Table of contents

Manage packages as a Watson Studio Local user

Watson Studio Local users can add additional packages to a base image (for example, custom, external, or third-party libraries and packages), which can then be reused by other users.

Watson Studio Local includes many preinstalled libraries. Before you install a library, check the list of preinstalled libraries. Run the appropriate command from a notebook cell:

  • Python: !pip list --isolated
  • R: installed.packages()

If the library that you want is not listed, or you want to use a Scala library in a notebook, use the steps in the following sections to install it. The format for library packages depends on the programming language.

To install a Python library

Notebook users can run the conda command to install Python libraries to their notebook.
Requirement: Packages can only be installed from the conda channels specified in the administrator's Manage conda channels page.
  1. Use the Python conda install command to install Python libraries to your notebook. For example, the following command installs the prettyplotlib library into a pod's conda, for instance, /opt/conda/lib/python2.7/site-packages, and then removes the package once the pod is terminated:
    !conda install prettyplotlib
  2. Use the Python import command to import the library components. For example, run the following command in a code cell:
    import prettyplotlib as ppl
To use custom functions defined in Python scripts

You can import a python script to the Scripts section of your project, and then import the functions like any other Python module. The following example imports all functions in a file named dsxl_support_functions.py:

sys.path.insert(0, '../scripts/')
from dsxl_support_functions import *

where ../scripts is the location where you imported your Python scripts. The imported functions can be called like any regular functions defined in modules.

To install an R package

  1. Use the R install.packages() function to install new R packages. For example, run the following command in a code cell to install the ggplot2 package for plotting functions:
    install.packages("ggplot2")
    The imported package can be used by all R notebooks running in the Spark service.
  2. Use the R library() function to load the installed package. For example, run the following command in a code cell:
    library("ggplot2")
    You can now call plotting functions from the ggplot2 package in your notebook.

To add a Scala library

Libraries for Scala notebooks are typically packaged as Java™ archive (JAR) files.

To cache a library temporarily
The libraries for a Scala notebook are not installed to the Spark service. Instead they are cached when they are downloaded and are only available for the time that the notebook runs.
  • To use a single library without dependencies, from a public web server:
    1. Locate the publicly available URL to the library that you want to install. If you create a custom library, you can post it to any publicly available repository, such as GitHub.
    2. Download the library you want to use in your notebook by running the following command in a code cell:
      %AddJar URL_to_jar_file
  • To use a library with dependencies, from a public Maven repository:
    1. Add and import a library with all its dependencies by running the following command. You need the groupId, artifactId, and version of the dependency. For example:
      %AddDeps org.apache.spark
      spark-streaming-kafka_2.10 1.1.0 --transitive

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