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.

For development:

pip install -e .[dev]

To update dependency versions:

make update

To use pinned dependencies for reproducible testing:

make

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...