Bento Library (for Python Bento microservices)
Common utilities and helpers for Bento platform services.
Installing
bento_lib can be added to a new service through normal installation, with any extras
that may be needed:
# Add to a project using Poetry for dependencies
poetry add bento_lib
# Install using pip with the FastAPI extra
pip install bento_lib[fastapi]
# etc...
Developing
Clone the repository and set up the Poetry environment using the following commands:
git clone git@github.com:bento-platform/bento_lib.git
poetry install --all-extras
Running Tests
For tests to complete successfully, the following external servers must be running:
- A Redis server at
localhost:6379 - A Postgres server at
localhost:5432withpeeraccess for thepostgresrole/database
Then, tests and linting can be run with the following command:
poetry run tox
Releasing
1. Release Checklist
-
All tests pass and test coverage has not been reduced
-
Package version has been updated (following semver) in
pyproject.toml -
The latest changes have been merged into the
masterbranch -
A release has been created, tagged in the format of
v#.#.#and named in the format ofVersion #.#.#, listing any changes made, in the GitHub releases page tagged from the master branch!
1A. Note on Versioning
The bento_lib project uses semantic versioning for
releasing. If the API is broken in any way, including minor differences in the
way a function behaves given an identical set of parameters (excluding bugfixes
for unintentional behaviour), the MAJOR version must be incremented. In this
way, we guarantee that projects relying on this API do not accidentally break
upon upgrading.
2. Releasing automatically
When a version is tagged on GitHub, a build + release CI pipeline is automatically triggered.
Make sure that the tagged version is a valid semantic versioning translation of the version in
pyproject.toml, and that the versions otherwise match.
Modules
apps
apps provides Python classes for setting up applications, wrapping a framework's base class with
additional code to set up error handling and basic Bento service boilerplate.
auth
auth provides Python service middleware for dealing with the Bento authorization service.
db
db contains common base classes for setting up database managers.
discovery
discovery contains models and helper functions for the Bento Discovery Configuration specification, used
in Katsu.
Guides
drs
drs provides utilities for fetching data and record metadata from
GA4GH-compatible DRS services, and Bento's own implementation (which has some
non-standard extensions.)
events
events facilitates JSON-serialized message-passing between Bento
microservices. Serialized objects can be at most 512 MB.
Events should have a lower-case type which is type-insensitively unique and adequately describes the associated data.
All Bento channels are prefixed with bento..
i18n
i18n provides language literals and mixin model for handling pydantic models which are language specific.
logging
logging contains helper functions and types for standardized Bento logging
configuration and formatting, including structured logging using
structlog.
Guides
ontologies
ontologies contains models, types, and helpers for working with ontology classes,
especially in the context of classes which must be eventually ingested into
Katsu.
Guides
provenance
provenance contains Pydantic models for dataset provenance metadata, used
for describing datasets with rich contextual information including stakeholders,
funding sources, publications, licenses, and spatial coverage. The main model,
DatasetModel, provides a standardized schema for dataset metadata used in
Katsu.
The module also includes converters for transforming external dataset formats (e.g., PCGL) into the Bento dataset model.
responses
responses contains standardized error message-generating functions
and exception handling functions for different Python web frameworks.
schemas
schemas contains common JSON schemas which may be useful to a variety of
different Bento services.
schemas.bento contains Bento-specific schemas, and schemas.ga4gh contains
GA4GH-standardized schemas (possibly not exactly to spec.)
search
search contains definitions, validators, and transformations for the query
syntax for Bento, as well as a transpiler to the psycopg2 PostgreSQL IR.
The query syntax for Bento takes advantage of JSON schemas augmented with additional properties about the field's accessibility and, in the case of Postgres, how the field maps to a table column (or JSON column sub-field.)
search.data_structure contains code for evaluating a Bento query against a
Python data structure.
search.operations contains constants representing valid search operations one
can allow against particular fields from within an augmented JSON schema.
search.postgres contains a "transpiler" from the Bento query syntax to the
psycopg2-provided
intermediate representation (IR) for
PostgreSQL, allowing safe queries against a Postgres database.
search.queries provides definitions for the Bento query AST and some helper
methods for creating and processing ASTs.
service_info
service_info contains Python typed dictionaries, Pydantic models, and helpers
for common structures and operations related to GA4GH's /service-info
specification.
Guides
streaming
streaming contains helper code for streaming bytes via HTTP from files, and
proxied HTTP resources, including exception definitions and HTTP Range header
parsing.
utils
Small common-use utilities for Bento services and other libraries.
workflows
workflows contains common code used for handling workflow metadata processing
and response generation, as well as code associated with Bento's ingestion
routines across the different data services.
1 maintainer
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