Spawn MongoDB resources from JSON Schema
Project description
mongospawn is a tool to help spawn MongoDB resources given JSON Schema
specifications.
The primary near-term use case is support for the National Microbiome Data
Collaborative (NMDC) pilot project. In particular,
given a JSON Schema with all array-typed properties and with each array item a
$ref reference to one of the JSON Schema definitions (see NMDC
example),
mongospawn can generate MongoDB $jsonSchema documents to apply as validators
for collections in a database that correspond to each of the original JSON
Schema's array-typed properties. MongoDB's implementation of JSON Schema does
not support $ref, definitions, etc., so mongospawn expands references to
generate appropriate per-collection schema documents.
In addition to generating derived schema documents, mongospawn can spawn new
databases/collections, with schema validation set, via the pymongo driver, and
can also manage access to the spawned resources via mongogrant.
Setup
For development:
pip install -e .[dev]
To update dependency versions:
make update
To use pinned dependencies for reproducible testing:
make
Usage
Example using NMDC's JSON Schema:
from mongospawn.schema import dbschema_from_file, collschemas_for
from pymongo import MongoClient
client = MongoClient()
db = client.nmdc_test
dbschema = dbschema_from_file("nmdc.schema.json")
collschemas = collschemas_for(dbschema)
for name in collschemas:
db.drop_collection(name)
db.create_collection(name, validator={"$jsonSchema": collschemas[name]})
print(f"created {name} collection")
# created activity_set collection
# created biosample_set collection
# created data_object_set collection
# created omics_processing_set collection
# created study_set collection
Now, e.g. if you try to insert a non-conformant JSON document, a
pymongo.errors.WriteError will be raised:
db.biosample_set.insert_one({"not_a_real_field": 1})
# => WriteError: Document failed validation...
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