lco-ingester 2.1.15

Ingest frames into the LCO Archive

Ingester Library

A library for adding new science data products to an observatory control system's science archive. The library handles uploading FITS files into AWS S3, as well as adding records to the science archive's database containing the searchable metadata of all available FITS files.

Prerequisites

Optional prerequisites may be skipped for reduced functionality.

• Python >= 3.6
• A running science archive
• Write access to the same S3 bucket that the running science archive is using
• (Optional) A running OpenTSDB for metrics collection

Installation

It is highly recommended that you install and run your python code inside a dedicated python virtual environment.

Add the lco_ingester package to your python environment:

(venv) $ pip install lco_ingester

Configuration

AWS and science archive credentials must be set in order to upload data. Science archive configuration as well as the AWS Bucket can be either passed explicitly or set as environment variables. The rest of the configuration must be set as environment variables.

Environment Variables

	Variable	Description	Default
Science Archive	API_ROOT	Science Archive URL	"http://localhost:8000/"
	AUTH_TOKEN	Science Archive Authentication Token. This token must be associated with an admin user.	empty string
AWS	BUCKET	AWS S3 Bucket Name	ingestertest
	AWS_ACCESS_KEY_ID	AWS Access Key with write access to the S3 bucket	empty string
	AWS_SECRET_ACCESS_KEY	AWS Secret Access Key	empty string
	AWS_DEFAULT_REGION	AWS S3 Default Region	empty string
Metrics	OPENTSDB_HOSTNAME	OpenTSDB Host to send metrics to	empty string
	OPENTSDB_PYTHON_METRICS_TEST_MODE	Set to any value to turn off metrics collection	False
	INGESTER_PROCESS_NAME	A tag set with the collected metrics to identify where the metrics are coming from	ingester
	SUBMIT_METRICS_ASYNCHRONOUSLY	Optionally submit metrics asynchronously. This option does not apply when the command line entrypoint is used, in which case metrics are always submitted synchronously. Note that some metrics may be lost when submitted asynchronously.	False
Postprocessing	FITS_BROKER	FITS exchange broker	memory://localhost
	PROCESSED_EXCHANGE_NAME	Processed files RabbitMQ Exchange Name	archived_fits
	POSTPROCESS_FILES	Optionally submit files to fits queue	True

For Developers

Running the Tests

After cloning this project, from the project root and inside your virtual environment:

(venv) $ pip install -r requirements.txt
(venv) $ pytest