管理软件包#

使用终端完成以下步骤。

要查看某个特定软件包（例如 SciPy）是否可供安装：

conda search scipy

要查看某个特定软件包（例如 SciPy）是否可以从 Anaconda.org 安装：

conda search --override-channels --channel defaults scipy

要查看某个特定软件包（例如 iminuit）是否存在于某个特定的渠道（例如 http://conda.anaconda.org/mutirri）中，并可供安装：

conda search --override-channels --channel http://conda.anaconda.org/mutirri iminuit

Use the terminal for the following steps.

To see if a specific package, such as SciPy, is available for installation:

conda search scipy

To see if a specific package, such as SciPy, is available for installation from Anaconda.org:

conda search --override-channels --channel defaults scipy

To see if a specific package, such as iminuit, exists in a specific channel, such as http://conda.anaconda.org/mutirri, and is available for installation:

conda search --override-channels --channel http://conda.anaconda.org/mutirri iminuit

要将特定软件包（如 SciPy）安装到已有的环境 "myenv" 中：

conda install --name myenv scipy

如果未指定环境名称（在此例中通过 --name myenv 指定），该软件包将安装到当前环境中：

conda install scipy

要安装特定版本的软件包（如 SciPy）：

conda install scipy=0.15.0

要一次性安装多个软件包，例如 SciPy 和 cURL：

conda install scipy curl

要一次性安装多个软件包并指定版本号：

conda install scipy=0.15.0 curl=7.26.0

要为特定 Python 版本安装某个软件包：

conda install scipy=0.15.0 curl=7.26.0 -n py34_env

如果希望使用特定的 Python 版本，建议创建使用该版本的环境。有关更多信息，请参阅 故障排除。

Use the terminal for the following steps.

To install a specific package such as SciPy into an existing environment "myenv":

conda install --name myenv scipy

If you do not specify the environment name, which in this example is done by --name myenv, the package installs into the current environment:

conda install scipy

To install a specific version of a package such as SciPy:

conda install scipy=0.15.0

To install multiple packages at once, such as SciPy and cURL:

conda install scipy curl

To install multiple packages at once and specify the version of the package:

conda install scipy=0.15.0 curl=7.26.0

To install a package for a specific Python version:

conda install scipy=0.15.0 curl=7.26.0 -n py34_env

If you want to use a specific Python version, it is best to use an environment with that version. For more information, see 故障排除.

安装名称相似、功能相近的软件包可能会产生意外结果。通常，后安装的软件包会决定最终的行为，这种行为可能并非所期望的。 如果这两个软件包名称不同，或你正在构建软件包变体并需要协调栈中其它软件，我们建议使用 互斥元软件包。

Installing packages that have similar filenames and serve similar purposes may return unexpected results. The package last installed will likely determine the outcome, which may be undesirable. If the two packages have different names, or if you're building variants of packages and need to line up other software in the stack, we recommend using 互斥元软件包.

使用 conda install 无法获得的软件包可以通过 Anaconda.org 获取。Anaconda.org 是一个支持公共和私有软件包仓库的软件包管理服务。它与 Anaconda 和 Miniconda 一样，是 Anaconda 的产品之一。

要从 Anaconda.org 安装软件包：

1. 打开浏览器，访问 http://anaconda.org。

2. 在左上角的“Search Packages”搜索框中输入 bottleneck。

3. 找到你需要的软件包并点击进入其详情页。

   详情页会显示该软件包所属的渠道名，例如本例中为 "pandas" 渠道。

4. 现在你已知道渠道名，可以使用 conda install 命令安装该软件包。在终端中运行：

   conda install -c pandas bottleneck
   

   此命令指示 conda 从 Anaconda.org 上的 pandas 渠道安装 bottleneck 软件包。

5. 要确认该软件包已被安装，在终端中运行：

   conda list
   

   会显示一个软件包列表，其中应包含 bottleneck。

Packages that are not available using conda install can be obtained from Anaconda.org, a package management service for both public and private package repositories. Anaconda.org is an Anaconda product, just like Anaconda and Miniconda.

To install a package from Anaconda.org:

1. In a browser, go to http://anaconda.org.

2. To find the package named bottleneck, type bottleneck in the top-left box named Search Packages.

3. Find the package that you want and click it to go to the detail page.

   The detail page displays the name of the channel. In this example it is the "pandas" channel.

4. Now that you know the channel name, use the conda install command to install the package. In your terminal window, run:

   conda install -c pandas bottleneck
   

   This command tells conda to install the bottleneck package from the pandas channel on Anaconda.org.

5. To check that the package is installed, in your terminal window, run:

   conda list
   

   A list of packages appears, including bottleneck.

如果某个软件包无法通过 conda 或 Anaconda.org 获取，可以尝试通过 conda-forge 或其它包管理器（如 pip）安装。

pip 安装的软件包不具备 conda 软件包的全部功能，因此我们建议首先尝试使用 conda 安装。如无法通过 conda 获取该软件包，可尝试从 conda-forge 寻找并安装。

若仍无法安装该软件包，可尝试使用 pip 进行安装。由于 pip 与 conda 软件包的差异，可能存在某些兼容性限制，但 conda 已尽可能实现与 pip 的兼容。

pip 可以安装在 conda 环境之外，也可以安装在 conda 环境之内。

为获得 conda 的集成优势，确保在当前激活的 conda 环境中安装 pip，并使用该环境中的 pip 安装软件包。使用 conda list 命令可查看此方式安装的软件包，并显示它们是通过 pip 安装的标识。

你可以使用以下命令在当前 conda 环境中安装 pip，如 在环境中使用 pip 所述：

conda install pip

如果当前 conda 环境中既安装了 pip，同时环境之外也存在 pip 实例，系统将使用当前环境中安装的 pip。

要安装一个非 conda 的软件包：

1. 激活目标环境：

   • 在终端中运行 conda activate myenv。

2. 使用 pip 安装程序（如 See）：

   pip install see
   

3. 验证软件包是否已安装：

   conda list
   

   如果未显示该软件包，先按 在环境中使用 pip 中说明安装 pip，然后再尝试上述命令。

If a package is not available from conda or Anaconda.org, you may be able to find and install the package via conda-forge or with another package manager like pip.

Pip packages do not have all the features of conda packages and we recommend first trying to install any package with conda. If the package is unavailable through conda, try finding and installing it with conda-forge.

If you still cannot install the package, you can try installing it with pip. The differences between pip and conda packages cause certain unavoidable limits in compatibility but conda works hard to be as compatible with pip as possible.

It is possible to have pip installed outside a conda environment or inside a conda environment.

To gain the benefits of conda integration, be sure to install pip inside the currently active conda environment and then install packages with that instance of pip. The command conda list shows packages installed this way, with a label showing that they were installed with pip.

You can install pip in the current conda environment with the command conda install pip, as discussed in 在环境中使用 pip.

If there are instances of pip installed both inside and outside the current conda environment, the instance of pip installed inside the current conda environment is used.

To install a non-conda package:

1. Activate the environment where you want to put the program:

   • In your terminal window, run conda activate myenv.

2. To use pip to install a program such as See, in your terminal window, run:

   pip install see
   

3. To verify the package was installed, in your terminal window, run:

   conda list
   

   If the package is not shown, install pip as described in 在环境中使用 pip and try these commands again.

安装商业软件包（如 IOPro）与安装其他软件包相同。在终端中运行：

conda install --name myenv iopro

此命令会安装 Anaconda 的一款商业软件包 IOPro 的免费试用版， 该软件包可加速 Python 的数据处理。除学术用途外，该免费试用将在 30 天后到期。

Installing a commercial package such as IOPro is the same as installing any other package. In your terminal window, run:

conda install --name myenv iopro

This command installs a free trial of one of Anaconda's commercial packages called IOPro, which can speed up your Python processing. Except for academic use, this free trial expires after 30 days.

使用终端完成以下步骤。

要列出当前活动环境中的所有软件包：

conda list

要列出某个未激活环境（如 myenv）中的所有软件包：

conda list -n myenv

Use the terminal for the following steps.

To list all of the packages in the active environment:

conda list

To list all of the packages in a deactivated environment:

conda list -n myenv

要查找某个环境中依赖特定软件包的其他软件包，conda 并没有提供单一命令，而是需要执行一系列步骤：

1. 查看某个特定软件包所依赖的运行时依赖项：

   conda search package_name --info

2. 找到你当前安装的包缓存目录：

   conda info

3. 查找软件包依赖项。默认情况下，Anaconda / Miniconda 将软件包存储在 ~/anaconda/pkgs/ 目录中（在 macOS Catalina 上为 ~/opt/pkgs/）。 每个软件包目录中包含一个 index.json 文件，列出了该软件包的依赖项。 该文件位于 ~anaconda/pkgs/package_name/info/index.json。

4. 现在，你可以使用 grep 搜索所有 index.json 文件，以找出哪些软件包依赖某个特定软件包：

   grep package_name ~/anaconda/pkgs/*/info/index.json

该命令的输出将显示包含 <package_name> 的所有软件包的完整路径及其版本号。

示例：

grep numpy ~/anaconda3/pkgs/*/info/index.json

上述命令的输出示例:

/Users/testuser/anaconda3/pkgs/anaconda-4.3.0-np111py36_0/info/index.json: numpy 1.11.3 py36_0
/Users/testuser/anaconda3/pkgs/anaconda-4.3.0-np111py36_0/info/index.json: numpydoc 0.6.0 py36_0
/Users/testuser/anaconda3/pkgs/anaconda-4.3.0-np111py36_0/info/index.json: numpy 1.11.3 py36_0

注意，这里也返回了 “numpydoc”，因为它包含字符串 “numpy”。若要获得更精确的匹配结果，可使用 \< 和 \> 进行边界限定。

To find what packages are depending on a specific package in your environment, there is not one specific conda command. It requires a series of steps:

1. List the dependencies that a specific package requires to run: conda search package_name --info

2. Find your installation’s package cache directory: conda info

3. Find package dependencies. By default, Anaconda/Miniconda stores packages in ~/anaconda/pkgs/ (or ~/opt/pkgs/ on macOS Catalina). Each package has an index.json file which lists the package’s dependencies. This file resides in ~anaconda/pkgs/package_name/info/index.json.

4. Now you can find what packages depend on a specific package. Use grep to search all index.json files as follows: grep package_name ~/anaconda/pkgs/*/info/index.json

The result will be the full package path and version of anything containing the <package_name>.

Example: grep numpy ~/anaconda3/pkgs/*/info/index.json

Output from the above command:

/Users/testuser/anaconda3/pkgs/anaconda-4.3.0-np111py36_0/info/index.json: numpy 1.11.3 py36_0
/Users/testuser/anaconda3/pkgs/anaconda-4.3.0-np111py36_0/info/index.json: numpydoc 0.6.0 py36_0
/Users/testuser/anaconda3/pkgs/anaconda-4.3.0-np111py36_0/info/index.json: numpy 1.11.3 py36_0

Note this also returned “numpydoc” as it contains the string “numpy”. To get a more specific result set you can add < and >.

使用 conda update 命令可以检查是否有可用的更新。如果 conda 显示有可用更新，你可以选择是否进行安装。

使用终端完成以下步骤。

• 更新特定软件包，例如 biopython：

  conda update biopython
  

• 更新 Python：

  conda update python
  

• 更新 conda 本身：

  conda update conda
  

要更新 Anaconda 元包：

conda update conda
conda update anaconda

无论你更新的是哪个软件包，conda 都会比较版本信息并报告可用的更新内容。如果没有可用更新，conda 会提示：

All requested packages are already installed.

如果有可用的新版本，你希望更新该软件包，输入 y 确认更新：

Proceed ([y]/n)? y

Use conda update command to check to see if a new update is available. If conda tells you an update is available, you can then choose whether or not to install it.

Use the terminal for the following steps.

• To update a specific package:

  conda update biopython
  

• To update Python:

  conda update python
  

• To update conda itself:

  conda update conda
  

To update the Anaconda metapackage:

conda update conda
conda update anaconda

Regardless of what package you are updating, conda compares versions and then reports what is available to install. If no updates are available, conda reports "All requested packages are already installed."

If a newer version of your package is available and you wish to update it, type y to update:

Proceed ([y]/n)? y

在环境中固定（pin）某些软件包的版本可以防止它们被更新。这可以通过在环境的 conda-meta 目录中添加一个名为 pinned 的文件来实现， 文件中列出不希望被更新的软件包。

示例：以下文件将 NumPy 固定在 1.7 系列（即所有以 1.7 开头的版本），同时强制 SciPy 固定在精确版本 0.14.2:

numpy 1.7.*
scipy ==0.14.2

在该 pinned 文件存在的情况下，conda update numpy 将保持 NumPy 在 1.7.1， 而尝试 conda install scipy=0.15.0 将导致错误。

若想忽略 pinned 文件对某个软件包更新的限制，可以使用 --no-pin 标志。在终端中执行：

conda update numpy --no-pin

由于 pinned 规范会包含在每次 conda 安装操作中，因此在未使用 --no-pin 的情况下执行的后续 conda update 命令仍会将 NumPy 恢复为 1.7 系列。

Pinning a package specification in an environment prevents packages listed in the pinned file from being updated.

In the environment's conda-meta directory, add a file named pinned that includes a list of the packages that you do not want updated.

EXAMPLE: The file below forces NumPy to stay on the 1.7 series, which is any version that starts with 1.7. This also forces SciPy to stay at exactly version 0.14.2:

numpy 1.7.*
scipy ==0.14.2

With this pinned file, conda update numpy keeps NumPy at 1.7.1, and conda install scipy=0.15.0 causes an error.

Use the --no-pin flag to override the update restriction on a package. In the terminal, run:

conda update numpy --no-pin

Because the pinned specs are included with each conda install, subsequent conda update commands without --no-pin will revert NumPy back to the 1.7 series.

若想在每次新建环境时自动添加默认软件包：

1. 打开终端并执行：

   conda config --add create_default_packages PACKAGENAME1 PACKAGENAME2

2. 此后创建的所有新环境中，都会自动安装这些默认软件包。

你也可以 编辑 .condarc 文件，为默认创建环境配置软件包列表。

此外，也可以通过在命令行中添加 --no-default-packages 标志来临时禁用默认软件包。

To automatically add default packages to each new environment that you create:

1. Open a terminal window and run: conda config --add create_default_packages PACKAGENAME1 PACKAGENAME2

2. Now, you can create new environments and the default packages will be installed in all of them.

You can also edit the .condarc file with a list of packages to create by default.

You can override this option at the command prompt with the --no-default-packages flag.

使用终端完成以下步骤。

• 从某个环境（例如 myenv）中移除某个软件包（如 SciPy）：

  conda remove -n myenv scipy
  

• 从当前环境中移除某个软件包（如 SciPy）：

  conda remove scipy
  

• 一次移除多个软件包，例如 SciPy 和 cURL：

  conda remove scipy curl
  

• 确认软件包已被移除：

  conda list
  

Use the terminal for the following steps.

• To remove a package such as SciPy in an environment such as myenv:

  conda remove -n myenv scipy
  

• To remove a package such as SciPy in the current environment:

  conda remove scipy
  

• To remove multiple packages at once, such as SciPy and cURL:

  conda remove scipy curl
  

• To confirm that a package has been removed:

  conda list