bas-metadata-library 0.3.0

Python library for generating metadata records

BAS Metadata Library

Python library for generating metadata records.

Purpose

This library is designed to assist in generating metadata records for the discovery of datasets. As a library, this package is intended to be embedded within other tools and services, to avoid the need to implement the complexity and verbosity of specific metadata standards.

This library is built around the needs of the British Antarctic Survey and NERC Polar Data Centre. This means only standards, and elements of these standards, used by BAS or the UK PDC are supported. Additions that would enable this library to be useful to others are welcome as contributions.

Supported standards

Standard	Implementation	Library Namespace	Introduced In
ISO 19115:2003	ISO 19139:2007	bas_metadata_library.standards.iso_19115_1_v1	#46
ISO 19115-2:2009	ISO 19139-2:2012	bas_metadata_library.standards.iso_19115_2_v1	#50

Note: In this library ISO 19115:2003 is referred to as ISO-19115-1 (iso_19115_1_v1) for consistency with ISO 19115-2:2009 (referred to as ISO-19115-2, iso_19115_2_v1). As ISO have subsequently created ISO 19115-1:2014 this creates a conflict/ambiguity. To resolve this without making breaking changes, ISO 19115-1:2014 will be referred to as ISO-19115-3 when added to this library.

Supported profiles

Standard	Profile	Implementation	Library Namespace	Introduced In
ISO 19115:2003	EU Inspire	UK Gemini	bas_metadata_library.standards.iso_19115_1_v1.profiles.inspire_v1_3	#40
ISO 19115:2003	UK Polar Data Centre Discovery Metadata	-	bas_metadata_library.standards.iso_19115_1_v1.profiles.uk_pdc_discovery_v1	#45
ISO 19115-2:2009	EU Inspire	UK Gemini	bas_metadata_library.standards.iso_19115_2_v1.profiles.inspire_v1_3	#40
ISO 19115-2:2009	UK Polar Data Centre Discovery Metadata	-	bas_metadata_library.standards.iso_19115_2_v1.profiles.uk_pdc_discovery_v1	#45

Installation

This package can be installed using Pip from PyPi:

$ pip install bas-metadata-library

Usage

To generate an ISO 19115 metadata record and return it as an XML document:

from bas_metadata_library.standards.iso_19115_2_v1 import MetadataRecordConfig, MetadataRecord

minimal_record_config = {
    "contacts": [{"role": ["pointOfContact"]}],
    "date_stamp": datetime(2018, 10, 18, 14, 40, 44, tzinfo=timezone.utc),
    "resource": {
        "title": {"value": "Test Record"},
        "dates": [{"date": date(2018, 1, 1), "date_precision": "year", "date_type": "creation"}],
        "abstract": "Test Record for ISO 19115-2:2009 metadata standard (no profile) with required properties only.",
        "language": "eng",
    },
}

configuration = MetadataRecordConfig(**minimal_record_config)
record = MetadataRecord(configuration=configuration)
document = record.generate_xml_document()

# output document
print(document)

Where metadata_configs.record is a Python dictionary implementing the BAS metadata generic schema, documented in the BAS Metadata Standards project.

To reverse this process and convert an XML record into a configuration object:

from bas_metadata_library.standards.iso_19115_2_v1 import MetadataRecord

with open(f"minimal-record.xml") as record_file:
    record_data = record_file.read()

record = MetadataRecord(record=record_data)
configuration = record.make_config()
minimal_record_config = configuration.config

# output configuration
print(minimal_record_config)

HTML entities

Do not include HTML entities in input to this generator, as it will be douple escaped by Lxml, the underlying XML processing library.

This means >, the HTML entity for >, will be escaped again to > which will not be correctly interpreted when decoded. Instead the literal character should be used (e.g. >), which Lxml will escape if needed.

This applies to any unicode character, such as accents (e.g. å) and symbols (e.g. µ).

Implementation

This library consists of a set of base classes using lxml for generating XML based metadata records from a configuration object, or generating a configuration object from an XML record.

Each supported standard implements these classes for supported elements as per their respective standard. Two methods are implemented, make_element() builds an XML element using values from a configuration object, make_config() typically uses XPath expressions to build a configuration object from XML. These element classes are combined to generate complete metadata records or configuration objects.

Configuration objects are python dicts, the properties and values of which are defined by, and validated against, a JSON Schema.

See the development section for more information on the base classes used across all standards and how to add a new standard.

Setup

Terraform

Terraform is used to provision resources required to operate this application in staging and production environments.

These resources allow Configuration schemas for each standard to be accessed externally.

Access to the BAS AWS account is needed to provisioning these resources.

Note: This provisioning should have already been performed (and applies globally). If changes are made to this provisioning it only needs to be applied once.

# start terraform inside a docker container
$ cd provisioning/terraform
$ docker-compose run terraform
# setup terraform
$ terraform init
# apply changes
$ terraform validate
$ terraform fmt
$ terraform apply
# exit container
$ exit
$ docker-compose down

Terraform remote state

State information for this project is stored remotely using a Backend.

Specifically the AWS S3 backend as part of the BAS Terraform Remote State project.

Remote state storage will be automatically initialised when running terraform init. Any changes to remote state will be automatically saved to the remote backend, there is no need to push or pull changes.

Remote state authentication

Permission to read and/or write remote state information for this project is restricted to authorised users. Contact the BAS Web & Applications Team to request access.

See the BAS Terraform Remote State project for how these permissions to remote state are enforced.

Development

This API is developed as a Python library. A bundled Flask application is used to simulate its usage and to act as framework for running tests etc.

$ git clone https://gitlab.data.bas.ac.uk/uk-pdc/metadata-infrastructure/metadata-generator.git
$ cd metadata-generator

Development environment

Docker and Docker Compose are required to setup a local development environment of this application.

If you have access to the BAS GitLab instance, you can pull the application Docker image from the BAS Docker Registry. Otherwise you will need to build the Docker image locally.

# If you have access to gitlab.data.bas.ac.uk:
$ docker login docker-registry.data.bas.ac.uk
$ docker-compose pull
# If you don't have access:
$ docker-compose build

To run the application using the Flask development server (which reloads automatically if source files are changed):

$ docker-compose up

To run other commands against the Flask application (such as Integration tests):

# in a separate terminal to `docker-compose up`
$ docker-compose run app flask [command]
# E.g.
$ docker-compose run app flask test
# List all available commands
$ docker-compose run app flask

Library base classes

The bas_metadata_library module defines a series of modules for each standard (in bas_metadata_library.standards) as well as base classes used across all standards, that providing common functionality. See existing standards for how these are used.

Configuration schemas

This library accepts a 'configuration' for each metadata record. This contains values for elements, or values that are used to compute values. For example, a title element would use a value taken directly from the record configuration.

To ensure all required configuration attributes are included, and where relevant that their values are allowed, this configuration is validated against a schema. This schema uses the JSON Schema standard.

Configuration schemas are stored as JSON files in bas_metadata_library.standards_schemas and loaded as resource files within this package. Schemas are also made available externally through the BAS Metadata Standards website metadata-standards.data.bas.ac.uk to allow:

1. other applications to ensure their output will be compatible with this library, but that can't use this library
2. to allow schema inheritance/extension where used for standards that inherit from other standards (such as profiles)

JSON Schema's can be developed using jsonschemavalidator.net.

Adding a new standard

To add a new standard:

1. create a new module in bas_metadata_library.standards/ e.g. bas_metadata_library.standards.foo_v1/__init__.py
2. in this module, overload the Namespaces, MetadataRecordConfig and MetadataRecord classes as needed
3. create a suitable metadata configuration JSON schema in bas_metadata_library.standards_schemas/ e.g. bas_metadata_library.standards_schemas/foo_v1/configuration-schema.json
4. add a script line to the publish-schemas-stage and publish-schemas-prod to copy the configuration schema to the relevant S3 buckets for external access
5. define a series of test configurations (e.g. minimal, typical and complete) for generating test records in tests/resources/configs/ e.g. tests/resources/configs/foo_v1_standard.py
6. update the inbuilt Flask application in app.py with a route for generating test records for the new standard
7. use the inbuilt Flask application to generate the test records and save to tests/resources/records/
8. add relevant tests with methods to test each metadata element class and test records

Code Style

PEP-8 style and formatting guidelines must be used for this project, with the exception of the 80 character line limit.

Black is used to ensure compliance, configured in pyproject.toml.

Black can be integrated with a range of editors, such as PyCharm, to perform formatting automatically.

To apply formatting manually:

$ docker-compose run app black bas_metadata_library/

To check compliance manually:

$ docker-compose run app black --check bas_metadata_library/

Checks are ran automatically in Continuous Integration.

Dependencies

Python dependencies for this project are managed with Poetry in pyproject.toml.

Non-code files, such as static files, can also be included in the Python package using the include key in pyproject.toml.

Adding new dependencies

To add a new (development) dependency:

$ docker-compose run app ash
$ poetry add [dependency] (--dev)

Then rebuild the development container, and if you can, push to GitLab:

$ docker-compose build app
$ docker-compose push app

Updating dependencies

$ docker-compose run app ash
$ poetry update

Then rebuild the development container, and if you can, push to GitLab:

$ docker-compose build app
$ docker-compose push app

Static security scanning

To ensure the security of this API, source code is checked against Bandit for issues such as not sanitising user inputs or using weak cryptography.

Warning: Bandit is a static analysis tool and can't check for issues that are only be detectable when running the application. As with all security tools, Bandit is an aid for spotting common mistakes, not a guarantee of secure code.

Through Continuous Integration, each commit is tested.

To check locally:

$ docker-compose run app bandit -r .

Editor support

PyCharm

A run/debug configuration, App, is included in the project.

Testing

All code in the bas_metadata_library module must be covered by tests, defined in tests/. This project uses PyTest which should be ran in a random order using pytest-random-order.

Tests are written to create metadata records based on a series of configurations defined in tests/config.py. These define 'minimal' to 'complete' test records, intended to test different ways a standard can be used, both for individual elements and whole records. These tests are designed to ensure that records are generally well-formed and that where config options are used the corresponding elements in the metadata record are generated.

As this library does not seek to support all possible elements and variations within each standard, these tests are similarly not exhaustive, nor are they a substitute for formal metadata validation.

Test methods are used to test individual elements are formed correctly. Comparisons against static records are used to test the structure of whole records.

To run tests manually from the command line:

$ docker-compose run app pytest --random-order

To run tests manually using PyCharm, use the included App (Tests) run/debug configuration.

Tests are ran automatically in Continuous Integration.

Capturing static test records

To capture static test records, which verify complete records are assembled correctly, a custom Flask CLI command, capture-test-records is available. This requires the Flask application to first be running. The Requests library is used to make requests against the Flask app save responses to a relevant directory in tests/resources/records.

# start Flask application:
$ docker-compose up
# then in a separate terminal:
$ docker-compose run app flask capture-test-records

It is intended that this command will update pre-existing static records, with differences captured in version control and reviewed manually to ensure they are correct.

Test coverage

pytest-cov is used to measure test coverage.

To prevent noise, .coveragerc is used to omit empty __init__.py files from reports.

To measure coverage manually:

$ docker-compose run app pytest --random-order --cov=bas_metadata_library --cov-fail-under=100 --cov-report=html .

Continuous Integration will check coverage automatically and fail if less than 100%.

Continuous Integration

All commits will trigger a Continuous Integration process using GitLab's CI/CD platform, configured in .gitlab-ci.yml.

Deployment

Python package

This project is distributed as a Python package, hosted in PyPi.

Source and binary packages are built and published automatically using Poetry in Continuous Delivery.

Package versions are determined automatically using the support/python-packaging/parse_version.py script.

Continuous Deployment

A Continuous Deployment process using GitLab's CI/CD platform is configured in .gitlab-ci.yml.

Release procedure

For all releases:

1. create a release branch
2. close release in CHANGELOG.md
3. push changes, merge the release branch into master and tag with version

Feedback

The maintainer of this project is the BAS Web & Applications Team, they can be contacted at: [e-mail].

Issue tracking

This project uses issue tracking, see the Issue tracker for more information.

Note: Read & write access to this issue tracker is restricted. Contact the project maintainer to request access.

License

© UK Research and Innovation (UKRI), 2019 - 2020, British Antarctic Survey.

You may use and re-use this software and associated documentation files free of charge in any format or medium, under the terms of the Open Government Licence v3.0.

You may obtain a copy of the Open Government Licence at http://www.nationalarchives.gov.uk/doc/open-government-licence/