo.continuum.io/pkgs/free/noarch", 
    "https://repo.continuum.io/pkgs/r/osx-64", 
    "https://repo.continuum.io/pkgs/r/noarch", 
    "https://repo.continuum.io/pkgs/pro/osx-64", 
    "https://repo.continuum.io/pkgs/pro/noarch"
  ], 
  "conda_build_version": "2.0.2", 
  "conda_env_version": "4.3.25", 
  "conda_location": "/Users/user/anaconda/lib/python2.7/site-packages/conda", 
  "conda_prefix": "/Users/user/anaconda", 
  "conda_private": false, 
  "conda_version": "4.3.25", 
  "default_prefix": "/Users/user/anaconda", 
  "env_vars": {
    "CIO_TEST": "<not set>", 
    "CONDA_DEFAULT_ENV": "<not set>", 
    "CONDA_ENVS_PATH": "<not set>", 
    "DYLD_LIBRARY_PATH": "<not set>", 
    "PATH": "/Users/user/Dropbox (Personal)/firefoxdriver_osx/bin:/Users/user/Dropbox (Personal)/chromedriver_osx/bin:/Users/user/anaconda/bin:/Library/Frameworks/Python.framework/Versions/Current/bin:/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin:/opt/X11/bin:/Library/TeX/texbin", 
    "PYTHONHOME": "<not set>", 
    "PYTHONPATH": "<not set>"
  }, 
  "envs": [
    "/Users/user/anaconda/envs/P34", 
    "/Users/user/anaconda/envs/R"
  ], 
  "envs_dirs": [
    "/Users/user/anaconda/envs", 
    "/Users/user/.conda/envs"
  ], 
  "netrc_file": null, 
  "offline": false, 
  "pkgs_dirs": [
    "/Users/user/anaconda/pkgs", 
    "/Users/user/.conda/pkgs"
  ], 
  "platform": "osx-64", 
  "python_version": "2.7.13.final.0", 
  "rc_path": "/Users/user/.condarc", 
  "requests_version": "2.14.2", 
  "root_prefix": "/Users/user/anaconda", 
  "root_writable": true, 
  "site_dirs": [], 
  "sys.executable": "/Users/user/anaconda/bin/python", 
  "sys.prefix": "/Users/user/anaconda", 
  "sys.version": "2.7.13 |Anaconda 4.4.0 (x86_64)| (default, Dec 20 2016, 23:05:08) \n[GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.57)]", 
  "sys_rc_path": "/Users/user/anaconda/.condarc", 
  "user_agent": "conda/4.3.25 requests/2.14.2 CPython/2.7.13 Darwin/16.7.0 OSX/10.12.6", 
  "user_rc_path": "/Users/user/.condarc"
}

我如何調和jupyter筆記本的內容和conda報告的內容? 如何刪除Jupyter Notebook報告的某些環境? 這個問題是由一些我認為已加載到環境中但最終出現在“鬼”環境中的庫造成的。

Conda附帶了nb_conda_kernels ,它繞過了常規的內核機制。 因此,並非您計算機的所有程序都能看到所有內核。

nb_conda_kernels旨在自動將任何conda env公開為可能的內核。 它確實(或至少確實如此)僅針對筆記本服務器,因此您可以在筆記本UI中看到更多內核。

它具有優點:不再需要手動注冊內核-缺點:許多其他軟件都看不到內核; 值得注意的是,還有Atom,Nteract,Nbconvert和其他較低級別的工具,以及您提到的問題。

您可以通過查看jupyter配置文件來停用nb_conda_kernel並刪除anaconda啟用的選項; 卸載nb_conda_kernels。 然后以經典方式安裝kernelspec。

IPython內核!= conda環境。 您可能具有多個內核的環境(在您的情況下,“ P34”和“ R”每個都有2個內核-用於R和Python),或者可能有完全沒有IPython內核的環境。

如果要刪除conda環境,請使用conda env remove -n ENV_NAME命令執行此操作。

如果要在不刪除整個環境的情況下從Jupyter分離內核,則可以刪除相應的內核spec文件夾。 有關如何查找內核spec文件夾的詳細信息,請參見我對其他問題的回答

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