terra-notebook-utils

Python API and CLI providing utilities for working with DRS objects, VCF files, and the Terra notebook environment.

Installation

From the CLI:

pip install terra-notebook-utils

In a Jupyter notebook (note the ipython magic "%pip"):

%pip install terra-notebook-utils

To upgrade to the newest version:

pip install --upgrade --no-cache-dir terra-notebook-utils

Credentials

Much of the terra-notebook-utilities functionality requires credentialed access through a Google Cloud Platform account. Credentials are already available when running in a Terra notebook environment. Otherwise, credentials may be obtained with the command

gcloud auth application-default login

Usage

terra-notebook-utils exposes a Python API, as well as wrappers to execute some functionality on the CLI. The Python API is best explored with Pythons great help function. For instance, issuing the follow commands into a Python interpreter or Jupyter notebook will produce help and usage for the drs module.

import terra_notebook_utils as tnu
help(tnu.drs)

Similarly, the CLI may be explored using the typical -h argument. Try the following commands at a bash prompt.

# See the command groups available to the CLI
tnu -h

# See the commands available to the vcf group
tnu vcf -h

# Show your available billing projects
tnu profile list-billing-projects

CLI Configuration

Several CLI commands target a workspace or require a Google billing project. Defaults can be configured using the commands

tnu config set-workspace my-workspace
tnu config set-workspace-google-project my-billing-project

Alternatively, workspace and billing project can be passed in to individual commands instead of, or as overrides to, the configured defaults. See command help, e.g. tnu table get --help, for usage information.

Finally, workspace and billing project can be specified with the environment variables WORKSPACE_NAME and GOOGLE_PROJECT. These values are used with lowest precedence.

The DRS API and CLI

terra-notebook-utils provides several methods and CLI commands useful for working with DRS resolved objects:

Python API

Copy drs object to local file system or bucket:

from terra_notebook_utils import drs
drs.copy("drs://my-drs-url", "gs://my-dst-bucket/my-dst-key")
drs.copy("drs://my-drs-url", "local_filepath")

CLI

Copy drs object to local or bucket:

tnu drs copy drs://my-drs-url gs://my-dst-bucket/my-dstkey
tnu drs copy drs://my-drs-url local_filepath

The VCF API and CLI

terra-notebook-utils provides some CLI commands useful for getting information about VCF files. These commands work for VCFs stored locally, in a Google Storage bucket, or at a DRS url.

Print VCF header:

tnu vcf head drs://my-vcf
tnu vcf head gs://my-vcf
tnu vcf head my.vcf.gz

Print VCF samples:

tnu vcf samples drs://my-vcf
tnu vcf samples gs://my-vcf
tnu vcf samples my.vcf.gz

Print VCF stats. This command executes quickly, and shows the length and file size of the VCF. If the VCF is compressed, the compressed size is returned.

tnu vcf stats drs://my-vcf
tnu vcf stats gs://my-vcf
tnu vcf stats my.vcf.gz

While a Python API for working with VCFs is currently available, usage is more complex. Please contact the maintainer for more information.

Local Development

For local development:

1. Make the decision whether you want to run this using your local environment, or develop from within a docker image. Developing within a docker image is recommended, since that most closely models how users will use this. Additionally, there are some issues with installing the requirements.txt on mac. If you don't wish to run this within a docker image, skip to step 5.
2. run docker pull us.gcr.io/broad-dsp-gcr-public/terra-jupyter-python:0.0.12
3. run the image from one directory above the root directory of this repo via docker run -itd --entrypoint='/bin/bash' -v $PWD/terra-notebook-utils:/work -u root -e PIP_USER=false --name test-image terra-jupyter-python:0.0.12
4. Attach your terminal to the image via docker exec -it test-image bash, then navigate to the directory the code is mounted to via cd /work. Note that the above command ensures any changes you make to files in the repo will be updated in the image as well.
5. log in with your Google credentials using gcloud auth application-default login,
6. install requirements with pip install -r requirements.txt
7. set up the following environment variables, depending on what you will be using:

• export GOOGLE_PROJECT=[validProject]
• export WORKSPACE_NAME=[workspaceWithinProject]
• export TERRA_DEPLOYMENT_ENV=dev
• export WORKSPACE_BUCKET=[bucketWithinWorkspace]

8. run the python shell via python, and import any modules you wish to use. For example, from terra_notebook_utils import drs

A sample non-protected test DRS url that resolves to a small file in dev: drs://dg.712C/fa640b0e-9779-452f-99a6-16d833d15bd0

Tests

To run tests,

1. log in with your Google credentials using gcloud auth application-default login,
2. Your account must have access to the workspace terra-notebook-utils-tests
3. Run export GOOGLE_PROJECT=firecloud-cgl; export TERRA_DEPLOYMENT_ENV=prod; export WORKSPACE_NAME=terra-notebook-utils-tests
4. install requirements with pip install -r requirements-dev.txt,
5. run make test in the package root.

Links

Project home page GitHub
Package distribution PyPI

Bugs

Please report bugs, issues, feature requests, etc. on GitHub.