Python library for generating metadata records
Project description
BAS Metadata Library
Python library for generating metadata records.
Overview
Purpose
This library is designed to assist in generating metadata records for the discovery of datasets, services and related resources. As a library, this project is intended to be used as a dependency within other tools and services, to avoid the need to duplicate the implementation of complex and verbose metadata standards.
This library is built around the needs of the British Antarctic Survey and NERC (UK) Polar Data Centre. This means only standards, and elements of these standards, used by BAS or the UK PDC are supported. However, additions that would enable this library to be useful to other organisations and use-case are welcome as contributions providing they do not add significant complexity or maintenance.
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, the ISO 19115:2003 standard 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
). In the future, the
ISO 19115-1:2014 standard will be referred to as ISO-19115-3.
Supported profiles
Standard | Profile | Implementation | Library Namespace | Introduced In |
---|---|---|---|---|
- | - | - | - | - |
Note: Support for profiles has been removed to allow underlying standards to be implemented more easily, and to wait until stable profiles for UK PDC Discovery metadata have been developed and approved.
Supported configuration versions
Standard | Profile | Configuration Version | Status | Notes |
---|---|---|---|---|
ISO 19115:2003 | - | v1 |
Deprecated | Deprecated version replaced by v2 |
ISO 19115:2003 | - | v2 |
Live | Stable version |
ISO 19115-2:2009 | - | v1 |
Deprecated | Deprecated version replaced by v2 |
ISO 19115-2:2009 | - | v2 |
Live | Stable version |
Installation
This package can be installed using Pip from PyPi:
$ pip install bas-metadata-library
Usage
Encode XML document from record configuration
To generate an ISO 19115 metadata record from a Python record configuration and return it as an XML document:
from datetime import date
from bas_metadata_library.standards.iso_19115_2 import MetadataRecordConfigV2, MetadataRecord
minimal_record_config = {
"hierarchy_level": "dataset",
"metadata": {
"language": "eng",
"character_set": "utf-8",
"contacts": [{"organisation": {"name": "UK Polar Data Centre"}, "role": ["pointOfContact"]}],
"date_stamp": date(2018, 10, 18),
},
"identification": {
"title": {"value": "Test Record"},
"dates": {"creation": {"date": date(2018, 1, 1), "date_precision": "year"}},
"abstract": "Test Record for ISO 19115 metadata standard (no profile) with required properties only.",
"character_set": "utf-8",
"language": "eng",
"topics": ["environment", "climatologyMeteorologyAtmosphere"],
"extent": {
"geographic": {
"bounding_box": {
"west_longitude": -45.61521,
"east_longitude": -27.04976,
"south_latitude": -68.1511,
"north_latitude": -54.30761,
}
}
},
},
}
configuration = MetadataRecordConfigV2(**minimal_record_config)
record = MetadataRecord(configuration=configuration)
document = record.generate_xml_document()
# output document
print(document.decode())
Loading a record configuration from JSON
The load()
and loads()
methods on the configuration class can be used to load a record configuration encoded as a
JSON file or JSON string respectively:
from pathlib import Path
from bas_metadata_library.standards.iso_19115_2 import MetadataRecordConfigV2
configuration = MetadataRecordConfigV2()
configuration.load(file=Path("/path/to/file.json"))
from bas_metadata_library.standards.iso_19115_2 import MetadataRecordConfigV2
configuration = MetadataRecordConfigV2()
configuration.loads(string='{"file_identifier": "696770d9-7cd8-40f0-b269-11af1687c772"}')
Disabling XML declaration
To disable the XML declaration (i.e. <?xml version='1.0' encoding='utf-8'?>
), you can set the xml_declaration
parameter to false. This is sometimes needed when the generated XML documented needs to be embedded into a larger
document, such as a CSW transaction.
# disable XML declaration
document = record.generate_xml_document(xml_declaration=False)
# output document
print(document)
Decode record configuration from XML document
To reverse this process and convert a XML record into a configuration object:
from bas_metadata_library.standards.iso_19115_2 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)
Migrating to new configuration versions
Version 1 to version 2
Note: The version 1 configuration schema is deprecated and will be removed in the next version #116.
Utility methods are provided within the V1 and V2 Record configuration classes to convert to and from the V2/V1 Record Configuration Schema.
Note: The version 1 and version 2 schemas are largely, but not fully, backwards compatible. Additional elements added to the version 2 schema (i.e. for elements the version 1 schema didn't support) will be dropped to prevent validation errors. For some elements (access/usage constraints), hard coded conversions are used for known use cases.
To convert a record configuration from version 1 to version 2 (lossless for known use cases):
from datetime import date
from bas_metadata_library.standards.iso_19115_1 import (
MetadataRecordConfigV1 as ISO19115_1_MetadataRecordConfigV1,
MetadataRecord as ISO19115_1_MetadataRecord,
)
configuration_object = {
"language": "eng",
"character_set": "utf-8",
"hierarchy_level": "dataset",
"contacts": [{"organisation": {"name": "UK Polar Data Centre"}, "role": ["pointOfContact"]}],
"date_stamp": date(2018, 10, 18),
"resource": {
"title": {"value": "Test Record"},
"dates": [{"date": date(2018, 1, 1), "date_precision": "year", "date_type": "creation"}],
"abstract": "Test Record for ISO 19115 metadata standard (no profile) with required properties only.",
"character_set": "utf-8",
"language": "eng",
"topics": ["environment", "climatologyMeteorologyAtmosphere"],
"extent": {
"geographic": {
"bounding_box": {
"west_longitude": -45.61521,
"east_longitude": -27.04976,
"south_latitude": -68.1511,
"north_latitude": -54.30761,
}
}
},
},
}
configurationV1 = ISO19115_1_MetadataRecordConfigV1(**configuration_object)
configurationV2 = configurationV1.convert_to_v2_configuration()
# encode converted configuration into an XML document
record = ISO19115_1_MetadataRecord(configurationV2)
document = record.generate_xml_document()
# output document
print(document)
To convert a record configuration from version 2 to version 1 (lossy):
from datetime import date
from bas_metadata_library.standards.iso_19115_1 import (
MetadataRecordConfigV2 as ISO19115_1_MetadataRecordConfigV2,
MetadataRecordConfigV1 as ISO19115_1_MetadataRecordConfigV1
)
configuration_object = {
"hierarchy_level": "dataset",
"metadata": {
"language": "eng",
"character_set": "utf-8",
"contacts": [{"organisation": {"name": "UK Polar Data Centre"}, "role": ["pointOfContact"]}],
"date_stamp": date(2018, 10, 18),
},
"identification": {
"title": {"value": "Test Record"},
"dates": {"creation": {"date": date(2018, 1, 1), "date_precision": "year"}},
"abstract": "Test Record for ISO 19115 metadata standard (no profile) with required properties only.",
"character_set": "utf-8",
"language": "eng",
"topics": ["environment", "climatologyMeteorologyAtmosphere"],
"extent": {
"geographic": {
"bounding_box": {
"west_longitude": -45.61521,
"east_longitude": -27.04976,
"south_latitude": -68.1511,
"north_latitude": -54.30761,
}
}
},
},
}
configurationV2 = ISO19115_1_MetadataRecordConfigV2(**configuration_object)
configurationV1 = ISO19115_1_MetadataRecordConfigV1()
configurationV1.convert_from_v2_configuration(configuration=configurationV2)
# print V1 configuration
print(configurationV1.config)
HTML entities
Do not include HTML entities in input to this generator, as they will be double escaped by Lxml, the
underlying XML processing library used by this project. Instead, literal characters should be used (e.g. >
), which
will be escaped as needed automatically. This applies to any unicode character, such as accents (e.g. å
) and
symbols (e.g. µ
).
E.g. If >
, the HTML entity for >
(greater than), were used as input, it would be escaped again to &gt;
which will not be valid output.
Linking transfer options and formats
To support generating a table of download options for a resource (such as [1]), this library uses a 'distribution option' concept to group related formats and transfer option elements in Record Configurations.
In ISO these elements are independent of each other, with no formal mechanism to associate formats and transfer options. As this library seeks to be fully reversible between a configuration object and XML, this information would be lost once records are encoded as XML.
To avoid this, this library uses the ID attribute available in both format and transfer option elements with values can be used when decoding XML to reconstruct these associations. This functionality should be fully transparent to the user, except for these auto-generated IDs being present in records.
See the Automatic transfer option / format IDs section for more details.
Note: Do not modify these IDs, as this will break this functionality.
[1]
Format | Size | Download Link |
---|---|---|
CSV | 68 kB | Link |
GeoPackage | 1.2 MB | Link |
Implementation
This library is implemented in Python and consists of a set of classes used to generate XML metadata records from a configuration object, or to generate a configuration object from an XML record.
Metadata Record classes
Each supported Standard and Supported Profile is implemented as a module
under bas_metadata_library.standards
(where profiles are implemented as modules under their respective standard).
For each, classes inherited from these parent classes are defined:
Namespaces
MetadataRecord
MetadataRecordConfig
The namespaces
class is a set of mappings between XML namespaces, their shorthand aliases and their definitions XSDs.
The MetadataRecord
class represents a metadata record and defines the Root Element. This class
provides methods to generate an XML document for example.
The MetadataRecordConfig
class represents the Configuration used to define values within a
MetadataRecord
, either for new records, or derived from existing records. This class provides methods to validate the
configuration used in a record for example.
Element classes
Each supported element, in each supported standard, inherit and use the MetadataRecordElement
class to:
- encode configuration values into an XML fragment of at least one element
- decode an XML fragment into one or more configuration values
Specifically, at least two methods are implemented:
make_element()
which builds an XML element using values from a configuration objectmake_config()
which uses typically XPath expressions to build a configuration object from XML
These methods may be simple (if encoding or decoding a simple free text value for example), or quite complex through the use of sub-elements (which themselves may contain sub-elements as needed).
Configuration classes
The configuration of each metadata record is held in a Python dictionary, within a MetadataRecordConfig
class. This
class includes methods to validate its configuration against a relevant Configuration Schema.
Configuration classes are defined at the root of each standard or profile, alongside its root Metadata Element and XML namespaces.
A configuration class will exist for each supported configuration schema with methods to convert from one version to another, see the Record configuration schema migration section for more information.
Configuration schemas
Allowed configuration values for each supported Standard and Supported Profile are described by a JSON Schema. These configuration schemas include which configuration properties are required, and in some cases, allowed values for these properties.
Configuration schemas are stored as JSON files in the bas_metadata_library.standards_schemas
module and loaded as
resource files from within this package. Schemas are also made available externally through the BAS Metadata Standards
website, metadata-standards.data.bas.ac.uk, to allow:
- other applications to ensure their output will be compatible with this library but that can't, or don't want to, use this library
- to allow schema inheritance/extension where used for standards that inherit from other standards (such as profiles)
Configuration schemas a versioned (e.g. v1
, v2
) to allow for backwards incompatible changes to be made.
Source and distribution schemas
Standards and profiles usually inherit from other standards and profiles. In order to prevent this creating huge duplication within configuration schemas, inheritance is used to incorporate a base schema and extend it as needed. For example, the ISO 19115-2 standard extends, and therefore incorporates the configuration schema for, ISO 19115-1.
JSON Schema references and identifier properties are used to implement this, using URIs within the BAS Metadata Standards website. Unfortunately, this creates a problem when developing these schemas, as if Schema B relies on Schema A, using its published identifier as a reference, the published instance of the schema will be used (i.e. the remote schema will be downloaded when Schema B is validated). If Schema A is being developed, and is not ready to be republished, there is a difference between the local and remote schemas used, creating unreliable tests for example.
To avoid this problem, a set of source schemas are used which use references to avoid duplication, from which a set
of distribution schemas are generated. These distribution schemas inline any references contained in their source
counterpart. These distribution schemas are therefore self-contained and can be updated locally without any
dependencies on remote sources. Distribution schemas are used by Configuration Classes and
published to the BAS Metadata Standards website, they are located in the bas_metadata_library.schemas.dist
module.
When editing configuration schemas, you should edit the source schemas, located in the
bas_metadata_library.schemas.src
module, then run the
regenerate distribution schemas using an internal command line utility.
JSON Schema's can be developed using jsonschemavalidator.net.
Adding a new standard
To add a new standard:
- create a new module under
bas_metadata_library.standards
, e.g.bas_metadata_library.standards.foo_v1/__init__.py
- in this module, overload the
Namespaces
,MetadataRecordConfig
andMetadataRecord
classes as needed - 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
- add a script line to the
publish-schemas-stage
andpublish-schemas-prod
jobs in.gitlab-ci.yml
, to publish the configuration schema within the BAS Metadata Standards website - 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
- update the inbuilt Flask application in
app.py
with a route for generating test records for the new standard - use the inbuilt Flask application to generate the test records and save to
tests/resources/records/
- add relevant tests with methods to test each metadata element class and test records
Adding a new element to an existing standard
[WIP]
- amend configuration schema:
- new or changed properties should be added to the configuration for the relevant standard (e.g. ISO 19115-1)
- typically, this involves adding new elements to the
definitions
property and referencing these in the relevant parent element (e.g. to theidentification
property)
- generate distribution schemas
- amend test configs:
- new or changed properties should be made to the relevant test record configurations in
tests/resources/configs/
- there are different levels of configuration, from minimal to complete, which should, where possible, build on each other (e.g. the complete record should include all the properties and values of the minimal record)
- the
minimum
configuration should not be changed, as all mandatory elements are already implemented - the
base_simple
configuration should contain elements used most of the time, that use free-text values - the
base_complex
configuration should contain elements used most of the time, that use URL or other identifier values - the
complete
configuration should contain examples of all supported elements, providing this still produces a valid record, in order to ensure high test coverage - where possible, configurations should be internally consistent, but this can be ignored if needed
- values used for identifiers and other external references should use the correct form/structure but do not need to exist or relate to the resource described by each configuration (i.e. DOIs should be valid URLs but could be a DOI for another resource for example)
- new or changed properties should be made to the relevant test record configurations in
- add relevant element class:
- new or changed elements should be added to the configuration for the relevant package for each standard
- for the ISO 19115 family of standards, element classes should be added to the
iso_19115_common
package - the exact module to use within this package will depend on the nature of the element being added, but in general,
elements should be added to the module of their parent element (e.g.
data_identification.py
for elements under theidentification
record configuration property), elements used across a range of elements should be added to thecommon_elements.py
module - remember to include references to new element class in the parent element class (in both the
make_element
andmake_config
methods)
- until support for Version 1 configuration schemas is removed, add logic to the
bas_metadata_library.standards.iso_19115_common.utils.convert_from_v1_to_v2_configuration
and/orbas_metadata_library.standards.iso_19115_common.utils.convert_from_v2_to_v1_configuration
methods as needed- for new elements, this usually consists of deleting configuration properties that don't exist in the V1 schema (as additional/unexpected keys are not allowed and will therefore fail validation)
- for existing elements, logic may be needed to both upgrade and downgrade configurations, especially where refactoring has occurred between V1 and V2 configurations
- where possible, such logic should be generic and agnostic to values used for configuration options, however there may be cases where this is unavoidable in order to produce a more complete translation between versions
- if such logic would prove very unwieldy, and not confined to a limited set of known circumstances, it is ok to not implement such logic, on the basis that supporting multiple versions is temporary
- capture test records
- initially this acts as a good way to check new or changed element classes encode configuration properties correctly
- check the git status of these test records to check existing records have changed how you expect (and haven't changed things you didn't intend to for example)
- add tests
- new test cases should be added, or existing test cases updated, in the relevant module within
tests/bas_metadata_library/
- for the ISO 19115 family of standards, this should be
test_standard_iso_19115_1.py
, unless the element is only part of the ISO 19115-2 standard - providing there are enough test configurations to test all the ways a new element can be used (e.g. with a simple text string or anchor element for example), adding a test case for each element is typically enough to ensure sufficient test coverage
- where this isn't the case, it's suggested to add one or more 'edge case' test cases to test remaining code paths explicitly
- new test cases should be added, or existing test cases updated, in the relevant module within
- check test coverage
- for missing coverage, consider adding edge case test cases where applicable
- wherever possible, the coverage exemptions should be minimised
- there are a number of general types of code that can be exempted as part of an existing convention (but that
will be reviewed in the future):
- within
make_config
methods to check whether child elements are empty - within the
convert_from_v1_to_v2_configuration
andconvert_from_v2_to_v1_configuration
utility methods
- within
- where exceptions are added, they should be documented as an issue with information on how they will be addressed in the longer term
- issue #111) will document existing exceptions and conventions, and look at how these can be removed in the future
- update
README.md
examples if common element- this is probably best done before releasing a new version
- update
CHANGELOG.md
- if needed, add name to
authors
property inpyproject.toml
Automatic transfer option / format IDs
ID attributes are automatically added to gmd:MD_Format
and gmd:MD_DigitalTransferOptions
elements in order to
reconstruct related formats and transfer options (see the
Linking transfer options and formats section for more information).
When a record is encoded, ID values are generated by hashing a JSON encoded string of the distribution object. This
ID is used as a shared base between the format and transfer option, with -fmt
appended for the format and -tfo
for the transfer option.
When a record is decoded, ID values are extracted (stripping the -fmt
/-tfo
suffixes) to index and then match up
format and transfer options back into distribution options. Any format and transfer options without an ID value, or
without a corresponding match, are added as partial distribution options.
As a worked example for encoding a (simplified) distribution object such as:
do = {
'format': 'csv',
'transfer_option': {
'size': '40',
'url': 'https://example.com/foo.csv'
}
}
Becomes:
'{"format":"csv","transfer_option":{"size":40,"url":"https://example.com/foo.csv"}}'
When encoded as a JSON encoded string, which when hashed becomes:
16b7b5df78a664b15d69feda7ccc7caed501f341
The ID value added to the gmd:MD_Format
element would be:
<gmd:MD_Format id="16b7b5df78a664b15d69feda7ccc7caed501f341-fmt">
And for the gmd:MD_DigitalTransferOptions
element:
<gmd:MD_DigitalTransferOptions id="16b7b5df78a664b15d69feda7ccc7caed501f341-tfo">
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, act as framework for running tests etc., and provide utility methods for generating schemas etc.
Development environment
Git, Docker and Docker Compose are required to set up a local development environment of this application.
If you have access to the BAS GitLab instance, you can clone the project and pull Docker images from the BAS GitLab instance and BAS Docker Registry.
$ git clone https://gitlab.data.bas.ac.uk/uk-pdc/metadata-infrastructure/metadata-generator.git
$ cd metadata-generator
$ docker login docker-registry.data.bas.ac.uk
$ docker compose pull
Otherwise, you will need to build the Docker image locally.
$ git clone https://github.com/antarctica/metadata-library.git
$ cd metadata-library
$ 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 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
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
$ apk update
$ apk add build-base cargo
$ poetry update
Then rebuild the development container, and if you can, push to GitLab:
$ docker compose build app
$ docker compose push app
jsonschema
package
The jsonschema
dependency is locked to version 3.2.0 because version 4.0 > dropped Python 3.6 support. This
library cannot require newer Python versions to ensure it can be used in projects that run on BAS IT infrastructure.
lxml
package
The lxml
dependency takes a long time to install/update inside the container image because it needs to be installed
from source each time the container is built. This is because Alpine Linux, used by the official Python Docker base
images, is not supported by the Python manylinux system, and therefore cannot use
pre-built, binary, wheels.
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 . -x './tests'
Editor support
PyCharm
A run/debug configuration, App, is included in the project.
Generating configuration schemas
To generate distribution schemas from source schemas, a custom Flask CLI command,
generate-schemas
is available. The jsonref
library is used to resolve
any references in source schemas and write the output as distribution schemas, replacing any existing output.
# then in a separate terminal:
$ docker compose run app flask generate-schemas
To configure this command, (e.g. to add a new schema for a new standard/profile), adjust the schemas
list in the
generate_schemas
method in manage.py
. This list should contain dictionaries with keys for the common name of the
schema (based on the common file name of the schema JSON file), and whether the source schema should be resolved or
simply copied. This should be true by default, and is only relevant to schemas that do not contain any references, as
this will cause an error if resolved.
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/resources/configs/
.
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.
Continuous Deployment
A Continuous Deployment process using GitLab's CI/CD platform is configured in .gitlab-ci.yml
.
Release procedure
For all releases:
- create a release branch
- close release in
CHANGELOG.md
- bump package version using
docker compose run app poetry version
- push changes, merge the release branch into
master
and tag with version
Feedback
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© UK Research and Innovation (UKRI), 2019 - 2021, British Antarctic Survey.
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
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