NASA-PDS / operations

Tickets for the PDSEN Operations Team
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NASA PDS Engineering Node Operations Team

This repository is a repo to track issues intended for the Planetary Data System (PDS) Engineering Node (EN) Operations Team. These issues may include, but are not limited to, PDS4 NSSDCA Deliveries via PDS Deep Archive, data releases, website updates, or other actions where a corresponding GitHub repository is unknown.

Support

For help with the PDS Engineering Node, you can either create a ticket in GitHub Issues or email pds-operator@jpl.nasa.gov for more assistance.

Installation

This section specifies the requirements needed to run the software in this repository and gives narrative instructions on performing the installation.

System Requirements

Prior to installing this software, ensure your system meets the following requirements:

Consult your operating system instructions or system administrator to install the required packages. For those without system administrator access and are feeling anxious, you could try a local (home directory) Python 3 installation using a Miniconda installation.

Doing the Installation

We will install the operations too using Python Pip, the Python Package Installer. If you have Python on your system, you probably already have Pip; you can run pip --help or pip3 -help to check.

It's best install the tools virtual environment, so it won’t interfere with—or be interfered by—other packages. To do so:

$ # Clone the repo or do a git pull if it already exists
$ git clone https://github.com/NASA-PDS/pdsen-operations.git
$ cd pdsen-operations
$ # For Linux, macOS, or other Unix systems:
$ mkdir -p $HOME/.virtualenvs
$ python3 -m venv $HOME/.virtualenvs/pdsen-ops
$ source $HOME/.virtualenvs/pdsen-ops/bin/activate
$ pip3 install --requirement requirements.txt

pds-stats.py

The pds-stats.py script can be used to get the total download metrics for GitHub software tools. Here is an example of how to get metrics for the Validate, MILabel, and Transform tools.

For usage information run bin/pds-stats.py --help

Example Usage

  1. Activate your virtual environment:

    source $HOME/.virtualenvs/pdsen-ops/bin/activate
  2. Execute the script:

    bin/pds-stats.py --github_repos validate mi-label transform --token $GITHUB_TOKEN

ldd-corral.py

This utility is used to autonomously generate the data dictionaries web page for each PDS4 Build.

This software determines all the discipline LDDs to be included with this release, auto-generates the web page, and downloads and stages all the discipline LDDs from the LDD Github repos.

Configuration

The ldd-corral configuration can be modified to add additional discipline LDDs to the workflow.

Format:

<github-repo-name>:
    name: a title to be used in the output web page that overrides the <name> from the repo IngestLDD
    description: |
        description here

Usage

For latest usage capabilities:

bin/ldds/ldd-corral.py  --help

Base usage example (note: the GITHUB_TOKEN environment variable must be set):

$ source $HOME/.virtualenvs/pdsen-ops/bin/activate
$ ldd-corral.py  --pds4_version 1.15.0.0 --token $GITHUB_TOKEN

Default outputs:


LDD Utility Scripts

The LDD utility script prep_for_ldd_release.sh is usually run as follows:

  1. Execute bin/prep_for_ldd_release.sh script as follows to create new branches in all Discipline LDD repositories:

TBD

  1. Go to each Discipline LDD Repo and create Pull Requests for each new branch (branch names like IM_release_1.15.0.0).

    • PR Title: PDS4 IM Release <IM_version>
    • PR Description:
      
      ## Summary

    PR for testing LDD with new IM release.

    
    - PR Labels: `release`
  2. If build failed on new branch, contact the LDD Steward to investigate a potential regression test failure or incompatibility with the new IM version.