Google datalab Python package. Used in [Google Cloud Datalab] (https://github.com/GoogleCloudPlatform/datalab) and can be used in Jupyter Notebook.
This adds a number of Python modules such as datalab.bigquery,
datalab.storage, etc, for accessing [Google Cloud Platform services]
(https://cloud.google.com/) as well as adding some new cell magics such as %chart,
%bigquery, %storage, etc.
See https://github.com/googledatalab/notebooks for samples of using this package.
You will need the Typscript compiler installed. In future we should be installable from PyPI.
First:
git clone https://github.com/googledatalab/pydatalab.git
cd pydatalab
Then do one of the folowing:
./install-virtualenv.sh # For use in Python virtual environments
./install-no-virtualenv.sh # For installing in a non-virtual environment
You can ignore the message about running jupyter nbextension enable; it is not required.
In a notebook cell, enable with:
%load_ext datalab.kernel
Alternatively add this to your ipython_config.py file in your profile:
c = get_config()
c.InteractiveShellApp.extensions = [
'datalab.kernel'
]
You will typically put this under ~/.ipython/profile_default.
See [http://ipython.readthedocs.io/en/stable/development/config.html]
(http://ipython.readthedocs.io/en/stable/development/config.html)
for more about IPython profiles.
If you want to access Google Cloud Platform services such as BigQuery, you will also need to install [gcloud] (https://cloud.google.com/sdk/gcloud). You will need to use gcloud to authenticate; e.g. with:
gcloud auth login
You will also need to set the project ID to use; either set a PROJECT_ID
environment variable to the project name, or call set_datalab_project_id(name)
from within your notebook.
You can read the Sphinx generated docs at: http://googledatalab.github.io/pydatalab/