nsidc-metgen
via the MetGenC utility, enables Operations staff and data
producers to create metadata files conforming to NASA's Common Metadata Repository UMM-G
specification and ingest data directly to NASA EOSDIS’s Cumulus archive. Cumulus is an
open source cloud-based data ingest, archive, distribution, and management framework
developed for NASA's Earth Science data.
This repository is fully supported by NSIDC. If you discover any problems or bugs, please submit an Issue. If you would like to contribute to this repository, you may fork the repository and submit a pull request.
See the LICENSE for details on permissions and warranties. Please contact [email protected] for more information.
To use the nsidc-metgen
command-line tool, metgenc
, you must first have
Python version 3.12 installed. To determine the version of Python you have, run
this at the command-line:
$ python --version
or
$ python3 --version
Next, install Poetry by using the official installer if you’re comfortable with the instructions, or by installing it using a package manager (like Homebrew) if this is more familiar to you. When successfully installed, you should be able to run:
$ poetry --version
Poetry (version 1.8.3)
Finally, install the AWS commandline interface (CLI) by following the appropriate instructions for your platform.
- Checksums are all SHA256
- In the data files to be ingested:
- The global attribute "date_modified" exists and will be used to represent the production date and time.
- Global attributes "time_coverage_start" and "time_coverage_end" exist and will be used for the time range metadata values.
- Only one coordinate system is used by all variables (i.e. only one grid mapping variable is present in a file)
- (x[0],y[0]) represents the upper left corner of the spatial coverage.
- x,y coordinates represent the center of the pixel
- The grid mapping variable contains a GeoTransform attribute (which defines the pixel size ), and can be used to determine the padding added to x and y values.
- Date/time strings can be parsed using
datetime.fromisoformat
Make a local directory (i.e., on your computer), and then cd
into that
directory. Clone the granule-metgen
repository using ssh if you have added
ssh keys to your GitHub
account
or https if you have not:
$ mkdir -p ~/my-projects; cd ~/my-projects
# Install using ssh:
$ git clone [email protected]:nsidc/granule-metgen.git
# Install using https:
$ git clone https://github.com/nsidc/granule-metgen.git
Enter the granule-metgen
directory and run Poetry to have it install the granule-metgen
dependencies. Then start a new shell in which you can run the tool:
$ cd granule-metgen
$ poetry install
$ poetry shell
With the Poetry shell running, start the metgenc tool just to verify that it’s working by requesting its usage options and having them returned (there’s more to do—explained in the Usage section below—before MetGenC can be run successfully to create ummg, cnm, and stage data!)::
$ metgenc --help
Usage: metgenc [OPTIONS] COMMAND [ARGS]...
Options:
--help Show this message and exit.
Commands:
info
init
process
In order to process science data and stage it for Cumulus, you must first create & setup your AWS credentials. Two options for doing this are detailed here:
First, create a directory in your user's home directory to store the AWS configuration:
$ mkdir -p ~/.aws
In the ~/.aws
directory, create a file named config
with the contents:
[default]
region = us-west-2
output = json
In the ~/.aws
directory, create a file named credentials
with the contents:
[default]
aws_access_key_id = TBD
aws_secret_access_key = TBD
Finally, restrict the permissions of the directory and files:
$ chmod -R go-rwx ~/.aws
When you obtain the AWS key pair (not covered here), edit the ~/.aws/credentials
file
and replace TBD
with the public and secret key values.
You may install (or already have it installed) the AWS Command Line Interface on the machine where you are running the tool. Follow the AWS CLI Install instructions for the platform on which you are running.
Once you have the AWS CLI, you can use it to create the ~/.aws
directory and the
config
and credentials
files:
$ aws configure
You will be prompted to enter your AWS public access and secret key values, along with the AWS region and CLI output format. The AWS CLI will create and populate the directory and files with your values.
If you require access to multiple AWS accounts, each with their own configuration--for example, different accounts for pre-production vs. production--you can use the AWS CLI 'profile' feature to manage settings for each account. See the AWS configuration documentation for the details.
When you have data files, a Cumulus Collection and its Rules established in the Cumulus Dashboard, you’re ready to run MetGenC to generate umm-g files, cnm messages, and kick off data ingest directly to Cumulus! Note: MetGenC can be run without a Cumulus Collection ready, it will only function to output umm-g metadata files and cnm messages.
-
Show the help text:
$ metgenc --help
Usage: metgenc [OPTIONS] COMMAND [ARGS]...
The metgenc utility allows users to create granule-level metadata, stage
granule files and their associated metadata to Cumulus, and post CNM
messages.
Options:
--help Show this message and exit.`
Commands:
info Summarizes the contents of a configuration file.
init Populates a configuration file based on user input.
process Processes science data files based on configuration file...
For detailed help on each command, run: metgenc --help`, for example:
$ metgenc process --help
Usage: metgenc process [OPTIONS]
Processes science data files based on configuration file contents.
Options:
-c, --config TEXT Path to configuration file [required]
-e, --env TEXT environment [default: uat]
-n, --number count Process at most 'count' granules.
-wc, --write-cnm Write CNM messages to files.
-o, --overwrite Overwrite existing UMM-G files.
--help Show this message and exit.
-
Show summary information about an
metgenc
configuration file. Here we use the example configuration file provided in the repo:$ metgenc info --config example/modscg.ini
-
Process science data and stage it for Cumulus:
# Source the AWS profile (once) before running 'process'-- use 'default' or a named profile $ source scripts/env.sh default $ metgenc process --config example/modscg.ini
-
Exit the Poetry shell:
$ exit
TBD
-
Use Poetry to create and activate a virtual environment
$ poetry shell
-
Install dependencies
$ poetry install
$ poetry run pytest
Run tests when source changes (uses pytest-watcher):
$ poetry run ptw . --now --clear
This content was developed by the National Snow and Ice Data Center with funding from multiple sources.