diff --git a/.gitignore b/.gitignore index ea82d36f..de307a60 100644 --- a/.gitignore +++ b/.gitignore @@ -160,4 +160,7 @@ repl.ipynb tests/nmdcdb/ -neon_cache.sqlite \ No newline at end of file +neon_cache.sqlite + +# output of changesheet generation +nmdc_runtime/site/changesheets/changesheets_output/ \ No newline at end of file diff --git a/README.md b/README.md index 292e4627..103df781 100644 --- a/README.md +++ b/README.md @@ -6,8 +6,8 @@ http://nmdcstatus.polyneme.xyz/ ## How It Fits In -* [nmdc-metadata](https://github.com/microbiomedata/nmdc-metadata) -tracks issues related to NMDC metadata, which may necessitate work across multiple repos. +* [issues](https://github.com/microbiomedata/issues) +tracks issues related to NMDC, which may necessitate work across multiple repos. * [nmdc-schema](https://github.com/microbiomedata/nmdc-schema/) houses the LinkML schema specification, as well as generated artifacts (e.g. JSON Schema). @@ -111,7 +111,7 @@ If you are connecting to resources that require an SSH tunnel—for example, a M The following command could be useful to you, either directly or as a template (see `Makefile`). ```shell -make nersc-ssh-tunnel +make nersc-mongo-tunnels ``` Finally, spin up the Docker Compose stack. diff --git a/components/nmdc_runtime/workflow_execution_activity/core.py b/components/nmdc_runtime/workflow_execution_activity/core.py index 8a550e80..ad7d020d 100644 --- a/components/nmdc_runtime/workflow_execution_activity/core.py +++ b/components/nmdc_runtime/workflow_execution_activity/core.py @@ -94,7 +94,9 @@ def insert_into_keys( workflow: Workflow, data_objects: list[DataObject] ) -> dict[str, Any]: """Insert data object url into correct workflow input field.""" - workflow_dict = workflow.dict() + workflow_dict = workflow.model_dump( + mode="json", + ) for key in workflow_dict["inputs"]: for do in data_objects: if workflow_dict["inputs"][key] == str(do.data_object_type): diff --git a/components/nmdc_runtime/workflow_execution_activity/spec.py b/components/nmdc_runtime/workflow_execution_activity/spec.py index 0ac56fa9..7ceb9fe4 100644 --- a/components/nmdc_runtime/workflow_execution_activity/spec.py +++ b/components/nmdc_runtime/workflow_execution_activity/spec.py @@ -6,10 +6,11 @@ WorkflowExecutionActivity, Database, ) -from pydantic import BaseModel +from pydantic import BaseModel, ConfigDict class ActivityTree(BaseModel): + model_config = ConfigDict(arbitrary_types_allowed=True) children: list["ActivityTree"] = [] data: WorkflowExecutionActivity spec: Workflow diff --git a/docker-compose.test.yml b/docker-compose.test.yml index c2a031c3..cb25e977 100644 --- a/docker-compose.test.yml +++ b/docker-compose.test.yml @@ -36,6 +36,7 @@ services: DAGSTER_POSTGRES_DB: "postgres_db" depends_on: - dagster-postgresql + restart: on-failure volumes: - ./:/opt/dagster/lib diff --git a/docker-compose.yml b/docker-compose.yml index 18cfdf5a..8b544298 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -36,6 +36,7 @@ services: DAGSTER_POSTGRES_DB: "postgres_db" depends_on: - dagster-postgresql + restart: on-failure volumes: - ./:/opt/dagster/lib diff --git a/docs/nb/get_data.ipynb b/docs/nb/get_data.ipynb index d76d4531..203c64b9 100644 --- a/docs/nb/get_data.ipynb +++ b/docs/nb/get_data.ipynb @@ -640,8 +640,7 @@ "32,590.4511390833583,590.450730484585,,33051017.328779608,174529.72008540362,95.62528562170476,-1,,,,,,,,unassigned,,,,,,,,,\n", "33,574.4557295997837,574.4553249571502,,57270445.86539885,179389.47009937343,165.6984621406013,-1,,,,,,,,unassigned,,,,,,,,,\n", "34,509.29372586837684,509.2933397523243,,3016102.9919072534,115624.41149005273,8.726379197243881,-1,,,,,,,,unassigned,,,,,,,,,\n", - "36,311.1007284631918,311.10042248349583,,2602658.391103224,220831.98006834995,7.530175230287296,-1,,,,,,,,unassigned,,,,,,,,,\n", - "\n" + "36,311.1007284631918,311.10042248349583,,2602658.391103224,220831.98006834995,7.530175230287296,-1,,,,,,,,unassigned,,,,,,,,,\n" ] } ], diff --git a/nmdc_runtime/__init__.py b/nmdc_runtime/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/nmdc_runtime/api/core/auth.py b/nmdc_runtime/api/core/auth.py index 9a4a7d34..fe026162 100644 --- a/nmdc_runtime/api/core/auth.py +++ b/nmdc_runtime/api/core/auth.py @@ -35,7 +35,7 @@ class TokenExpires(BaseModel): class Token(BaseModel): access_token: str token_type: str - expires: Optional[TokenExpires] + expires: Optional[TokenExpires] = None class TokenData(BaseModel): @@ -95,8 +95,25 @@ def __init__( super().__init__(flows=flows, scheme_name=scheme_name, auto_error=auto_error) async def __call__(self, request: Request) -> Optional[str]: - authorization: str = request.headers.get("Authorization") - scheme, param = get_authorization_scheme_param(authorization) + header_authorization: str = request.headers.get("Authorization") + cookie_authorization: str = f"Bearer {request.cookies.get('session')}" + header_scheme, header_param = get_authorization_scheme_param( + header_authorization + ) + cookie_scheme, cookie_param = get_authorization_scheme_param( + cookie_authorization + ) + scheme, param = "", "" + if header_scheme.lower() == "bearer": + authorization = True + scheme = header_scheme + param = header_param + elif cookie_scheme.lower() == "bearer": + authorization = True + scheme = cookie_scheme + param = cookie_param + else: + authorization = False if not authorization or scheme.lower() != "bearer": if self.auto_error: raise HTTPException( diff --git a/nmdc_runtime/api/core/util.py b/nmdc_runtime/api/core/util.py index 5aad716d..48d15ed1 100644 --- a/nmdc_runtime/api/core/util.py +++ b/nmdc_runtime/api/core/util.py @@ -98,6 +98,6 @@ def generate_secret(length=12): def json_clean(data, model, exclude_unset=False) -> dict: """Run data through a JSON serializer for a pydantic model.""" if not isinstance(data, (dict, BaseModel)): - raise TypeError("`data` must be a pydantic model or its .dict()") + raise TypeError("`data` must be a pydantic model or its .model_dump()") m = model(**data) if isinstance(data, dict) else data return json.loads(m.json(exclude_unset=exclude_unset)) diff --git a/nmdc_runtime/api/endpoints/find.py b/nmdc_runtime/api/endpoints/find.py index 4807c3d3..d2c712a9 100644 --- a/nmdc_runtime/api/endpoints/find.py +++ b/nmdc_runtime/api/endpoints/find.py @@ -266,7 +266,7 @@ def pipeline_search( response_model=PipelineFindResponse, response_model_exclude_unset=True, ) -def pipeline_search( +def pipeline_search_form( pipeline_spec: str = Form(...), description: str = Form(...), mdb: MongoDatabase = Depends(get_mongo_db), @@ -276,7 +276,7 @@ def pipeline_search( @router.get("/pipeline_search", response_class=HTMLResponse) -def pipeline_search( +def pipeline_search_get( mdb: MongoDatabase = Depends(get_mongo_db), ): template = jinja_env.get_template("pipeline_search.html") diff --git a/nmdc_runtime/api/endpoints/objects.py b/nmdc_runtime/api/endpoints/objects.py index 13cfa3aa..0dd3b443 100644 --- a/nmdc_runtime/api/endpoints/objects.py +++ b/nmdc_runtime/api/endpoints/objects.py @@ -78,7 +78,7 @@ def create_object( """ id_supplied = supplied_object_id( - mdb, client_site, object_in.dict(exclude_unset=True) + mdb, client_site, object_in.model_dump(mode="json", exclude_unset=True) ) drs_id = local_part( id_supplied if id_supplied is not None else generate_one_id(mdb, S3_ID_NS) @@ -255,7 +255,9 @@ def update_object( status_code=status.HTTP_403_FORBIDDEN, detail=f"client authorized for different site_id than {object_mgr_site}", ) - doc_object_patched = merge(doc, object_patch.dict(exclude_unset=True)) + doc_object_patched = merge( + doc, object_patch.model_dump(mode="json", exclude_unset=True) + ) mdb.operations.replace_one({"id": object_id}, doc_object_patched) return doc_object_patched diff --git a/nmdc_runtime/api/endpoints/operations.py b/nmdc_runtime/api/endpoints/operations.py index 1f1f67b3..ecb4d33e 100644 --- a/nmdc_runtime/api/endpoints/operations.py +++ b/nmdc_runtime/api/endpoints/operations.py @@ -61,12 +61,16 @@ def update_operation( detail=f"client authorized for different site_id than {site_id_op}", ) op_patch_metadata = merge( - op_patch.dict(exclude_unset=True).get("metadata", {}), + op_patch.model_dump(mode="json", exclude_unset=True).get("metadata", {}), pick(["site_id", "job", "model"], doc_op.get("metadata", {})), ) doc_op_patched = merge( doc_op, - assoc(op_patch.dict(exclude_unset=True), "metadata", op_patch_metadata), + assoc( + op_patch.model_dump(mode="json", exclude_unset=True), + "metadata", + op_patch_metadata, + ), ) mdb.operations.replace_one({"id": op_id}, doc_op_patched) return doc_op_patched diff --git a/nmdc_runtime/api/endpoints/portal.py b/nmdc_runtime/api/endpoints/portal.py new file mode 100644 index 00000000..8d406f9d --- /dev/null +++ b/nmdc_runtime/api/endpoints/portal.py @@ -0,0 +1,1236 @@ +"""API endpoints.""" + +from enum import Enum +from typing import Any, Dict, List, Optional, Tuple + +from fastapi import APIRouter, Depends, HTTPException, Query, Request, Response +from pymongo.database import Database as MongoDatabase +from nmdc_schema.nmdc_data import get_nmdc_file_type_enums +from pydantic import BaseModel, Field # pylint: disable=no-name-in-module + +from nmdc_runtime.api.endpoints.util import strip_oid_recursive +from nmdc_runtime.api.models.user import get_current_active_user, User +from nmdc_runtime.api.db.mongo import get_mongo_db + +router = APIRouter() + +BIOSAMPLE_SEARCH_COLLECTION = "biosample_denormalized" +OMICS_PROCESSING_SEARCH_COLLECTION = "omics_processing_denormalized" + + +# get application settings +# @router.get("/settings", name="Get application settings") +# async def get_settings() -> Dict[str, Any]: +# settings = Settings() +# return {"disable_bulk_download": settings.disable_bulk_download.upper() == "YES"} + + +# get the current user information +@router.get("/me", tags=["user"], name="Return the current user name") +async def me( + _request: Request, user: str = Depends(get_current_active_user) +) -> Optional[str]: + return user + + +# @router.get("/me/orcid", tags=["user"], name="Return the ORCID iD of current user") +# async def my_orcid( +# _request: Request, +# orcid: str = Depends(get_current_user_orcid) +# ) -> Optional[str]: +# return orcid + + +# autocomplete search +# @router.get("/search", tags=["aggregation"], response_model=List[query.ConditionResultSchema]) +# def text_search(terms: str, limit=6, db: Session = Depends(get_db)): +# return crud.text_search(db, terms, limit) + + +# database summary +@router.get( + "/summary", + tags=["aggregation"], +) +async def get_database_summary(): + """Return types and value ranges for each field.""" + return { + "biosample": { + "attributes": { + "depth.has_numeric_value": { + "min": 0, + "max": 2000, + "type": "float", + }, + "geo_loc_name.has_raw_value": { + "type": "string", + }, + "gold_classification": { + "type": "sankey-tree", + }, + "env_broad_scale.term.id": { + "type": "tree", + }, + "env_local_scale.term.id": { + "type": "tree", + }, + "env_medium.term.id": { + "type": "tree", + }, + "lat_lon.latitude": { + "type": "float", + "min": -90, + "max": 90, + }, + "lat_lon.longitude": { + "type": "float", + "min": -180, + "max": 180, + }, + "collection_date.has_date_value": { + "type": "date", + "min": "2000-03-15T00:00:00", + "max": "2022-08-12T00:00:00", + }, + }, + }, + "gene_function": { + "attributes": { + "id": { + "type": "kegg_search", + }, + }, + }, + "omics_processing": { + "attributes": { + "omics_type.has_raw_value": { + "type": "string", + }, + "instrument_name": { + "type": "string", + }, + "processing_institution": { + "type": "string", + }, + }, + }, + "study": { + "attributes": { + "principal_investigator.has_raw_value": { + "type": "string", + }, + }, + }, + } + + +from datetime import datetime +from typing import Annotated, List, Literal, Optional, Union + + +AnnotationValue = Union[float, int, datetime, str, dict, list] + + +class Table(Enum): + biosample = "biosample" + study = "study" + omics_processing = "omics_processing" + reads_qc = "reads_qc" + metagenome_assembly = "metagenome_assembly" + metagenome_annotation = "metagenome_annotation" + metaproteomic_analysis = "metaproteomic_analysis" + mags_analysis = "mags_analysis" + nom_analysis = "nom_analysis" + read_based_analysis = "read_based_analysis" + metabolomics_analysis = "metabolomics_analysis" + metatranscriptome = "metatranscriptome" + gene_function = "gene_function" + metap_gene_function = "metap_gene_function" + data_object = "data_object" + + env_broad_scale = "env_broad_scale" + env_local_scale = "env_local_scale" + env_medium = "env_medium" + + principal_investigator = "principal_investigator" + + +# Custom exceptions to provide better error responses in the API. +class InvalidAttributeException(Exception): + def __init__(self, table: str, attribute: str): + self.table = table + self.attribute = attribute + super(InvalidAttributeException, self).__init__( + f"Attribute {self.attribute} not found in table {self.table}" + ) + + +class InvalidFacetException(Exception): + pass + + +class Operation(Enum): + equal = "==" + greater = ">" + greater_equal = ">=" + less = "<" + less_equal = "<=" + not_equal = "!=" + + +NumericValue = Union[float, int, datetime] +RangeValue = Annotated[List[AnnotationValue], Field(min_items=2, max_items=2)] + + +class GoldTreeValue(BaseModel): + ecosystem: Optional[str] + ecosystem_category: Optional[str] + ecosystem_type: Optional[str] + ecosystem_subtype: Optional[str] + specific_ecosystem: Optional[str] + + +ConditionValue = Union[AnnotationValue, RangeValue, List[GoldTreeValue]] + + +class BaseConditionSchema(BaseModel): + field: str + value: ConditionValue + table: Table + + +# This condition type represents the original DSL for comparisons. It +# represents simple binary operators on scalar fields and is generally +# compatible with all attributes. +class SimpleConditionSchema(BaseConditionSchema): + op: Operation = Operation.equal + field: str + value: AnnotationValue + table: Table + + +# A range query that can't be achieved with simple conditions (because they are "or"-ed together). +class RangeConditionSchema(BaseConditionSchema): + op: Literal["between"] + field: str + value: RangeValue + table: Table + + +# A special condition type used on gold terms that supports hierarchical queries. +class GoldConditionSchema(BaseConditionSchema): + table: Table # can't do a Literal on an enum type + value: List[GoldTreeValue] + field: Literal["gold_tree"] + op: Literal["tree"] + + +# A special condition type on multiomics bitstrings +class MultiomicsConditionSchema(BaseConditionSchema): + table: Table + value: Union[int, List[str]] + field: Literal["multiomics"] + op: Literal["has"] + + +ConditionSchema = Union[ + RangeConditionSchema, + SimpleConditionSchema, + GoldConditionSchema, + MultiomicsConditionSchema, +] + + +class BaseQuerySchema(BaseModel): + conditions: List[ConditionSchema] = [] + + +class WorkflowActivityTypeEnum(Enum): + reads_qc = "nmdc:ReadQCAnalysisActivity" + metagenome_assembly = "nmdc:MetagenomeAssembly" + metagenome_annotation = "nmdc:MetagenomeAnnotation" # TODO name out of date, fix + metaproteomic_analysis = "nmdc:MetaProteomicAnalysis" + mags_analysis = "nmdc:MAGsAnalysisActivity" + read_based_analysis = "nmdc:ReadbasedAnalysis" # TODO name out of date, fix + nom_analysis = "nmdc:NomAnalysisActivity" + metabolomics_analysis = "nmdc:MetabolomicsAnalysisActivity" + raw_data = "nmdc:RawData" + metatranscriptome = "nmdc:metaT" + + +class DataObjectFilter(BaseModel): + workflow: Optional[WorkflowActivityTypeEnum] + file_type: Optional[str] + + +class BiosampleQuerySchema(BaseQuerySchema): + data_object_filter: List[DataObjectFilter] = [] + + +class DataObjectAggregation(BaseModel): + count: int + size: int + + +class DataObjectQuerySchema(BaseQuerySchema): + data_object_filter: List[DataObjectFilter] = [] + + +class BaseSearchResponse(BaseModel): + count: int + + +class SearchQuery(BaseModel): + conditions: List[ConditionSchema] = [] + + +class FacetQuery(SearchQuery): + attribute: str + + +class BiosampleSearchQuery(SearchQuery): + data_object_filter: List[DataObjectFilter] = [] + + +class KeggTermText(BaseModel): + term: str + text: str + + +class KeggTermTextListResponse(BaseModel): + terms: List[KeggTermText] + + +class EnvoTreeNode(BaseModel): + id: str + label: str + children: List["EnvoTreeNode"] + + +class EnvoTreeResponse(BaseModel): + trees: Dict[str, List[EnvoTreeNode]] + + +class Contributor(BaseModel): + name: str + orcid: str + roles: List[str] + + +class StudyForm(BaseModel): + studyName: str + piName: str + piEmail: str + piOrcid: str + linkOutWebpage: List[str] + studyDate: Optional[str] + description: str + notes: str + contributors: List[Contributor] + + +class MultiOmicsForm(BaseModel): + alternativeNames: List[str] + studyNumber: str + GOLDStudyId: str + JGIStudyId: str + NCBIBioProjectId: str + omicsProcessingTypes: List[str] + + +class NmcdAddress(BaseModel): + name: str + email: str + phone: str + line1: str + line2: str + city: str + state: str + postalCode: str + + +class AddressForm(BaseModel): + shipper: NmcdAddress + expectedShippingDate: Optional[datetime] + shippingConditions: str + sample: str + description: str + experimentalGoals: str + randomization: str + usdaRegulated: Optional[bool] + permitNumber: str + biosafetyLevel: str + irbOrHipaa: Optional[bool] + comments: str + + +class ContextForm(BaseModel): + datasetDoi: str + dataGenerated: Optional[bool] + facilityGenerated: Optional[bool] + facilities: List[str] + award: Optional[str] + otherAward: str + + +class MetadataSubmissionRecord(BaseModel): + packageName: str + contextForm: ContextForm + addressForm: AddressForm + templates: List[str] + studyForm: StudyForm + multiOmicsForm: MultiOmicsForm + sampleData: Dict[str, List[Any]] + + +class SubmissionMetadataSchemaCreate(BaseModel): + metadata_submission: MetadataSubmissionRecord + status: Optional[str] + + +class SubmissionMetadataSchema(SubmissionMetadataSchemaCreate): + # id: UUID + # author_orcid: str + created: datetime + status: str + author: User + + +class MetadataSubmissionResponse(BaseSearchResponse): + results: List[SubmissionMetadataSchema] + + +@router.post( + "/environment/sankey", + tags=["aggregation"], +) +async def get_environmental_sankey( + biosample_query: BiosampleQuerySchema = BiosampleQuerySchema(), + mdb: MongoDatabase = Depends(get_mongo_db), +): + """Retrieve biosample counts by ecosystem used as input for a sankey diagram.""" + mongo_filter = conditions_to_mongo_filter(biosample_query.conditions) + results = mdb[BIOSAMPLE_SEARCH_COLLECTION].aggregate( + [ + { + "$match": mongo_filter, + }, + { + "$group": { + "_id": { + "ecosystem": "$ecosystem", + "ecosystem_category": "$ecosystem_category", + "ecosystem_subtype": "$ecosystem_subtype", + "ecosystem_type": "$ecosystem_type", + "specific_ecosystem": "$specific_ecosystem", + }, + "count": { + "$count": {}, + }, + }, + }, + { + "$set": { + "_id.count": "$count", + }, + }, + { + "$replaceRoot": { + "newRoot": "$_id", + }, + }, + ] + ) + return strip_oid_recursive(results) + + +@router.post( + "/environment/geospatial", + tags=["aggregation"], +) +async def get_environmental_geospatial( + biosample_query: BiosampleQuerySchema = BiosampleQuerySchema(), + mdb: MongoDatabase = Depends(get_mongo_db), +): + """Return samples binned by lat/lon and ecosystem type.""" + mongo_filter = conditions_to_mongo_filter(biosample_query.conditions) + results = mdb[BIOSAMPLE_SEARCH_COLLECTION].aggregate( + [ + { + "$match": mongo_filter, + }, + { + "$group": { + "_id": { + "latitude": "$lat_lon.latitude", + "longitude": "$lat_lon.longitude", + "ecosystem": "$ecosystem", + "ecosystem_category": "$ecosystem_category", + }, + "count": { + "$count": {}, + }, + }, + }, + { + "$set": { + "_id.count": "$count", + }, + }, + { + "$replaceRoot": { + "newRoot": "$_id", + }, + }, + ] + ) + return strip_oid_recursive(list(results)) + + +def facet_value_to_key(value): + """Convert a value to a key for use in a facet counting response.""" + if isinstance(value, list): + return ";".join(value) + return value + + +def conditions_to_mongo_filter(conditions, base_type="biosample"): + """Convert query conditions to a MongoDB filter.""" + mongo_filter = dict() + for condition in conditions: + if condition.table.name == base_type: + field_name = condition.field + else: + field_name = f"{condition.table.name}.{condition.field}" + + if condition.op == Operation.equal: + if not mongo_filter.get(field_name): + mongo_filter[field_name] = {"$in": []} + mongo_filter[field_name]["$in"].append(condition.value) + elif condition.op == Operation.less: + mongo_filter[field_name] = {"$lt": condition.value} + elif condition.op == Operation.less_equal: + mongo_filter[field_name] = {"$lte": condition.value} + elif condition.op == Operation.greater: + mongo_filter[field_name] = {"$gt": condition.value} + elif condition.op == Operation.greater_equal: + mongo_filter[field_name] = {"$gte": condition.value} + elif condition.op == "between": + mongo_filter[field_name] = { + "$gte": condition.value[0], + "$lte": condition.value[1], + } + elif condition.op == "has": + mongo_filter[field_name] = {"$all": condition.value} + + return mongo_filter + + +class Pagination: + """ + This class is responsible for generating paged responses from sqlalchemy queries. + """ + + DEFAULT_OFFSET = 0 + DEFAULT_LIMIT = 25 + + def __init__( + self, + request: Request, + response: Response, + offset: int = Query(default=DEFAULT_OFFSET, ge=0), + limit: int = Query(default=DEFAULT_LIMIT, ge=1), + ): + self._request = request + self._response = response + self.offset = offset + self.limit = limit + + +@router.post( + "/biosample/search", + tags=["biosample"], + name="Search for biosamples", + description="Faceted search of biosample data.", +) +async def search_biosample( + biosample_query: BiosampleSearchQuery = BiosampleSearchQuery(), + mdb: MongoDatabase = Depends(get_mongo_db), + pagination: Pagination = Depends(), +): + """Search for biosamples.""" + mongo_filter = conditions_to_mongo_filter(biosample_query.conditions) + aggregation = [ + { + "$match": mongo_filter, + }, + { + "$unset": "gene_function", + }, + { + "$sort": {"multiomics_count": -1}, + }, + ] + + def data_object_is_selected(data_object): + for condition in biosample_query.data_object_filter: + if ( + data_object.get("data_object_type") == condition.file_type + and data_object.get("activity_type") == condition.workflow.value + ): + return True + return False + + file_type_map: Dict[str, Tuple[str, str]] = {} + for val in get_nmdc_file_type_enums(): + file_type_map[val["name"]] = val["description"] + + def add_data_object_selection_and_type(sample): + for obj in sample["data_object"]: + obj["data_object_type_description"] = file_type_map.get( + obj.get("data_object_type", None), None + ) + obj["selected"] = data_object_is_selected(obj) + return sample + + return { + "count": list( + mdb[BIOSAMPLE_SEARCH_COLLECTION].aggregate( + [*aggregation, {"$count": "count"}] + ) + )[0]["count"], + "results": [ + strip_oid_recursive(add_data_object_selection_and_type(doc)) + for doc in mdb[BIOSAMPLE_SEARCH_COLLECTION].aggregate( + [ + *aggregation, + {"$skip": pagination.offset}, + {"$limit": pagination.limit}, + ] + ) + ], + } + + +@router.post( + "/biosample/facet", + tags=["biosample"], + name="Get all values of an attribute", +) +async def facet_biosample( + facet_query: FacetQuery, + mdb: MongoDatabase = Depends(get_mongo_db), +): + """Get all values of an attribute.""" + aggregation = [ + { + "$match": conditions_to_mongo_filter(facet_query.conditions), + }, + { + "$sortByCount": f"${facet_query.attribute}", + }, + ] + + return strip_oid_recursive( + { + "facets": { + facet_value_to_key(facet["_id"]): facet["count"] + for facet in mdb[BIOSAMPLE_SEARCH_COLLECTION].aggregate(aggregation) + }, + } + ) + + +@router.post( + "/biosample/binned_facet", + tags=["biosample"], + name="Get all values of an attribute", +) +async def binned_facet_biosample( + facet_query: FacetQuery, + mdb: MongoDatabase = Depends(get_mongo_db), +): + """Get all values of an attribute.""" + aggregation = [ + { + "$match": conditions_to_mongo_filter(facet_query.conditions), + }, + { + "$group": { + "_id": { + "year": {"$year": "$collection_date.has_date_value"}, + "month": {"$month": "$collection_date.has_date_value"}, + }, + "count": {"$count": {}}, + }, + }, + ] + + def date_string(doc): + return f"{doc['_id']['year']}-{str(doc['_id']['month']).zfill(2)}-01" + + binned_data = list(mdb[BIOSAMPLE_SEARCH_COLLECTION].aggregate(aggregation)) + binned_data.sort(key=date_string) + binned_data = [d for d in binned_data if d["_id"]["year"] is not None] + + # Fill in missing months with zero counts + def next_month(doc): + if doc["month"] < 12: + return {"month": doc["month"] + 1, "year": doc["year"]} + return {"month": 1, "year": doc["year"] + 1} + + full_binned_data: List[Any] = [] + for doc in binned_data: + if len(full_binned_data) == 0: + full_binned_data.append(doc) + continue + while ( + full_binned_data[-1]["_id"]["year"] != doc["_id"]["year"] + or full_binned_data[-1]["_id"]["month"] != doc["_id"]["month"] + ): + full_binned_data.append( + {"_id": next_month(full_binned_data[-1]["_id"]), "count": 0} + ) + full_binned_data[-1] = doc + + # Add one more month with zero count so we have a bin end boundary for the last bin + full_binned_data.append( + {"_id": next_month(full_binned_data[-1]["_id"]), "count": 0} + ) + return strip_oid_recursive( + { + "bins": [date_string(d) for d in full_binned_data], + "facets": [d["count"] for d in full_binned_data][:-1], + } + ) + + +@router.get( + "/biosample/{biosample_id}", + tags=["biosample"], +) +async def get_biosample( + biosample_id: str, + mdb: MongoDatabase = Depends(get_mongo_db), +): + """Get a biosample by ID.""" + biosamples = list(mdb[BIOSAMPLE_SEARCH_COLLECTION].find({"id": biosample_id})) + if len(biosamples) == 0: + raise HTTPException(status_code=404, detail="Biosample not found") + + return strip_oid_recursive(biosamples[0]) + + +# @router.get( +# "/envo/tree", +# response_model=EnvoTreeResponse, +# tags=["envo"], +# ) +# async def get_envo_tree(): +# return EnvoTreeResponse(trees=nested_envo_trees()) + + +# @router.get( +# "/kegg/module/{module}", +# response_model=schemas.KeggTermListResponse, +# tags=["kegg"], +# ) +# async def get_kegg_terms_for_module(module: str, db: Session = Depends(get_db)): +# terms = crud.list_ko_terms_for_module(db, module) +# return schemas.KeggTermListResponse(terms=terms) + + +# @router.get( +# "/kegg/pathway/{pathway}", +# response_model=schemas.KeggTermListResponse, +# tags=["kegg"], +# ) +# async def get_kegg_terms_for_pathway(pathway: str, db: Session = Depends(get_db)): +# terms = crud.list_ko_terms_for_pathway(db, pathway) +# return schemas.KeggTermListResponse(terms=terms) + + +@router.get( + "/kegg/term/search", + response_model=KeggTermTextListResponse, + tags=["kegg"], +) +async def kegg_text_search( + query: str, + limit=20, + mdb: MongoDatabase = Depends(get_mongo_db), +): + """Search for KEGG terms by text.""" + return KeggTermTextListResponse( + terms=[ + KeggTermText( + term="K00001", + text="E1.1.1.1, adh; alcohol dehydrogenase [EC:1.1.1.1]", + ) + ] + ) + + +@router.post( + "/study/search", + tags=["study"], + name="Search for studies", + description="Faceted search of study data.", +) +async def search_study( + study_query: BiosampleSearchQuery = BiosampleSearchQuery(), + mdb: MongoDatabase = Depends(get_mongo_db), + pagination: Pagination = Depends(), +): + """Search for studies.""" + aggregation = [ + { + "$match": conditions_to_mongo_filter(study_query.conditions), + }, + { + "$unwind": {"path": "$study"}, + }, + { + "$group": { + "_id": "$study.id", + "study": {"$first": "$study"}, + }, + }, + { + "$replaceRoot": {"newRoot": "$study"}, + }, + ] + + return strip_oid_recursive( + { + "count": list( + mdb[BIOSAMPLE_SEARCH_COLLECTION].aggregate( + [*aggregation, {"$count": "count"}] + ) + )[0]["count"], + "results": [ + doc + for doc in mdb[BIOSAMPLE_SEARCH_COLLECTION].aggregate( + [ + *aggregation, + {"$skip": pagination.offset}, + {"$limit": pagination.limit}, + ] + ) + ], + } + ) + + +@router.post( + "/study/facet", + tags=["study"], + name="Get all values of an attribute", +) +async def facet_study( + study_query: FacetQuery, + mdb: MongoDatabase = Depends(get_mongo_db), +): + """Get counts of values of a study attribute.""" + aggregation = [ + { + "$match": conditions_to_mongo_filter(study_query.conditions), + }, + { + "$unwind": {"path": "$study"}, + }, + { + "$group": { + "_id": "$study.id", + "study": {"$first": "$study"}, + }, + }, + { + "$replaceRoot": {"newRoot": "$study"}, + }, + { + "$sortByCount": f"${study_query.attribute}", + }, + ] + + return strip_oid_recursive( + { + "facets": { + facet_value_to_key(facet["_id"]): facet["count"] + for facet in mdb[BIOSAMPLE_SEARCH_COLLECTION].aggregate(aggregation) + }, + } + ) + + +@router.get( + "/study/{study_id}", + tags=["study"], +) +async def get_study( + study_id: str, + mdb: MongoDatabase = Depends(get_mongo_db), +): + """Get study by ID.""" + studies = list(mdb.study_transformed.find({"id": study_id})) + if len(studies) == 0: + raise HTTPException(status_code=404, detail="Study not found") + + return strip_oid_recursive(studies[0]) + + +# @router.get("/study/{study_id}/image", tags=["study"]) +# async def get_study_image(study_id: str, db: Session = Depends(get_db)): +# image = crud.get_study_image(db, study_id) +# if image is None: +# raise HTTPException(status_code=404, detail="No image exists for this study") +# return StreamingResponse(BytesIO(image), media_type="image/jpeg") + + +@router.post( + "/omics_processing/facet", + tags=["omics_processing"], + name="Get all values of an attribute", +) +async def facet_omics_processing( + omics_processing_query: FacetQuery, + mdb: MongoDatabase = Depends(get_mongo_db), +): + """Get all values of an attribute.""" + aggregation = [ + { + "$match": conditions_to_mongo_filter( + omics_processing_query.conditions, + "omics_processing", + ), + }, + ] + + aggregation += [ + { + "$sortByCount": f"${omics_processing_query.attribute}", + }, + ] + + return strip_oid_recursive( + { + "facets": { + facet_value_to_key(facet["_id"]): facet["count"] + for facet in mdb[OMICS_PROCESSING_SEARCH_COLLECTION].aggregate( + aggregation + ) + }, + } + ) + + +# @router.get( +# "/data_object/{data_object_id}/download", +# tags=["data_object"], +# responses=login_required_responses, +# ) +# async def download_data_object( +# data_object_id: str, +# user_agent: Optional[str] = Header(None), +# x_forwarded_for: Optional[str] = Header(None), +# db: Session = Depends(get_db), +# user: models.User = Depends(login_required), +# ): +# ip = (x_forwarded_for or "").split(",")[0].strip() +# data_object = crud.get_data_object(db, data_object_id) +# if data_object is None: +# raise HTTPException(status_code=404, detail="DataObject not found") +# url = data_object.url +# if url is None: +# raise HTTPException(status_code=404, detail="DataObject has no url reference") + +# file_download = schemas.FileDownloadCreate( +# ip=ip, +# user_agent=user_agent, +# orcid=user.orcid, +# data_object_id=data_object_id, +# ) +# crud.create_file_download(db, file_download) +# return RedirectResponse(url=url) + + +@router.post( + "/data_object/workflow_summary", + tags=["data_object"], + name="Aggregate data objects by workflow", +) +def data_object_aggregation( + data_object_query: DataObjectQuerySchema = DataObjectQuerySchema(), + mdb: MongoDatabase = Depends(get_mongo_db), +): + """Aggregate data objects by workflow.""" + aggregation = [ + { + "$match": conditions_to_mongo_filter(data_object_query.conditions), + }, + { + "$unwind": {"path": "$data_object"}, + }, + { + "$group": { + "_id": "$data_object.id", + "data_object": {"$first": "$data_object"}, + }, + }, + { + "$replaceRoot": {"newRoot": "$data_object"}, + }, + { + "$set": { + "combined_type": { + "data_object_type": "$data_object_type", + "activity_type": "$activity_type", + }, + }, + }, + { + "$sortByCount": "$combined_type", + }, + ] + + result: Dict[str, Any] = dict() + for facet in mdb[BIOSAMPLE_SEARCH_COLLECTION].aggregate(aggregation): + if "data_object_type" not in facet["_id"]: + # We are not considering data_objects without a data_object_type + continue + if result.get(facet["_id"]["activity_type"]) is None: + result[facet["_id"]["activity_type"]] = {"count": 0, "file_types": dict()} + result[facet["_id"]["activity_type"]]["file_types"][ + facet["_id"]["data_object_type"] + ] = facet["count"] + result[facet["_id"]["activity_type"]]["count"] += facet["count"] + + return strip_oid_recursive(result) + + +# @router.get( +# "/principal_investigator/{principal_investigator_id}", +# tags=["principal_investigator"] +# ) +# async def get_pi_image(principal_investigator_id: UUID, db: Session = Depends(get_db)): +# image = crud.get_pi_image(db, principal_investigator_id) +# if image is None: +# raise HTTPException(status_code=404, detail="Principal investigator not found") + +# return StreamingResponse(BytesIO(image), media_type="image/jpeg") + + +# from fastapi import Header +# from fastapi.responses import JSONResponse, Response +# from uuid import UUID +# from sqlalchemy.orm import Session +# from nmdc_server.auth import login_required_responses, login_required, admin_required +# from nmdc_server import crud, jobs, query, models, schemas, schemas_submission +# from nmdc_server.bulk_download_schema import BulkDownload, BulkDownloadCreate +# from nmdc_server.database import get_db +# from nmdc_server.models import User, SubmissionMetadata + +# @router.post( +# "/jobs/ping", +# tags=["jobs"], +# responses=login_required_responses, +# ) +# async def ping_celery(user: models.User = Depends(admin_required)) -> bool: +# try: +# return jobs.ping.delay().wait(timeout=0.5) +# except TimeoutError: +# return False + + +# @router.post( +# "/jobs/ingest", +# tags=["jobs"], +# responses=login_required_responses, +# ) +# async def run_ingest( +# user: models.User = Depends(admin_required), +# params: schemas.IngestArgumentSchema = schemas.IngestArgumentSchema(), +# db: Session = Depends(get_db), +# ): +# lock = db.query(IngestLock).first() +# if lock: +# raise HTTPException( +# status_code=409, +# detail=f"An ingest started at {lock.started} is already in progress", +# ) +# jobs.ingest.delay( +# function_limit=params.function_limit, +# skip_annotation=params.skip_annotation +# ) +# return "" + + +# @router.post( +# "/bulk_download", +# tags=["download"], +# response_model=BulkDownload, +# responses=login_required_responses, +# status_code=201, +# ) +# async def create_bulk_download( +# user_agent: Optional[str] = Header(None), +# x_forwarded_for: Optional[str] = Header(None), +# query: query.BiosampleQuerySchema = query.BiosampleQuerySchema(), +# db: Session = Depends(get_db), +# user: models.User = Depends(login_required), +# ): +# ip = (x_forwarded_for or "").split(",")[0].strip() +# bulk_download = crud.create_bulk_download( +# db, +# BulkDownloadCreate( +# ip=ip, +# user_agent=user_agent, +# orcid=user.orcid, +# conditions=query.conditions, +# filter=query.data_object_filter, +# ), +# ) +# if bulk_download is None: +# return JSONResponse(status_code=400, content={"error": "no files matched the filter"}) +# return bulk_download + + +# @router.post( +# "/bulk_download/summary", +# tags=["download"], +# response_model=query.DataObjectAggregation, +# ) +# async def get_data_object_aggregation( +# query: query.DataObjectQuerySchema = query.DataObjectQuerySchema(), +# db: Session = Depends(get_db), +# ): +# return query.aggregate(db) + + +# @router.get( +# "/bulk_download/{bulk_download_id}", +# tags=["download"], +# responses=login_required_responses, +# ) +# async def download_zip_file( +# bulk_download_id: UUID, +# db: Session = Depends(get_db), +# user: models.User = Depends(login_required), +# ): +# table = crud.get_zip_download(db, bulk_download_id) +# return Response( +# content=table, +# headers={ +# "X-Archive-Files": "zip", +# "Content-Disposition": "attachment; filename=archive.zip", +# }, +# ) + + +@router.get( + "/metadata_submission", + tags=["metadata_submission"], + # responses=login_required_responses, + response_model=MetadataSubmissionResponse, +) +async def list_submissions( + mdb: MongoDatabase = Depends(get_mongo_db), + user: User = Depends(get_current_active_user), + pagination: Pagination = Depends(), +): + # query = db.query(SubmissionMetadata) + # try: + # await admin_required(user) + # except HTTPException: + # query = query.join(User).filter(User.orcid == user.orcid) + # return pagination.response(query) + return [user] + + +# @router.get( +# "/metadata_submission/{id}", +# tags=["metadata_submission"], +# responses=login_required_responses, +# response_model=schemas_submission.SubmissionMetadataSchema, +# ) +# async def get_submission( +# id: str, +# db: Session = Depends(get_db), +# user: models.User = Depends(login_required), +# ): +# submission = db.query(SubmissionMetadata).get(id) +# if submission is None: +# raise HTTPException(status_code=404, detail="Submission not found") +# if submission.author.orcid != user.orcid: +# await admin_required(user) +# return submission + + +# @router.patch( +# "/metadata_submission/{id}", +# tags=["metadata_submission"], +# responses=login_required_responses, +# response_model=schemas_submission.SubmissionMetadataSchema, +# ) +# async def update_submission( +# id: str, +# body: schemas_submission.SubmissionMetadataSchemaCreate, +# db: Session = Depends(get_db), +# user: models.User = Depends(login_required), +# ): +# submission = db.query(SubmissionMetadata).get(id) +# body_dict = body.dict() +# if submission is None: +# raise HTTPException(status_code=404, detail="Submission not found") +# if submission.author_orcid != user.orcid: +# await admin_required(user) +# submission.metadata_submission = body_dict["metadata_submission"] +# if body_dict["status"]: +# submission.status = body_dict["status"] +# db.commit() +# return submission + + +# @router.post( +# "/metadata_submission", +# tags=["metadata_submission"], +# responses=login_required_responses, +# response_model=schemas_submission.SubmissionMetadataSchema, +# status_code=201, +# ) +# async def submit_metadata( +# body: schemas_submission.SubmissionMetadataSchemaCreate, +# db: Session = Depends(get_db), +# user: models.User = Depends(login_required), +# ): +# submission = SubmissionMetadata(**body.dict(), author_orcid=user.orcid) +# submission.author_id = user.id +# db.add(submission) +# db.commit() +# return submission + + +# @router.get( +# "/users", responses=login_required_responses, response_model=query.UserResponse, tags=["user"] +# ) +# async def get_users( +# db: Session = Depends(get_db), +# user: models.User = Depends(admin_required), +# pagination: Pagination = Depends(), +# ): +# users = db.query(User) +# return pagination.response(users) + + +# @router.post( +# "/users/{id}", responses=login_required_responses, response_model=schemas.User, tags=["user"] +# ) +# async def update_user( +# id: UUID, +# body: schemas.User, +# db: Session = Depends(get_db), +# current_user: models.User = Depends(admin_required), +# ): +# if body.id != id: +# raise HTTPException(status_code=400, detail="Invalid id") +# return crud.update_user(db, body) diff --git a/nmdc_runtime/api/endpoints/portal_denormalize.py b/nmdc_runtime/api/endpoints/portal_denormalize.py new file mode 100644 index 00000000..822aab86 --- /dev/null +++ b/nmdc_runtime/api/endpoints/portal_denormalize.py @@ -0,0 +1,410 @@ +from pymongo import MongoClient +import time +from typing import List, Dict + +from nmdc_runtime.api.db.mongo import get_mongo_db + +# from nmdc_server.ingest import envo +# from nmdc_server.config import Settings + +omics_types = [ + "Metagenome", + "Organic Matter Characterization", + "Metatranscriptome", + "Proteomics", + "Metabolomics", +] + +# A couple transforms needed for optimal queries +biosample_transformed_aggregation: List[Dict] = [ + # To filter by dates we need actual dates in the database + { + "$set": { + "collection_date.has_date_value": { + "$dateFromString": { + "dateString": "$collection_date.has_raw_value", + }, + }, + }, + }, + # Lookup related omics_processing temporarily to derive some summary properties + { + "$lookup": { + "from": "omics_processing_set", + "localField": "id", + "foreignField": "has_input", + "as": "omics_processing", + }, + }, + # Create an array of all the omics_processing types associated with this sample + { + "$set": { + "multiomics": { + "$sortArray": { + "input": { + # This set difference removes duplicate omics types and removes lipidomics + "$setDifference": [ + "$omics_processing.omics_type.has_raw_value", + ["Lipidomics"], + ], + }, + "sortBy": 1, + }, + }, + }, + }, + # Add a count so we can sort by the number of types of omics_processing each sample has + {"$set": {"multiomics_count": {"$size": "$multiomics"}}}, + # We don't want to actually store the related omics_processing + { + "$unset": "omics_processing", + }, + # Save the result + { + "$out": "biosample_transformed", + }, +] + +study_transformed_aggregation: List[Dict] = [ + { + "$lookup": { + "from": "biosample_transformed", + "localField": "id", + "foreignField": "part_of", + "as": "biosample", + }, + }, + { + "$lookup": { + "from": "omics_processing_set", + "localField": "biosample.id", + "foreignField": "has_input", + "as": "omics_processing", + }, + }, + # Count the number of each omics_type and get it in the form [{"type": "Metagenome", "count": 100}, ...]. + # This one is a kind of beast in mongo aggregation programming. + # + # The pipeline in procedural code is roughly: + # + # omics_type_count_map = reduce_to_count_of_each_omics_type(omics_processing_array) (e.g. {"Metagenome": 100, "Metabolomics": 50, ...}) + # key_value_array = object_to_key_value_array(omics_type_count_map) (e.g. [{"k": "Metagenome", "v": 100}, {"k": "Metabolomics", "v": 50}, ...]) + # type_count_array = rename_key_value_to_type_count(key_value_array) (e.g. [{"type": "Metagenome", "count": 100}, {"type": "Metabolomics", "count": 50}, ...]) + # omics_processing_counts = sort_by_omics_type_name(type_count_array) (e.g. [{"type": "Metabolomics", "count": 50}, {"type": "Metagenome", "count": 100}, ...]) + { + "$set": { + "omics_processing_counts": { + "$sortArray": { + "input": { + "$map": { + "input": { + "$objectToArray": { + "$reduce": { + "input": "$omics_processing", + "initialValue": { + omics_type: 0 for omics_type in omics_types + }, + "in": { + omics_type: { + "$cond": { + "if": { + "$eq": [ + "$$this.omics_type.has_raw_value", + omics_type, + ] + }, + "then": { + "$add": [ + f"$$value.{omics_type}", + 1, + ] + }, + "else": f"$$value.{omics_type}", + }, + } + for omics_type in omics_types + }, + }, + }, + }, + "in": { + "type": "$$this.k", + "count": "$$this.v", + }, + }, + }, + "sortBy": {"type": 1}, + }, + }, + }, + }, + { + "$unset": "omics_processing", + }, + # Count the number of biosamples + {"$set": {"sample_count": {"$size": "$biosample"}}}, + { + "$unset": "biosample", + }, + { + "$out": "study_transformed", + }, +] + + +def denormalize_analysis_aggregation(base_type): + aggregation = [] + + activity_types = { + "mags_activity": "nmdc:MAGsAnalysisActivity", + "metabolomics_analysis_activity": "nmdc:MetabolomicsAnalysisActivity", + "metagenome_annotation_activity": "nmdc:MetagenomeAnnotation", + "metagenome_assembly": "nmdc:MetagenomeAssembly", + "metaproteomics_analysis_activity": "nmdc:MetaProteomicAnalysis", + "metatranscriptome_activity": "nmdc:metaT", + "nom_analysis_activity": "nmdc:NomAnalysisActivity", + } + + for activity_type in activity_types: + # Pull in activities and data_objects associated with each omics_processing + aggregation.extend( + [ + { + "$lookup": { + "from": f"{activity_type}_set", + "localField": "id" + if base_type == "omics_processing" + else "omics_processing.id", + "foreignField": "was_informed_by", + "as": activity_type, + }, + }, + # Move this to after all analyses are concatenated - can be one step to get all data_object records + { + "$lookup": { + "from": "data_object_set", + "localField": f"{activity_type}.has_output", + "foreignField": "id", + "as": f"{activity_type}_data_object", + "pipeline": [ + {"$set": {"activity_type": activity_types[activity_type]}}, + ], + }, + }, + ] + ) + + aggregation.extend( + [ + # Lookup metagenome annotations + { + "$lookup": { + "from": "functional_annotation_agg", + "localField": "metagenome_annotation_activity.id", + "foreignField": "metagenome_annotation_id", + "as": "metagenome_annotation", + "pipeline": [ + { + "$set": { + "id": "$gene_function_id", + "activity_id": "$metagenome_annotation_id", + }, + }, + { + "$unset": [ + "_id", + "metagenome_annotation_id", + "gene_function_id", + ] + }, + ], + }, + }, + # Lookup metaproteomics annotations + { + "$lookup": { + "from": "metap_gene_function_aggregation", + "localField": "metaproteomics_analysis_activity.id", + "foreignField": "metaproteomic_analysis_id", + "as": "metaproteomics_annotation", + "pipeline": [ + { + "$set": { + "id": "$gene_function_id", + "activity_id": "$metaproteomic_analysis_id", + }, + }, + { + "$unset": [ + "_id", + "metaproteomic_analysis_id", + "gene_function_id", + ] + }, + ], + }, + }, + # Combine annotations into a single annotation array + { + "$set": { + "gene_function": { + "$concatArrays": [ + "$metagenome_annotation", + "$metaproteomics_annotation", + ] + } + }, + }, + { + "$unset": ["metagenome_annotation", "metaproteomics_annotation"], + }, + # Combine all activities into a single activity array + { + "$set": { + "activity": { + "$concatArrays": [ + f"${activity_type}" for activity_type in activity_types + ] + } + } + }, + # Remove the monstrous has_peptide_quantifications array to speed search + { + "$set": { + "activity": { + "$map": { + "input": "$activity", + "as": "d", + "in": { + "$setField": { + "field": "has_peptide_quantifications", + "value": "$$REMOVE", + "input": "$$d", + } + }, + } + }, + } + }, + # We are done with the separate activity types since they are all in the activity array now + { + "$unset": list(activity_types.keys()), + }, + ] + ) + + aggregation.extend( + [ + # Combine all data objects into a single data_object array + { + "$set": { + "data_object": { + "$concatArrays": [ + f"${activity_type}_data_object" + for activity_type in activity_types + ] + } + } + }, + # We no longer need the individual data_object fields + { + "$unset": [ + f"{activity_type}_data_object" for activity_type in activity_types + ] + }, + ] + ) + + return aggregation + + +biosample_denormalized_aggregation: List[Dict] = [ + { + "$lookup": { + "from": "study_transformed", + "localField": "part_of", + "foreignField": "id", + "as": "study", + }, + }, + { + "$lookup": { + "from": "omics_processing_set", + "localField": "id", + "foreignField": "has_input", + "as": "omics_processing", + }, + }, +] + +biosample_denormalized_aggregation += denormalize_analysis_aggregation("biosample") + +biosample_denormalized_aggregation += [ + { + "$out": "biosample_denormalized", + }, +] + +omics_processing_denormalized_aggregation: List[Dict] = [ + { + "$lookup": { + "from": "biosample_transformed", + "localField": "has_input", + "foreignField": "id", + "as": "biosample", + }, + }, + { + "$lookup": { + "from": "study_transformed", + "localField": "biosample.part_of", + "foreignField": "id", + "as": "study", + }, + }, +] + +omics_processing_denormalized_aggregation += denormalize_analysis_aggregation( + "omics_processing" +) + +omics_processing_denormalized_aggregation += [ + { + "$out": "omics_processing_denormalized", + }, +] + + +if __name__ == "__main__": + start = time.time() + + # settings = Settings() + # client = MongoClient( + # host=settings.mongo_host, + # username=settings.mongo_user, + # password=settings.mongo_password, + # port=settings.mongo_port, + # directConnection=True, + # ) + mdb = get_mongo_db() + + # envo.mongo_load(client) + + print("Generating study_transformed...") + q = mdb.study_set.aggregate(study_transformed_aggregation) + print("...done") + + print("Generating biosample_transformed...") + q = mdb.biosample_set.aggregate(biosample_transformed_aggregation) + print("...done") + + print("Generating biosample_denormalized...") + q = mdb.biosample_transformed.aggregate(biosample_denormalized_aggregation) + print("...done") + + print("Generating omics_processing_denormalized...") + q = mdb.omics_processing_set.aggregate(omics_processing_denormalized_aggregation) + print("...done") + + end = time.time() + print(f"Completed in {end - start}s") diff --git a/nmdc_runtime/api/endpoints/queries.py b/nmdc_runtime/api/endpoints/queries.py index 4e1c49c9..11417698 100644 --- a/nmdc_runtime/api/endpoints/queries.py +++ b/nmdc_runtime/api/endpoints/queries.py @@ -75,9 +75,9 @@ def run_query( id=qid, saved_at=saved_at, ) - mdb.queries.insert_one(query.dict(exclude_unset=True)) + mdb.queries.insert_one(query.model_dump(mode="json", exclude_unset=True)) cmd_response = _run_query(query, mdb) - return unmongo(cmd_response.dict(exclude_unset=True)) + return unmongo(cmd_response.model_dump(mode="json", exclude_unset=True)) @router.get("/queries/{query_id}", response_model=Query) @@ -107,7 +107,7 @@ def rerun_query( check_can_delete(user) cmd_response = _run_query(query, mdb) - return unmongo(cmd_response.dict(exclude_unset=True)) + return unmongo(cmd_response.model_dump(mode="json", exclude_unset=True)) def _run_query(query, mdb) -> CommandResponse: @@ -131,12 +131,12 @@ def _run_query(query, mdb) -> CommandResponse: detail="Failed to back up to-be-deleted documents. operation aborted.", ) - q_response = mdb.command(query.cmd.dict(exclude_unset=True)) + q_response = mdb.command(query.cmd.model_dump(mode="json", exclude_unset=True)) cmd_response: CommandResponse = command_response_for(q_type)(**q_response) query_run = ( QueryRun(qid=query.id, ran_at=ran_at, result=cmd_response) if cmd_response.ok else QueryRun(qid=query.id, ran_at=ran_at, error=cmd_response) ) - mdb.query_runs.insert_one(query_run.dict(exclude_unset=True)) + mdb.query_runs.insert_one(query_run.model_dump(mode="json", exclude_unset=True)) return cmd_response diff --git a/nmdc_runtime/api/endpoints/runs.py b/nmdc_runtime/api/endpoints/runs.py index c49b7800..8bd9f22d 100644 --- a/nmdc_runtime/api/endpoints/runs.py +++ b/nmdc_runtime/api/endpoints/runs.py @@ -94,5 +94,9 @@ def post_run_event( status_code=status.HTTP_400_BAD_REQUEST, detail=f"Supplied run_event.run.id does not match run_id given in request URL.", ) - mdb.run_events.insert_one(run_event.dict()) + mdb.run_events.insert_one( + run_event.model_dump( + mode="json", + ) + ) return _get_run_summary(run_event.run.id, mdb) diff --git a/nmdc_runtime/api/endpoints/search.py b/nmdc_runtime/api/endpoints/search.py index 5fe80d2c..4813f7d2 100644 --- a/nmdc_runtime/api/endpoints/search.py +++ b/nmdc_runtime/api/endpoints/search.py @@ -25,7 +25,9 @@ def data_objects( req: DataObjectListRequest = Depends(), mdb: MongoDatabase = Depends(get_mongo_db), ): - filter_ = list_request_filter_to_mongo_filter(req.dict(exclude_unset=True)) + filter_ = list_request_filter_to_mongo_filter( + req.model_dump(mode="json", exclude_unset=True) + ) max_page_size = filter_.pop("max_page_size", None) page_token = filter_.pop("page_token", None) req = ListRequest( diff --git a/nmdc_runtime/api/endpoints/sites.py b/nmdc_runtime/api/endpoints/sites.py index f63fd993..76adfdc1 100644 --- a/nmdc_runtime/api/endpoints/sites.py +++ b/nmdc_runtime/api/endpoints/sites.py @@ -56,7 +56,11 @@ def create_site( status_code=status.HTTP_409_CONFLICT, detail=f"site with supplied id {site.id} already exists", ) - mdb.sites.insert_one(site.dict()) + mdb.sites.insert_one( + site.model_dump( + mode="json", + ) + ) refresh_minter_requesters_from_sites() rv = mdb.users.update_one( {"username": user.username}, @@ -165,7 +169,11 @@ def put_object_in_site( }, } ) - mdb.operations.insert_one(op.dict()) + mdb.operations.insert_one( + op.model_dump( + mode="json", + ) + ) return op diff --git a/nmdc_runtime/api/endpoints/users.py b/nmdc_runtime/api/endpoints/users.py index 601a5be8..4ba7a1b3 100644 --- a/nmdc_runtime/api/endpoints/users.py +++ b/nmdc_runtime/api/endpoints/users.py @@ -1,7 +1,7 @@ from datetime import timedelta import pymongo.database -from fastapi import Depends, APIRouter, HTTPException, status +from fastapi import Depends, APIRouter, HTTPException, Response, status from nmdc_runtime.api.core.auth import ( OAuth2PasswordOrClientCredentialsRequestForm, @@ -24,6 +24,7 @@ @router.post("/token", response_model=Token) async def login_for_access_token( + response: Response, form_data: OAuth2PasswordOrClientCredentialsRequestForm = Depends(), mdb: pymongo.database.Database = Depends(get_mongo_db), ): @@ -35,7 +36,11 @@ async def login_for_access_token( detail="Incorrect username or password", headers={"WWW-Authenticate": "Bearer"}, ) - access_token_expires = timedelta(**ACCESS_TOKEN_EXPIRES.dict()) + access_token_expires = timedelta( + **ACCESS_TOKEN_EXPIRES.model_dump( + mode="json", + ) + ) access_token = create_access_token( data={"sub": f"user:{user.username}"}, expires_delta=access_token_expires ) @@ -50,15 +55,31 @@ async def login_for_access_token( headers={"WWW-Authenticate": "Bearer"}, ) # TODO make below an absolute time - access_token_expires = timedelta(**ACCESS_TOKEN_EXPIRES.dict()) + access_token_expires = timedelta( + **ACCESS_TOKEN_EXPIRES.model_dump( + mode="json", + ) + ) access_token = create_access_token( data={"sub": f"client:{form_data.client_id}"}, expires_delta=access_token_expires, ) + + response.set_cookie( + "session", + value=access_token, + domain="localhost", + httponly=True, + max_age=(60 * 99), + expires=(60 * 99), + ) + return { "access_token": access_token, "token_type": "bearer", - "expires": ACCESS_TOKEN_EXPIRES.dict(), + "expires": ACCESS_TOKEN_EXPIRES.model_dump( + mode="json", + ), } @@ -84,8 +105,10 @@ def create_user( check_can_create_user(requester) mdb.users.insert_one( UserInDB( - **user_in.dict(), + **user_in.model_dump( + mode="json", + ), hashed_password=get_password_hash(user_in.password), - ).dict(exclude_unset=True) + ).model_dump(mode="json", exclude_unset=True) ) return mdb.users.find_one({"username": user_in.username}) diff --git a/nmdc_runtime/api/endpoints/util.py b/nmdc_runtime/api/endpoints/util.py index d1c233b3..9ab2daa6 100644 --- a/nmdc_runtime/api/endpoints/util.py +++ b/nmdc_runtime/api/endpoints/util.py @@ -2,12 +2,14 @@ import os import re import tempfile +from datetime import datetime from functools import lru_cache from json import JSONDecodeError from pathlib import Path from time import time_ns from typing import List, Optional, Set, Tuple from urllib.parse import parse_qs, urlparse +from zoneinfo import ZoneInfo from bson import json_util from dagster import DagsterRunStatus @@ -198,6 +200,15 @@ def strip_oid(doc): return dissoc(doc, "_id") +def strip_oid_recursive(doc): + if isinstance(doc, dict): + return {k: strip_oid_recursive(v) for k, v in doc.items() if k != "_id"} + elif isinstance(doc, list): + return [strip_oid_recursive(v) for v in doc] + else: + return doc + + def timeit(cursor): """Collect from cursor and return time taken in milliseconds.""" tic = time_ns() @@ -433,7 +444,11 @@ def persist_content_and_get_drs_object( **drs_metadata_for( filepath, base={ - "description": description + f" (created by/for {username})", + "description": ( + description + + f" (created by/for {username}" + + f" at {datetime.now(tz=ZoneInfo('America/Los_Angeles')).isoformat(timespec='minutes')})" + ), "access_methods": [{"access_id": drs_id}], }, ) @@ -448,9 +463,11 @@ def _create_object( mdb: MongoDatabase, object_in: DrsObjectIn, mgr_site, drs_id, self_uri ): drs_obj = DrsObject( - **object_in.dict(exclude_unset=True), id=drs_id, self_uri=self_uri + **object_in.model_dump(exclude_unset=True, mode="json"), + id=drs_id, + self_uri=self_uri, ) - doc = drs_obj.dict(exclude_unset=True) + doc = drs_obj.model_dump(exclude_unset=True, mode="json") doc["_mgr_site"] = mgr_site # manager site try: mdb.objects.insert_one(doc) @@ -511,16 +528,22 @@ def _claim_job(job_id: str, mdb: MongoDatabase, site: Site): "workflow": job.workflow, "config": job.config, } - ).dict(exclude_unset=True), + ).model_dump(mode="json", exclude_unset=True), "site_id": site.id, "model": dotted_path_for(JobOperationMetadata), }, } ) - mdb.operations.insert_one(op.dict()) - mdb.jobs.replace_one({"id": job.id}, job.dict(exclude_unset=True)) + mdb.operations.insert_one( + op.model_dump( + mode="json", + ) + ) + mdb.jobs.replace_one( + {"id": job.id}, job.model_dump(mode="json", exclude_unset=True) + ) - return op.dict(exclude_unset=True) + return op.model_dump(mode="json", exclude_unset=True) @lru_cache diff --git a/nmdc_runtime/api/main.py b/nmdc_runtime/api/main.py index 5f4d799a..476d57e0 100644 --- a/nmdc_runtime/api/main.py +++ b/nmdc_runtime/api/main.py @@ -9,6 +9,7 @@ from starlette import status from starlette.responses import RedirectResponse + from nmdc_runtime.api.analytics import Analytics from nmdc_runtime.util import all_docs_have_unique_id, ensure_unique_id_indexes from nmdc_runtime.api.core.auth import get_password_hash @@ -24,6 +25,7 @@ object_types, objects, operations, + portal, queries, runs, sites, @@ -46,6 +48,7 @@ api_router.include_router(jobs.router, tags=["jobs"]) api_router.include_router(objects.router, tags=["objects"]) api_router.include_router(capabilities.router, tags=["capabilities"]) +api_router.include_router(portal.router, prefix="/api", tags=["portal"]) api_router.include_router(triggers.router, tags=["triggers"]) api_router.include_router(workflows.router, tags=["workflows"]) api_router.include_router(object_types.router, tags=["object types"]) @@ -232,7 +235,9 @@ def ensure_initial_resources_on_boot(): collection_boot = import_module(f"nmdc_runtime.api.boot.{collection_name}") for model in collection_boot.construct(): - doc = model.dict() + doc = model.model_dump( + mode="json", + ) mdb[collection_name].replace_one({"id": doc["id"]}, doc, upsert=True) username = os.getenv("API_ADMIN_USER") @@ -244,7 +249,7 @@ def ensure_initial_resources_on_boot(): username=username, hashed_password=get_password_hash(os.getenv("API_ADMIN_PASS")), site_admin=[os.getenv("API_SITE_ID")], - ).dict(exclude_unset=True), + ).model_dump(mode="json", exclude_unset=True), upsert=True, ) mdb.users.create_index("username") @@ -265,7 +270,9 @@ def ensure_initial_resources_on_boot(): ), ) ], - ).dict(), + ).model_dump( + mode="json", + ), upsert=True, ) diff --git a/nmdc_runtime/api/models/capability.py b/nmdc_runtime/api/models/capability.py index 4ac2cf15..6de4a2ff 100644 --- a/nmdc_runtime/api/models/capability.py +++ b/nmdc_runtime/api/models/capability.py @@ -5,8 +5,8 @@ class CapabilityBase(BaseModel): - name: Optional[str] - description: Optional[str] + name: Optional[str] = None + description: Optional[str] = None class Capability(CapabilityBase): diff --git a/nmdc_runtime/api/models/id.py b/nmdc_runtime/api/models/id.py index f989f693..687109a2 100644 --- a/nmdc_runtime/api/models/id.py +++ b/nmdc_runtime/api/models/id.py @@ -2,7 +2,8 @@ from enum import Enum from typing import Union, Any, Optional, Literal -from pydantic import BaseModel, constr, PositiveInt, root_validator +from pydantic import model_validator, StringConstraints, BaseModel, PositiveInt +from typing_extensions import Annotated # NO i, l, o or u. base32_letters = "abcdefghjkmnpqrstvwxyz" @@ -22,11 +23,11 @@ _base_object_name = f"{_naa}:{_shoulder}{_blade}" pattern_base_object_name = re.compile(_base_object_name) -Naa = constr(regex=_naa) -Shoulder = constr(regex=rf"^{_shoulder}$", min_length=2) -Blade = constr(regex=_blade, min_length=4) -AssignedBaseName = constr(regex=_assigned_base_name) -BaseObjectName = constr(regex=_base_object_name) +Naa = Annotated[str, StringConstraints(pattern=_naa)] +Shoulder = Annotated[str, StringConstraints(pattern=rf"^{_shoulder}$", min_length=2)] +Blade = Annotated[str, StringConstraints(pattern=_blade, min_length=4)] +AssignedBaseName = Annotated[str, StringConstraints(pattern=_assigned_base_name)] +BaseObjectName = Annotated[str, StringConstraints(pattern=_base_object_name)] NameAssigningAuthority = Literal[tuple(NAA_VALUES)] @@ -71,10 +72,10 @@ class IdBindingOp(str, Enum): class IdBindingRequest(BaseModel): i: BaseObjectName o: IdBindingOp = IdBindingOp.set - a: Optional[str] - v: Any + a: Optional[str] = None + v: Any = None - @root_validator() + @model_validator(mode="before") def set_or_add_needs_value(cls, values): op = values.get("o") if op in (IdBindingOp.set, IdBindingOp.addToSet): @@ -82,7 +83,7 @@ def set_or_add_needs_value(cls, values): raise ValueError("{'set','add'} operations needs value 'v'.") return values - @root_validator() + @model_validator(mode="before") def set_or_add_or_rm_needs_attribute(cls, values): op = values.get("o") if op in (IdBindingOp.set, IdBindingOp.addToSet, IdBindingOp.rm): diff --git a/nmdc_runtime/api/models/job.py b/nmdc_runtime/api/models/job.py index a6ab7da4..e39c2877 100644 --- a/nmdc_runtime/api/models/job.py +++ b/nmdc_runtime/api/models/job.py @@ -9,8 +9,8 @@ class JobBase(BaseModel): workflow: Workflow - name: Optional[str] - description: Optional[str] + name: Optional[str] = None + description: Optional[str] = None class JobClaim(BaseModel): @@ -20,7 +20,7 @@ class JobClaim(BaseModel): class Job(JobBase): id: str - created_at: Optional[datetime.datetime] + created_at: Optional[datetime.datetime] = None config: Dict[str, Any] claims: List[JobClaim] = [] diff --git a/nmdc_runtime/api/models/metadata.py b/nmdc_runtime/api/models/metadata.py index 7a5aabaa..5e70cba5 100644 --- a/nmdc_runtime/api/models/metadata.py +++ b/nmdc_runtime/api/models/metadata.py @@ -1,4 +1,4 @@ -from pydantic import BaseModel, Extra +from pydantic import ConfigDict, BaseModel class ChangesheetIn(BaseModel): @@ -8,5 +8,4 @@ class ChangesheetIn(BaseModel): class Doc(BaseModel): - class Config: - extra = Extra.allow + model_config = ConfigDict(extra="allow") diff --git a/nmdc_runtime/api/models/object.py b/nmdc_runtime/api/models/object.py index 6deb1559..26af100c 100644 --- a/nmdc_runtime/api/models/object.py +++ b/nmdc_runtime/api/models/object.py @@ -5,14 +5,15 @@ from typing import Optional, List, Dict from pydantic import ( + field_validator, + model_validator, + Field, + StringConstraints, BaseModel, AnyUrl, - constr, - conint, HttpUrl, - root_validator, - validator, ) +from typing_extensions import Annotated class AccessMethodType(str, Enum): @@ -27,17 +28,17 @@ class AccessMethodType(str, Enum): class AccessURL(BaseModel): - headers: Optional[Dict[str, str]] + headers: Optional[Dict[str, str]] = None url: AnyUrl class AccessMethod(BaseModel): - access_id: Optional[constr(min_length=1)] - access_url: Optional[AccessURL] - region: Optional[str] + access_id: Optional[Annotated[str, StringConstraints(min_length=1)]] = None + access_url: Optional[AccessURL] = None + region: Optional[str] = None type: AccessMethodType = AccessMethodType.https - @root_validator + @model_validator(mode="before") def at_least_one_of_access_id_and_url(cls, values): access_id, access_url = values.get("access_id"), values.get("access_url") if access_id is None and access_url is None: @@ -47,27 +48,30 @@ def at_least_one_of_access_id_and_url(cls, values): return values -ChecksumType = constr( - regex=rf"(?P({'|'.join(sorted(hashlib.algorithms_guaranteed))}))" -) +ChecksumType = Annotated[ + str, + StringConstraints( + pattern=rf"(?P({'|'.join(sorted(hashlib.algorithms_guaranteed))}))" + ), +] class Checksum(BaseModel): - checksum: constr(min_length=1) + checksum: Annotated[str, StringConstraints(min_length=1)] type: ChecksumType -DrsId = constr(regex=r"^[A-Za-z0-9._~\-]+$") -PortableFilename = constr(regex=r"^[A-Za-z0-9._\-]+$") +DrsId = Annotated[str, StringConstraints(pattern=r"^[A-Za-z0-9._~\-]+$")] +PortableFilename = Annotated[str, StringConstraints(pattern=r"^[A-Za-z0-9._\-]+$")] class ContentsObject(BaseModel): - contents: Optional[List["ContentsObject"]] - drs_uri: Optional[List[AnyUrl]] - id: Optional[DrsId] + contents: Optional[List["ContentsObject"]] = None + drs_uri: Optional[List[AnyUrl]] = None + id: Optional[DrsId] = None name: PortableFilename - @root_validator() + @model_validator(mode="before") def no_contents_means_single_blob(cls, values): contents, id_ = values.get("contents"), values.get("id") if contents is None and id_ is None: @@ -77,32 +81,32 @@ def no_contents_means_single_blob(cls, values): ContentsObject.update_forward_refs() -Mimetype = constr(regex=r"^\w+/[-+.\w]+$") -SizeInBytes = conint(strict=True, ge=0) +Mimetype = Annotated[str, StringConstraints(pattern=r"^\w+/[-+.\w]+$")] +SizeInBytes = Annotated[int, Field(strict=True, ge=0)] class Error(BaseModel): - msg: Optional[str] + msg: Optional[str] = None status_code: http.HTTPStatus class DrsObjectBase(BaseModel): - aliases: Optional[List[str]] - description: Optional[str] - mime_type: Optional[Mimetype] - name: Optional[PortableFilename] + aliases: Optional[List[str]] = None + description: Optional[str] = None + mime_type: Optional[Mimetype] = None + name: Optional[PortableFilename] = None class DrsObjectIn(DrsObjectBase): - access_methods: Optional[List[AccessMethod]] + access_methods: Optional[List[AccessMethod]] = None checksums: List[Checksum] - contents: Optional[List[ContentsObject]] + contents: Optional[List[ContentsObject]] = None created_time: datetime.datetime size: SizeInBytes - updated_time: Optional[datetime.datetime] - version: Optional[str] + updated_time: Optional[datetime.datetime] = None + version: Optional[str] = None - @root_validator() + @model_validator(mode="before") def no_contents_means_single_blob(cls, values): contents, access_methods = values.get("contents"), values.get("access_methods") if contents is None and access_methods is None: @@ -111,7 +115,8 @@ def no_contents_means_single_blob(cls, values): ) return values - @validator("checksums") + @field_validator("checksums") + @classmethod def at_least_one_checksum(cls, v): if not len(v) >= 1: raise ValueError("At least one checksum requried") @@ -123,7 +128,7 @@ class DrsObject(DrsObjectIn): self_uri: AnyUrl -Seconds = conint(strict=True, gt=0) +Seconds = Annotated[int, Field(strict=True, gt=0)] class ObjectPresignedUrl(BaseModel): @@ -137,8 +142,8 @@ class DrsObjectOutBase(DrsObjectBase): id: DrsId self_uri: AnyUrl size: SizeInBytes - updated_time: Optional[datetime.datetime] - version: Optional[str] + updated_time: Optional[datetime.datetime] = None + version: Optional[str] = None class DrsObjectBlobOut(DrsObjectOutBase): @@ -146,5 +151,5 @@ class DrsObjectBlobOut(DrsObjectOutBase): class DrsObjectBundleOut(DrsObjectOutBase): - access_methods: Optional[List[AccessMethod]] + access_methods: Optional[List[AccessMethod]] = None contents: List[ContentsObject] diff --git a/nmdc_runtime/api/models/object_type.py b/nmdc_runtime/api/models/object_type.py index a5e21e69..fca6262a 100644 --- a/nmdc_runtime/api/models/object_type.py +++ b/nmdc_runtime/api/models/object_type.py @@ -7,8 +7,8 @@ class ObjectTypeBase(BaseModel): - name: Optional[str] - description: Optional[str] + name: Optional[str] = None + description: Optional[str] = None class ObjectType(ObjectTypeBase): @@ -17,4 +17,4 @@ class ObjectType(ObjectTypeBase): class DrsObjectWithTypes(DrsObject): - types: Optional[List[str]] + types: Optional[List[str]] = None diff --git a/nmdc_runtime/api/models/operation.py b/nmdc_runtime/api/models/operation.py index 1bf12ece..e1819f24 100644 --- a/nmdc_runtime/api/models/operation.py +++ b/nmdc_runtime/api/models/operation.py @@ -1,44 +1,44 @@ import datetime from typing import Generic, TypeVar, Optional, List, Any, Union -from pydantic import BaseModel, HttpUrl, constr -from pydantic.generics import GenericModel +from pydantic import StringConstraints, BaseModel, HttpUrl from nmdc_runtime.api.models.util import ResultT +from typing_extensions import Annotated MetadataT = TypeVar("MetadataT") -PythonImportPath = constr(regex=r"^[A-Za-z0-9_.]+$") +PythonImportPath = Annotated[str, StringConstraints(pattern=r"^[A-Za-z0-9_.]+$")] class OperationError(BaseModel): code: str message: str - details: Any + details: Any = None -class Operation(GenericModel, Generic[ResultT, MetadataT]): +class Operation(BaseModel, Generic[ResultT, MetadataT]): id: str done: bool = False expire_time: datetime.datetime - result: Optional[Union[ResultT, OperationError]] - metadata: Optional[MetadataT] + result: Optional[Union[ResultT, OperationError]] = None + metadata: Optional[MetadataT] = None -class UpdateOperationRequest(GenericModel, Generic[ResultT, MetadataT]): +class UpdateOperationRequest(BaseModel, Generic[ResultT, MetadataT]): done: bool = False - result: Optional[Union[ResultT, OperationError]] + result: Optional[Union[ResultT, OperationError]] = None metadata: Optional[MetadataT] = {} -class ListOperationsResponse(GenericModel, Generic[ResultT, MetadataT]): +class ListOperationsResponse(BaseModel, Generic[ResultT, MetadataT]): resources: List[Operation[ResultT, MetadataT]] - next_page_token: Optional[str] + next_page_token: Optional[str] = None class Result(BaseModel): - model: Optional[PythonImportPath] + model: Optional[PythonImportPath] = None class EmptyResult(Result): @@ -47,7 +47,7 @@ class EmptyResult(Result): class Metadata(BaseModel): # XXX alternative: set model field using __class__ on __init__()? - model: Optional[PythonImportPath] + model: Optional[PythonImportPath] = None class PausedOrNot(Metadata): diff --git a/nmdc_runtime/api/models/query.py b/nmdc_runtime/api/models/query.py index 9c2351de..828f5a43 100644 --- a/nmdc_runtime/api/models/query.py +++ b/nmdc_runtime/api/models/query.py @@ -2,23 +2,24 @@ from typing import Optional, Any, Dict, List, Union from pydantic import ( + model_validator, + Field, BaseModel, - root_validator, - conint, PositiveInt, NonNegativeInt, ) +from typing_extensions import Annotated Document = Dict[str, Any] -OneOrZero = conint(ge=0, le=1) -One = conint(ge=1, le=1) -MinusOne = conint(ge=-1, le=-1) +OneOrZero = Annotated[int, Field(ge=0, le=1)] +One = Annotated[int, Field(ge=1, le=1)] +MinusOne = Annotated[int, Field(ge=-1, le=-1)] OneOrMinusOne = Union[One, MinusOne] class CommandBase(BaseModel): - comment: Optional[Any] + comment: Optional[Any] = None class CollStatsCommand(CommandBase): @@ -28,17 +29,17 @@ class CollStatsCommand(CommandBase): class CountCommand(CommandBase): count: str - query: Optional[Document] + query: Optional[Document] = None class FindCommand(CommandBase): find: str - filter: Optional[Document] - projection: Optional[Dict[str, OneOrZero]] + filter: Optional[Document] = None + projection: Optional[Dict[str, OneOrZero]] = None allowPartialResults: Optional[bool] = True batchSize: Optional[PositiveInt] = 101 - sort: Optional[Dict[str, OneOrMinusOne]] - limit: Optional[NonNegativeInt] + sort: Optional[Dict[str, OneOrMinusOne]] = None + limit: Optional[NonNegativeInt] = None class CommandResponse(BaseModel): @@ -49,7 +50,7 @@ class CollStatsCommandResponse(CommandResponse): ns: str size: float count: float - avgObjSize: Optional[float] + avgObjSize: Optional[float] = None storageSize: float totalIndexSize: float totalSize: float @@ -62,8 +63,8 @@ class CountCommandResponse(CommandResponse): class FindCommandResponseCursor(BaseModel): firstBatch: List[Document] - partialResultsReturned: Optional[bool] - id: Optional[int] + partialResultsReturned: Optional[bool] = None + id: Optional[int] = None ns: str @@ -74,7 +75,7 @@ class FindCommandResponse(CommandResponse): class DeleteCommandDelete(BaseModel): q: Document limit: OneOrZero - hint: Optional[Dict[str, OneOrMinusOne]] + hint: Optional[Dict[str, OneOrMinusOne]] = None class DeleteCommand(CommandBase): @@ -85,19 +86,19 @@ class DeleteCommand(CommandBase): class DeleteCommandResponse(CommandResponse): ok: OneOrZero n: NonNegativeInt - writeErrors: Optional[List[Document]] + writeErrors: Optional[List[Document]] = None class GetMoreCommand(CommandBase): getMore: int collection: str - batchSize: Optional[PositiveInt] + batchSize: Optional[PositiveInt] = None class GetMoreCommandResponseCursor(BaseModel): nextBatch: List[Document] - partialResultsReturned: Optional[bool] - id: Optional[int] + partialResultsReturned: Optional[bool] = None + id: Optional[int] = None ns: str @@ -138,10 +139,10 @@ class Query(BaseModel): class QueryRun(BaseModel): qid: str ran_at: datetime.datetime - result: Optional[Any] - error: Optional[Any] + result: Optional[Any] = None + error: Optional[Any] = None - @root_validator + @model_validator(mode="before") def result_xor_error(cls, values): result, error = values.get("result"), values.get("error") if result is None and error is None: diff --git a/nmdc_runtime/api/models/run.py b/nmdc_runtime/api/models/run.py index 4f7cd760..43bf734e 100644 --- a/nmdc_runtime/api/models/run.py +++ b/nmdc_runtime/api/models/run.py @@ -41,7 +41,7 @@ class JobSummary(OpenLineageBase): class Run(BaseModel): id: str - facets: Optional[dict] + facets: Optional[dict] = None class RunEventType(str, Enum): @@ -93,7 +93,11 @@ def _add_run_requested_event(run_spec: RunUserSpec, mdb: MongoDatabase, user: Us time=now(as_str=True), inputs=run_spec.inputs, ) - mdb.run_events.insert_one(event.dict()) + mdb.run_events.insert_one( + event.model_dump( + mode="json", + ) + ) return run_id @@ -113,7 +117,9 @@ def _add_run_started_event(run_id: str, mdb: MongoDatabase): job=requested.job, type=RunEventType.STARTED, time=now(as_str=True), - ).dict() + ).model_dump( + mode="json", + ) ) return run_id @@ -134,7 +140,9 @@ def _add_run_fail_event(run_id: str, mdb: MongoDatabase): job=requested.job, type=RunEventType.FAIL, time=now(as_str=True), - ).dict() + ).model_dump( + mode="json", + ) ) return run_id @@ -156,6 +164,8 @@ def _add_run_complete_event(run_id: str, mdb: MongoDatabase, outputs: List[str]) type=RunEventType.COMPLETE, time=now(as_str=True), outputs=outputs, - ).dict() + ).model_dump( + mode="json", + ) ) return run_id diff --git a/nmdc_runtime/api/models/util.py b/nmdc_runtime/api/models/util.py index 4a1413b9..c298560e 100644 --- a/nmdc_runtime/api/models/util.py +++ b/nmdc_runtime/api/models/util.py @@ -2,15 +2,15 @@ from fastapi import Query -from pydantic import BaseModel, root_validator, conint -from pydantic.generics import GenericModel +from pydantic import model_validator, Field, BaseModel +from typing_extensions import Annotated ResultT = TypeVar("ResultT") -class ListResponse(GenericModel, Generic[ResultT]): +class ListResponse(BaseModel, Generic[ResultT]): resources: List[ResultT] - next_page_token: Optional[str] + next_page_token: Optional[str] = None class ListRequest(BaseModel): @@ -19,9 +19,9 @@ class ListRequest(BaseModel): Query( description='MongoDB-style JSON filter document. Example: `{"ecosystem_type": "Freshwater"}`' ), - ] + ] = None max_page_size: Optional[int] = 20 - page_token: Optional[str] + page_token: Optional[str] = None projection: Annotated[ Optional[str], Query( @@ -33,28 +33,28 @@ class ListRequest(BaseModel): "Example: `ecosystem_type,name`" ) ), - ] + ] = None -PerPageRange = conint(gt=0, le=2_000) +PerPageRange = Annotated[int, Field(gt=0, le=2_000)] class FindRequest(BaseModel): - filter: Optional[str] - search: Optional[str] - sort: Optional[str] - page: Optional[int] + filter: Optional[str] = None + search: Optional[str] = None + sort: Optional[str] = None + page: Optional[int] = None per_page: Optional[PerPageRange] = 25 - cursor: Optional[str] - group_by: Optional[str] + cursor: Optional[str] = None + group_by: Optional[str] = None fields: Annotated[ Optional[str], Query( description="comma-separated list of fields you want the objects in the response to include" ), - ] + ] = None - @root_validator(pre=True) + @model_validator(mode="before") def set_page_if_cursor_unset(cls, values): page, cursor = values.get("page"), values.get("cursor") if page is not None and cursor is not None: diff --git a/nmdc_runtime/api/models/workflow.py b/nmdc_runtime/api/models/workflow.py index 10c2564d..a7740752 100644 --- a/nmdc_runtime/api/models/workflow.py +++ b/nmdc_runtime/api/models/workflow.py @@ -5,11 +5,11 @@ class WorkflowBase(BaseModel): - name: Optional[str] - description: Optional[str] - capability_ids: Optional[List[str]] + name: Optional[str] = None + description: Optional[str] = None + capability_ids: Optional[List[str]] = None class Workflow(WorkflowBase): id: str - created_at: Optional[datetime.datetime] + created_at: Optional[datetime.datetime] = None diff --git a/nmdc_runtime/api/v1/models/ingest.py b/nmdc_runtime/api/v1/models/ingest.py index 857383c2..a0e384f3 100644 --- a/nmdc_runtime/api/v1/models/ingest.py +++ b/nmdc_runtime/api/v1/models/ingest.py @@ -6,6 +6,6 @@ class Ingest(BaseModel): data_object_set: List[DataObject] = [] - read_qc_analysis_activity_set: Optional[List[ReadsQCSequencingActivity]] - metagenome_assembly_activity_set: Optional[List[ReadsQCSequencingActivity]] - metagenome_annotation_activity_set: Optional[List[ReadsQCSequencingActivity]] + read_qc_analysis_activity_set: Optional[List[ReadsQCSequencingActivity]] = None + metagenome_assembly_activity_set: Optional[List[ReadsQCSequencingActivity]] = None + metagenome_annotation_activity_set: Optional[List[ReadsQCSequencingActivity]] = None diff --git a/nmdc_runtime/core/exceptions/token.py b/nmdc_runtime/core/exceptions/token.py index c5e9b1c3..afe00871 100644 --- a/nmdc_runtime/core/exceptions/token.py +++ b/nmdc_runtime/core/exceptions/token.py @@ -1,4 +1,4 @@ -from core.exceptions import CustomException +from nmdc_runtime.core.exceptions import CustomException class DecodeTokenException(CustomException): diff --git a/nmdc_runtime/infrastructure/database/impl/mongo/models/user.py b/nmdc_runtime/infrastructure/database/impl/mongo/models/user.py index 88ad3423..586d4362 100644 --- a/nmdc_runtime/infrastructure/database/impl/mongo/models/user.py +++ b/nmdc_runtime/infrastructure/database/impl/mongo/models/user.py @@ -4,7 +4,7 @@ from typing import Optional, List from beanie import Document, Indexed -from pydantic import EmailStr +from pydantic import ConfigDict, EmailStr from nmdc_runtime.api.core.auth import verify_password from nmdc_runtime.domain.users.userSchema import UserAuth, UserUpdate, UserOut @@ -21,9 +21,8 @@ class DocumentMeta: full_name: Optional[str] = None site_admin: Optional[List[str]] = [] disabled: Optional[bool] = False - - class Config: - schema_extra = { + model_config = ConfigDict( + json_schema_extra={ "username": "bob", "email": "test@test.com", "full_name": "test", @@ -31,13 +30,13 @@ class Config: "site_admin": ["test_site"], "created_date": "1/1/2020", } + ) class UserQueries(IUserQueries): """Implementation of the User query interface""" async def create(self, user: UserAuth) -> UserOut: - auth_user = await User.get(user.username) if not auth_user: auth_user = User( diff --git a/nmdc_runtime/minter/adapters/repository.py b/nmdc_runtime/minter/adapters/repository.py index 25382731..879bdcc8 100644 --- a/nmdc_runtime/minter/adapters/repository.py +++ b/nmdc_runtime/minter/adapters/repository.py @@ -97,7 +97,9 @@ def mint(self, req_mint: MintingRequest) -> list[Identifier]: ) ) for id_ in ids: - self.db[id_.id] = id_.dict() + self.db[id_.id] = id_.model_dump( + mode="json", + ) return ids def bind(self, req_bind: BindingRequest) -> Identifier: @@ -184,7 +186,14 @@ def mint(self, req_mint: MintingRequest) -> list[Identifier]: ) for id_name in not_taken ] - self.db["minter.id_records"].insert_many([i.dict() for i in ids]) + self.db["minter.id_records"].insert_many( + [ + i.model_dump( + mode="json", + ) + for i in ids + ] + ) collected.extend(ids) if len(collected) == req_mint.how_many: break diff --git a/nmdc_runtime/minter/domain/model.py b/nmdc_runtime/minter/domain/model.py index c25dec48..28436509 100644 --- a/nmdc_runtime/minter/domain/model.py +++ b/nmdc_runtime/minter/domain/model.py @@ -9,7 +9,7 @@ class Entity(BaseModel): """A domain object whose attributes may change but has a recognizable identity over time.""" - id: str | None + id: str | None = None class ValueObject(BaseModel): @@ -65,7 +65,7 @@ class Identifier(Entity): typecode: Entity shoulder: Entity status: Status - bindings: Optional[dict] + bindings: Optional[dict] = None class Typecode(Entity): diff --git a/nmdc_runtime/minter/entrypoints/fastapi_app.py b/nmdc_runtime/minter/entrypoints/fastapi_app.py index d0ac097f..3d4b7efc 100644 --- a/nmdc_runtime/minter/entrypoints/fastapi_app.py +++ b/nmdc_runtime/minter/entrypoints/fastapi_app.py @@ -37,7 +37,13 @@ def mint_ids( requester = Entity(id=site.id) try: minted = s.mint( - MintingRequest(service=service, requester=requester, **req_mint.dict()) + MintingRequest( + service=service, + requester=requester, + **req_mint.model_dump( + mode="json", + ), + ) ) return [d.id for d in minted] except MinterError as e: diff --git a/nmdc_runtime/site/changesheets/__init__.py b/nmdc_runtime/site/changesheets/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/nmdc_runtime/site/changesheets/base.py b/nmdc_runtime/site/changesheets/base.py new file mode 100644 index 00000000..1f4ea745 --- /dev/null +++ b/nmdc_runtime/site/changesheets/base.py @@ -0,0 +1,85 @@ +# nmdc_runtime/site/changesheets/base.py +""" +base.py: Provides data classes for creating changesheets for NMDC database objects. +""" + +import logging +import time +from dataclasses import dataclass, field +from pathlib import Path +import requests +from typing import Any, ClassVar, Dict, TypeAlias, Optional + +from nmdc_runtime.site.resources import RuntimeApiUserClient + +logging.basicConfig( + level=logging.INFO, format="%(asctime)s %(levelname)s %(" "message)s" +) + +JSON_OBJECT: TypeAlias = Dict[str, Any] +CHANGESHEETS_DIR = Path(__file__).parent.absolute().joinpath("changesheets_output") + + +@dataclass +class ChangesheetLineItem: + """ + A line item in a changesheet + """ + + id: str + action: str + attribute: str + value: str + + @property + def line(self) -> str: + """ + Return the line item as a tab-separated string + """ + cleaned_value = self.value.replace("\n", " ").replace("\t", " ").strip() + return f"{self.id}\t{self.action}\t{self.attribute}\t{cleaned_value}" + + +@dataclass +class Changesheet: + """ + A changesheet + """ + + name: str + line_items: list = field(default_factory=list) + header: ClassVar[str] = "id\taction\tattribute\tvalue" + output_dir: Optional[Path] = None + + def __post_init__(self): + self.line_items = [] + if self.output_dir is None: + self.output_dir = CHANGESHEETS_DIR + self.output_dir.mkdir(parents=True, exist_ok=True) + self.output_filename_root: str = f"{self.name}-{time.strftime('%Y%m%d-%H%M%S')}" + self.output_filename: str = f"{self.output_filename_root}.tsv" + self.output_filepath: Path = self.output_dir.joinpath(self.output_filename) + + def validate_changesheet(self, base_url: str) -> bool: + """ + Validate the changesheet + :return: None + """ + logging.info(f"Validating changesheet {self.output_filepath}") + url = f"{base_url}/metadata/changesheets:validate" + resp = requests.post( + url, + files={"uploaded_file": open(self.output_filepath, "rb")}, + ) + return resp.ok + + def write_changesheet(self) -> None: + """ + Write the changesheet to a file + :return: None + """ + with open(self.output_filepath, "w") as f: + logging.info(f"Writing changesheet to {self.output_filepath}") + f.write(self.header + "\n") + for line_item in self.line_items: + f.write(line_item.line + "\n") diff --git a/nmdc_runtime/site/changesheets/data/OmicsProcessing-to-catted-Biosamples.tsv b/nmdc_runtime/site/changesheets/data/OmicsProcessing-to-catted-Biosamples.tsv new file mode 100644 index 00000000..384b6f40 --- /dev/null +++ b/nmdc_runtime/site/changesheets/data/OmicsProcessing-to-catted-Biosamples.tsv @@ -0,0 +1,1561 @@ +OmicsProcessing Biosamples +nmdc:omprc-11-t0jqr240 nmdc:bsm-11-n4htkv94|nmdc:bsm-11-xkrpjq36 +nmdc:omprc-11-c4v85b38 nmdc:bsm-11-e552n350|nmdc:bsm-11-mg8ehr76|nmdc:bsm-11-v15pnd34 +nmdc:omprc-11-pktdd848 nmdc:bsm-11-1ymf2v75|nmdc:bsm-11-7np03b47|nmdc:bsm-11-h5dd9655 +nmdc:omprc-11-gxkk6y58 nmdc:bsm-11-ahzpxd86|nmdc:bsm-11-kz5k2q77|nmdc:bsm-11-mxea3c60 +nmdc:omprc-11-akbn9h70 nmdc:bsm-11-bdjvey41|nmdc:bsm-11-g03vdw82|nmdc:bsm-11-ky3q8q24 +nmdc:omprc-11-5jgtpk10 nmdc:bsm-11-1yz48307|nmdc:bsm-11-7624jn29|nmdc:bsm-11-w2875212 +nmdc:omprc-11-wb44ve09 nmdc:bsm-11-6dk3nd34|nmdc:bsm-11-n8n67831|nmdc:bsm-11-z4sq0940 +nmdc:omprc-11-qqh9y864 nmdc:bsm-11-29y6f126|nmdc:bsm-11-9nppap58|nmdc:bsm-11-rx5rdg44 +nmdc:omprc-11-ka9t3a62 nmdc:bsm-11-3zbnxv93|nmdc:bsm-11-s1gn5316|nmdc:bsm-11-znh48572 +nmdc:omprc-11-nkxz4j62 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nmdc:bsm-11-ykk0ch50 +nmdc:omprc-11-5svn9459 nmdc:bsm-11-41mb3v03 +nmdc:omprc-11-tk524444 nmdc:bsm-11-hew13816 +nmdc:omprc-11-m3xy0c35 nmdc:bsm-11-jbk0f273 +nmdc:omprc-11-tvg68444 nmdc:bsm-11-84dyfy12 +nmdc:omprc-11-ftxaqb44 nmdc:bsm-11-8ywma992 diff --git a/nmdc_runtime/site/changesheets/scripts/missing_neon_soils_ecosystem_data.py b/nmdc_runtime/site/changesheets/scripts/missing_neon_soils_ecosystem_data.py new file mode 100755 index 00000000..032b3d37 --- /dev/null +++ b/nmdc_runtime/site/changesheets/scripts/missing_neon_soils_ecosystem_data.py @@ -0,0 +1,323 @@ +#!/usr/bin/env python +# nmdc_runtime/site/changesheets/scripts/missing_neon_soils_ecosystem_data.py +""" +missing_neon_soils_ecosystem_data.py: Create a changesheet for missing ecosystem data for NEON soils samples +""" + +import logging +import os +import time +from pathlib import Path +from typing import List, Tuple + +import click +from dotenv import load_dotenv + +from nmdc_runtime.site.changesheets.base import ( + Changesheet, + ChangesheetLineItem, + JSON_OBJECT, +) +from nmdc_runtime.site.normalization.gold import ( + get_gold_biosample_name_suffix, + normalize_gold_id, +) +from nmdc_runtime.site.resources import GoldApiClient, RuntimeApiUserClient + +load_dotenv() +GOLD_NEON_SOIL_STUDY_ID = "Gs0144570" +NAME = "missing_neon_soils_ecosystem_data" +# omics processing to biosamples file in data directory +DATA_PATH = Path(__file__).parent.parent.joinpath("data") + +log_filename = f"{NAME}-{time.strftime('%Y%m%d-%H%M%S')}.log" +logging.basicConfig( + level=logging.INFO, + format="%(asctime)s %(levelname)s %(message)s", + filename=log_filename, + encoding="utf-8", + filemode="w", +) + + +def read_omics_processing_to_biosample_map() -> dict: + """ + Map omics processing to biosamples + :return: dict + """ + omics_processing_to_biosamples = {} + with open(DATA_PATH.joinpath("OmicsProcessing-to-catted-Biosamples.tsv")) as f: + lines_read = 0 + lines_skipped = 0 + for line in f: + if not line.startswith("nmdc:"): + lines_skipped += 1 + continue + lines_read += 1 + omics_processing_id, biosample_ids = line.strip().split("\t") + omics_processing_to_biosamples[omics_processing_id] = biosample_ids.split( + "|" + ) + logging.debug( + f"Read {lines_read} lines from OmicsProcessing-to-catted-Biosamples.tsv" + ) + logging.info( + f"Skipped {lines_skipped} lines from OmicsProcessing-to-catted-Biosamples.tsv" + ) + return omics_processing_to_biosamples + + +def gold_biosample_to_nmdc_biosamples_and_omics_processing_records( + runtime_api_client, omprc_to_bs_map, goldbs +) -> Tuple[List[JSON_OBJECT], List[JSON_OBJECT]]: + """ + Find the corresponding NMDC biosamples and omics processing records for a + GOLD biosample + :param runtime_api_client: + :param omprc_to_bs_map: Dict of omics processing ID to biosample IDs + :param goldbs: a GOLD biosample + :return: ( + List of corresponding NMDC biosamples, + List of corresponding NMDC omics processing records + ) + """ + goldbs_id = normalize_gold_id(goldbs["biosampleGoldId"]) + goldbs_name_suffix = get_gold_biosample_name_suffix(goldbs["biosampleName"]) + logging.info(f"goldbs_id: {goldbs_id}") + logging.info(f"goldbs_name_suffix: {goldbs_name_suffix}") + + # Search for NMDC biosamples with by GOLD biosample ID + nmdc_biosamples = [] + logging.info(f"Searching for NMDC biosamples with {goldbs_id}...") + nmdcbs_response = runtime_api_client.get_biosamples_by_gold_biosample_id(goldbs_id) + if nmdcbs_response.status_code != 200: + logging.error( + f"Failed to retrieve NMDC biosamples with {goldbs_id}: {nmdcbs_response.status_code}" + ) + + nmdcbs = nmdcbs_response.json()["cursor"]["firstBatch"] + logging.info(f"Found {len(nmdcbs)} NMDC biosamples with {goldbs_id}...") + nmdc_biosamples.extend(nmdcbs) + + # Search for NMDC biosamples via omics processing name containing GOLD biosample name suffix + logging.info( + f"Searching for NMDC omics processing name containing {goldbs_name_suffix}..." + ) + omprc_response = runtime_api_client.get_omics_processing_by_name(goldbs_name_suffix) + if omprc_response.status_code != 200: + logging.error( + f"Failed to retrieve NMDC omics processing with {goldbs_name_suffix}: {omprc_response.status_code}" + ) + + omprc_records = omprc_response.json()["cursor"]["firstBatch"] + for omprc in omprc_records: + omprc_id = omprc["id"] + logging.info(f"omprc_id: {omprc_id}") + logging.info( + f"Searching for NMDC biosamples with omics processing {omprc_id}..." + ) + nmdcbs_ids = omprc_to_bs_map.get(omprc_id, []) + logging.info(f"Found {len(nmdcbs_ids)} NMDC biosamples with {omprc_id}...") + for nmdcbs_id in nmdcbs_ids: + nmdcbs_req = runtime_api_client.request("GET", f"/biosamples/{nmdcbs_id}") + if nmdcbs_req.status_code != 200: + logging.error( + f"Failed to retrieve NMDC biosample {nmdcbs_id}: {nmdcbs_req.status_code}" + ) + continue + nmdcbs = nmdcbs_req.json() + nmdc_biosamples.append(nmdcbs) + + logging.info(f"Found {len(nmdc_biosamples)} NMDC biosamples for {goldbs_id}...") + return nmdc_biosamples, omprc_records + + +def compare_biosamples(goldbs, nmdcbs) -> List[ChangesheetLineItem]: + changesheet_line_items = [] + + # Check for missing ecosystem metadata + changesheet_line_items.extend(_check_ecosystem_metadata(goldbs, nmdcbs)) + + # Check for missing gold biosample identifiers + changesheet_line_items.extend(_check_gold_biosample_identifiers(goldbs, nmdcbs)) + + return changesheet_line_items + + +def _check_ecosystem_metadata(goldbs, nmdcbs) -> List[ChangesheetLineItem]: + # nmdc to gold ecosystem key map + ecosystem_key_map = { + "ecosystem": "ecosystem", + "ecosystem_category": "ecosystemCategory", + "ecosystem_type": "ecosystemType", + "ecosystem_subtype": "ecosystemSubtype", + } + changesheet_line_items = [] + for nmdc_key, gold_key in ecosystem_key_map.items(): + if not gold_key in goldbs: + logging.warning(f"no {gold_key} for {goldbs['biosampleGoldId']}...") + continue + if not nmdc_key in nmdcbs: + changesheet_line_items.append( + ChangesheetLineItem( + id=nmdcbs["id"], + action="update", + attribute=nmdc_key, + value=goldbs.get(gold_key), + ) + ) + continue + if nmdcbs[nmdc_key] != goldbs.get(gold_key): + changesheet_line_items.append( + ChangesheetLineItem( + id=nmdcbs["id"], + action="update", + attribute=nmdc_key, + value=goldbs.get(gold_key), + ) + ) + continue + + return changesheet_line_items + + +def _check_gold_biosample_identifiers(goldbs, nmdcbs) -> List[ChangesheetLineItem]: + changesheet_line_items = [] + goldbs_id = normalize_gold_id(goldbs["biosampleGoldId"]) + if not goldbs_id in nmdcbs["gold_biosample_identifiers"]: + changesheet_line_items.append( + ChangesheetLineItem( + id=nmdcbs["id"], + action="insert", + attribute="gold_biosample_identifiers", + value=goldbs_id + "|", + ) + ) + return changesheet_line_items + + +def compare_projects(gold_project, omprc_record) -> ChangesheetLineItem: + gold_project_id = normalize_gold_id(gold_project["projectGoldId"]) + if "gold_sequencing_project_identifiers" not in omprc_record: + return ChangesheetLineItem( + id=omprc_record["id"], + action="insert", + attribute="gold_sequencing_project_identifiers", + value=gold_project_id + "|", + ) + + if gold_project_id not in omprc_record["gold_sequencing_project_identifiers"]: + return ChangesheetLineItem( + id=omprc_record["id"], + action="insert", + attribute="gold_sequencing_project_identifiers", + value=gold_project_id + "|", + ) + + +@click.command() +@click.option("--study_id", default=GOLD_NEON_SOIL_STUDY_ID, help="GOLD study ID") +@click.option("--use_dev_api", is_flag=True, default=False, help="Use the dev API") +def generate_changesheet(study_id, use_dev_api): + """ + Generate a changesheet for missing ecosystem data for NEON soils samples by: + 1. Retrieving GOLD biosamples for the given study + 2. Finding the corresponding NMDC biosamples and omics processing records for each GOLD biosample + 3. Comparing the GOLD biosample to the NMDC biosamples and omics processing records + 4. Generating a changesheet for the differences + + WARNING: This script is not idempotent. It will generate a new changesheet each time it is run. + + Changesheet is written to nmdc_runtime/site/changesheets/changesheets_output + + :param study_id: The GOLD study ID + :param use_dev_api: Use the dev API (default: False) + :return: + """ + start_time = time.time() + logging.info("starting missing_neon_soils_ecosystem_data.py...") + logging.info(f"study_id: {study_id}") + + gold_api_client = GoldApiClient( + base_url=os.getenv("GOLD_API_BASE_URL"), + username=os.getenv("GOLD_API_USERNAME"), + password=os.getenv("GOLD_API_PASSWORD"), + ) + logging.info("connected to GOLD API...") + + if use_dev_api: + base_url = os.getenv("API_HOST_DEV") + logging.info("using dev API...") + else: + base_url = os.getenv("API_HOST") + logging.info("using prod API...") + + runtime_api_user_client = RuntimeApiUserClient( + base_url=base_url, + username=os.getenv("API_QUERY_USER"), + password=os.getenv("API_QUERY_PASS"), + ) + logging.info("connected to NMDC API...") + + # Retrieve GOLD biosamples for the given study + gold_biosamples = gold_api_client.fetch_biosamples_by_study(study_id) + logging.info(f"retrieved {len(gold_biosamples)} biosamples from GOLD API...") + + # omics processing to biosamples map generated by a SPARQL query + omprc_to_bs_map = read_omics_processing_to_biosample_map() + + changesheet = Changesheet(name=NAME) + # For each GOLD biosample, find the corresponding NMDC biosamples + nmdcbs_count = 0 + unfindable_goldbs_ids = [] + for goldbs in gold_biosamples: + ( + nmdc_biosamples, + omprc_records, + ) = gold_biosample_to_nmdc_biosamples_and_omics_processing_records( + runtime_api_user_client, omprc_to_bs_map, goldbs + ) + if not nmdc_biosamples: + logging.warning( + f"no corresponding NMDC biosamples found for {goldbs['biosampleGoldId']}..." + ) + unfindable_goldbs_ids.append(goldbs["biosampleGoldId"]) + continue + logging.info( + f"found {len(nmdc_biosamples)} corresponding NMDC biosamples for {goldbs['biosampleGoldId']}..." + ) + nmdcbs_count += len(nmdc_biosamples) + for nmdcbs in nmdc_biosamples: + logging.info(f"nmdcbs: {nmdcbs['id']}") + changesheet.line_items.extend(compare_biosamples(goldbs, nmdcbs)) + + # Insert gold project id into omprc alternative identifiers + gold_projects = gold_api_client.request( + "/projects", params={"biosampleGoldId": goldbs["biosampleGoldId"]} + ) + for gold_project in gold_projects: + for omprc_record in omprc_records: + changesheet.line_items.append( + compare_projects(gold_project, omprc_record) + ) + + logging.info(f"Processed {len(gold_biosamples)} GOLD biosamples...") + logging.info(f"found {nmdcbs_count} corresponding NMDC biosamples...") + logging.info(f"unfindable_count: {len(unfindable_goldbs_ids)}...") + for unfindable_goldbs_ids in unfindable_goldbs_ids: + logging.info(f"unfindable_goldbs_id: {unfindable_goldbs_ids}...") + logging.info(f"changesheet has {len(changesheet.line_items)} line items...") + + changesheet.write_changesheet() + + logging.info("Validating changesheet...") + is_valid_changesheet = changesheet.validate_changesheet(base_url) + logging.info(f"Changesheet is valid: {is_valid_changesheet}") + + logging.info( + f"missing_neon_soils_ecosystem_data.py completed in {time.time() - start_time} seconds..." + ) + + +if __name__ == "__main__": + generate_changesheet() diff --git a/nmdc_runtime/site/drsobjects/ingest.py b/nmdc_runtime/site/drsobjects/ingest.py index b4b7dc38..26a26f43 100644 --- a/nmdc_runtime/site/drsobjects/ingest.py +++ b/nmdc_runtime/site/drsobjects/ingest.py @@ -44,7 +44,11 @@ def claim_metadata_ingest_jobs( ) jobs = [] while True: - rv = client.list_jobs(lr.dict()).json() + rv = client.list_jobs( + lr.model_dump( + mode="json", + ) + ).json() jobs.extend(rv["resources"]) if "next_page_token" not in rv: break diff --git a/nmdc_runtime/site/graphs.py b/nmdc_runtime/site/graphs.py index 503e6e8c..6c8cb4b9 100644 --- a/nmdc_runtime/site/graphs.py +++ b/nmdc_runtime/site/graphs.py @@ -40,6 +40,8 @@ nmdc_schema_database_export_filename_neon, get_neon_pipeline_mms_data_product, get_neon_pipeline_sls_data_product, + get_submission_portal_pipeline_inputs, + get_csv_rows_from_url, ) @@ -134,8 +136,19 @@ def gold_study_to_database(): @graph def translate_metadata_submission_to_nmdc_schema_database(): - metadata_submission = fetch_nmdc_portal_submission_by_id() - database = translate_portal_submission_to_nmdc_schema_database(metadata_submission) + ( + submission_id, + omics_processing_mapping_file_url, + data_object_mapping_file_url, + ) = get_submission_portal_pipeline_inputs() + + metadata_submission = fetch_nmdc_portal_submission_by_id(submission_id) + omics_processing_mapping = get_csv_rows_from_url(omics_processing_mapping_file_url) + data_object_mapping = get_csv_rows_from_url(data_object_mapping_file_url) + + database = translate_portal_submission_to_nmdc_schema_database( + metadata_submission, omics_processing_mapping, data_object_mapping + ) validate_metadata(database) @@ -147,8 +160,19 @@ def translate_metadata_submission_to_nmdc_schema_database(): @graph def ingest_metadata_submission(): - metadata_submission = fetch_nmdc_portal_submission_by_id() - database = translate_portal_submission_to_nmdc_schema_database(metadata_submission) + ( + submission_id, + omics_processing_mapping_file_url, + data_object_mapping_file_url, + ) = get_submission_portal_pipeline_inputs() + + metadata_submission = fetch_nmdc_portal_submission_by_id(submission_id) + omics_processing_mapping = get_csv_rows_from_url(omics_processing_mapping_file_url) + data_object_mapping = get_csv_rows_from_url(data_object_mapping_file_url) + + database = translate_portal_submission_to_nmdc_schema_database( + metadata_submission, omics_processing_mapping, data_object_mapping + ) run_id = submit_metadata_to_db(database) poll_for_run_completion(run_id) diff --git a/nmdc_runtime/site/normalization/__init__.py b/nmdc_runtime/site/normalization/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/nmdc_runtime/site/normalization/gold.py b/nmdc_runtime/site/normalization/gold.py new file mode 100644 index 00000000..36af11f2 --- /dev/null +++ b/nmdc_runtime/site/normalization/gold.py @@ -0,0 +1,44 @@ +# nmdc_runtime/site/normalization/gold.py +""" +gold.py: Provides functions to normalize and validate JGI GOLD data. +""" +import logging +from typing import Dict, Any + +JSON_OBJECT = Dict[str, Any] + +logging.basicConfig( + level=logging.INFO, + format="%(asctime)s %(levelname)s %(message)s", +) + + +def get_gold_biosample_name_suffix(biosample_name: str) -> str: + """ + Get the suffix for the name of a GOLD biosample - the last word in the biosampleName attribute + e.g. "biosampleName": "Terrestrial soil microbial communities from + Disney Wilderness Preserve, Southeast, FL, USA - DSNY_016-M-37-14-20140409-GEN-DNA1", + + Suffix = DSNY_016-M-37-14-20140409-GEN-DNA1 + + :param biosample_name: str - the value of the biosampleName attribute + :return: str + """ + return biosample_name.split()[-1] + + +def normalize_gold_id(gold_id: str) -> str: + """ + Normalize the given GOLD ID - e.g. biosample Gb012345 to the form + "gold:Gb012345" + :param gold_id: str - the GOLD ID to normalize + :return: str - the normalized GOLD ID + """ + if gold_id.startswith("gold:"): + return gold_id + elif gold_id.upper().startswith("GOLD:"): + return f"gold:{gold_id[5:]}" + elif gold_id.startswith("G") and ":" not in gold_id: + return f"gold:{gold_id}" + + return gold_id diff --git a/nmdc_runtime/site/ops.py b/nmdc_runtime/site/ops.py index 0f2fc2c3..265498ab 100644 --- a/nmdc_runtime/site/ops.py +++ b/nmdc_runtime/site/ops.py @@ -1,3 +1,4 @@ +import csv import json import mimetypes import os @@ -6,8 +7,10 @@ from collections import defaultdict from datetime import datetime, timezone from io import BytesIO +from typing import Tuple from zipfile import ZipFile import pandas as pd +import requests from bson import ObjectId, json_util from dagster import ( @@ -25,6 +28,7 @@ RetryRequested, String, op, + Optional, ) from gridfs import GridFS from linkml_runtime.dumpers import json_dumper @@ -77,7 +81,7 @@ from pymongo.database import Database as MongoDatabase from starlette import status from terminusdb_client.woqlquery import WOQLQuery as WQ -from toolz import assoc, dissoc, get_in +from toolz import assoc, dissoc, get_in, valfilter, identity @op @@ -263,7 +267,11 @@ def get_operation(context): def produce_curated_db(context, op: Operation): client: RuntimeApiSiteClient = context.resources.runtime_api_site_client mdb: MongoDatabase = context.resources.mongo.db - op = Operation[ResultT, JobOperationMetadata](**op.dict()) + op = Operation[ResultT, JobOperationMetadata]( + **op.model_dump( + mode="json", + ) + ) op_meta: JobOperationMetadata = op.metadata job_id = op_meta.job.id job = mdb.jobs.find_one({"id": job_id}) @@ -346,7 +354,12 @@ def filter_ops_undone_expired() -> str: @op(required_resource_keys={"runtime_api_site_client"}) def list_operations(context, filter_: str) -> list: client = context.resources.runtime_api_site_client - ops = [op.dict() for op in client.list_operations({"filter": filter_})] + ops = [ + op.model_dump( + mode="json", + ) + for op in client.list_operations({"filter": filter_}) + ] context.log.info(str(len(ops))) return ops @@ -462,7 +475,7 @@ def perform_changesheet_updates(context, sheet_in: ChangesheetIn): op = Operation(**mdb.operations.find_one({"id": op_id})) op.done = True op.result = {"update_cmd": json.dumps(update_cmd)} - op_doc = op.dict(exclude_unset=True) + op_doc = op.model_dump(mode="json", exclude_unset=True) mdb.operations.replace_one({"id": op_id}, op_doc) return ["/operations/" + op_doc["id"]] @@ -638,12 +651,34 @@ def id_minter(*args, **kwargs): return database +@op( + config_schema={ + "submission_id": str, + "omics_processing_mapping_file_url": str, + "data_object_mapping_file_url": str, + }, + out={ + "submission_id": Out(), + "omics_processing_mapping_file_url": Out(), + "data_object_mapping_file_url": Out(), + }, +) +def get_submission_portal_pipeline_inputs( + context: OpExecutionContext, +) -> Tuple[str, str, str]: + return ( + context.op_config["submission_id"], + context.op_config["omics_processing_mapping_file_url"], + context.op_config["data_object_mapping_file_url"], + ) + + @op( required_resource_keys={"nmdc_portal_api_client"}, - config_schema={"submission_id": str}, ) -def fetch_nmdc_portal_submission_by_id(context: OpExecutionContext) -> Dict[str, Any]: - submission_id = context.op_config["submission_id"] +def fetch_nmdc_portal_submission_by_id( + context: OpExecutionContext, submission_id: str +) -> Dict[str, Any]: client: NmdcPortalApiClient = context.resources.nmdc_portal_api_client return client.fetch_metadata_submission(submission_id) @@ -652,6 +687,8 @@ def fetch_nmdc_portal_submission_by_id(context: OpExecutionContext) -> Dict[str, def translate_portal_submission_to_nmdc_schema_database( context: OpExecutionContext, metadata_submission: Dict[str, Any], + omics_processing_mapping: List, + data_object_mapping: List, ) -> nmdc.Database: client: RuntimeApiSiteClient = context.resources.runtime_api_site_client @@ -659,7 +696,12 @@ def id_minter(*args, **kwargs): response = client.mint_id(*args, **kwargs) return response.json() - translator = SubmissionPortalTranslator(metadata_submission, id_minter=id_minter) + translator = SubmissionPortalTranslator( + metadata_submission, + omics_processing_mapping, + data_object_mapping, + id_minter=id_minter, + ) database = translator.get_database() return database @@ -773,3 +815,27 @@ def id_minter(*args, **kwargs): @op def nmdc_schema_database_export_filename_neon() -> str: return "database_from_neon_metadata.json" + + +@op +def get_csv_rows_from_url(url: str) -> List[Dict]: + """Download and parse a CSV file from a remote URL. + + This method fetches data from the given URL and parses that data as CSV. The parsed data + is returned as a list (each element corresponds to a row) of dicts (each key is a column + name and the value is the corresponding cell value). The dict will *not* contain keys + for columns where the cell was empty. + + :param url: Url to fetch and parse + :return: List[Dict] + """ + if not url: + return [] + + response = requests.get(url) + response.raise_for_status() + + reader = csv.DictReader(response.text.splitlines()) + # Collect all the rows into a list of dicts while stripping out (valfilter) cells where the + # value is an empty string (identity returns a Falsy value). + return [valfilter(identity, row) for row in reader] diff --git a/nmdc_runtime/site/repository.py b/nmdc_runtime/site/repository.py index 50a91be9..22b9a9c0 100644 --- a/nmdc_runtime/site/repository.py +++ b/nmdc_runtime/site/repository.py @@ -405,7 +405,9 @@ def claim_and_run_apply_changesheet_jobs(_context): def done_object_put_ops(_context): client = get_runtime_api_site_client(run_config_frozen__normal_env) ops = [ - op.dict() + op.model_dump( + mode="json", + ) for op in client.list_operations( { "filter": json.dumps( @@ -518,8 +520,12 @@ def biosample_submission_ingest(): ), "ops": { "export_json_to_drs": {"config": {"username": "..."}}, - "fetch_nmdc_portal_submission_by_id": { - "config": {"submission_id": "..."} + "get_submission_portal_pipeline_inputs": { + "config": { + "submission_id": "", + "omics_processing_mapping_file_url": "", + "data_object_mapping_file_url": "", + } }, }, }, @@ -542,8 +548,12 @@ def biosample_submission_ingest(): }, ), "ops": { - "fetch_nmdc_portal_submission_by_id": { - "config": {"submission_id": "..."} + "get_submission_portal_pipeline_inputs": { + "config": { + "submission_id": "", + "omics_processing_mapping_file_url": "", + "data_object_mapping_file_url": "", + } }, }, }, diff --git a/nmdc_runtime/site/resources.py b/nmdc_runtime/site/resources.py index 6aae27ec..983ab206 100644 --- a/nmdc_runtime/site/resources.py +++ b/nmdc_runtime/site/resources.py @@ -60,7 +60,9 @@ def request(self, method, url_path, params_or_json_data=None): self.ensure_token() kwargs = {"url": self.base_url + url_path, "headers": self.headers} if isinstance(params_or_json_data, BaseModel): - params_or_json_data = params_or_json_data.dict(exclude_unset=True) + params_or_json_data = params_or_json_data.model_dump( + mode="json", exclude_unset=True + ) if method.upper() == "GET": kwargs["params"] = params_or_json_data else: @@ -94,6 +96,30 @@ def validate_metadata(self, database: nmdc.Database): def get_run_info(self, run_id: str): return self.request("GET", f"/runs/{run_id}") + def get_biosamples_by_gold_biosample_id(self, gold_biosample_id: str): + return self.request( + "POST", + f"/queries:run", + { + "find": "biosample_set", + "filter": { + "gold_biosample_identifiers": { + "$elemMatch": {"$eq": gold_biosample_id} + } + }, + }, + ) + + def get_omics_processing_by_name(self, name: str): + return self.request( + "POST", + f"/queries:run", + { + "find": "omics_processing_set", + "filter": {"name": {"$regex": name, "$options": "i"}}, + }, + ) + class RuntimeApiSiteClient(RuntimeApiClient): def __init__( diff --git a/nmdc_runtime/site/terminusdb/schema.py b/nmdc_runtime/site/terminusdb/schema.py index fc6e551f..17f77431 100644 --- a/nmdc_runtime/site/terminusdb/schema.py +++ b/nmdc_runtime/site/terminusdb/schema.py @@ -122,7 +122,7 @@ class NamedThing(DocumentTemplate): _key = LexicalKey(["id"]) _abstract = [] alternative_identifiers: Set[str] - description: Optional[str] + description: Optional[str] = None id: str name: Optional[str] @@ -1105,7 +1105,7 @@ class ImageValue(AttributeValue): null """ - description: Optional[str] + description: Optional[str] = None display_order: Optional[str] url: Optional[str] @@ -1150,7 +1150,7 @@ class DataObject(NamedThing): _key = LexicalKey(["id"]) compression_type: Optional[str] data_object_type: Optional[str] - description: Optional[str] + description: Optional[str] = None file_size_bytes: Optional["xsd:long"] md5_checksum: Optional[str] name: Optional[str] diff --git a/nmdc_runtime/site/translation/submission_portal_translator.py b/nmdc_runtime/site/translation/submission_portal_translator.py index f9dbb7a8..c3050166 100644 --- a/nmdc_runtime/site/translation/submission_portal_translator.py +++ b/nmdc_runtime/site/translation/submission_portal_translator.py @@ -1,13 +1,16 @@ import logging import re -from typing import Any, List, Optional, Union -from nmdc_runtime.site.translation.translator import JSON_OBJECT, Translator -from nmdc_schema import nmdc -from toolz import get_in, groupby, concat +from datetime import datetime +from functools import lru_cache from importlib import resources +from typing import Any, List, Optional, Union + from linkml_runtime import SchemaView from linkml_runtime.linkml_model import SlotDefinition -from functools import lru_cache +from nmdc_schema import nmdc +from toolz import get_in, groupby, concat, valmap, dissoc + +from nmdc_runtime.site.translation.translator import JSON_OBJECT, Translator @lru_cache @@ -27,10 +30,19 @@ class SubmissionPortalTranslator(Translator): the nmdc:Biosample class (via a SchemaView instance) """ - def __init__(self, metadata_submission: JSON_OBJECT = {}, *args, **kwargs) -> None: + def __init__( + self, + metadata_submission: JSON_OBJECT = {}, + omics_processing_mapping: Optional[list] = None, + data_object_mapping: Optional[list] = None, + *args, + **kwargs, + ) -> None: super().__init__(*args, **kwargs) self.metadata_submission = metadata_submission + self.omics_processing_mapping = omics_processing_mapping + self.data_object_mapping = data_object_mapping self.schema_view: SchemaView = _get_schema_view() def _get_pi( @@ -51,19 +63,17 @@ def _get_pi( orcid=study_form.get("piOrcid"), ) - def _get_doi( - self, metadata_submission: JSON_OBJECT - ) -> Union[nmdc.AttributeValue, None]: - """Construct an nmdc:AttributeValue object using information from the context form data + def _get_doi(self, metadata_submission: JSON_OBJECT) -> Union[List[str], None]: + """Get DOI information from the context form data :param metadata_submission: submission portal entry - :return: nmdc:AttributeValue + :return: list of strings or None """ - doi = get_in(["contextForm", "datasetDoi"], metadata_submission) - if not doi: + dataset_doi = get_in(["contextForm", "datasetDoi"], metadata_submission) + if not dataset_doi: return None - return nmdc.AttributeValue(has_raw_value=doi) + return [dataset_doi] def _get_has_credit_associations( self, metadata_submission: JSON_OBJECT @@ -169,7 +179,7 @@ def _get_ontology_class( :param raw_value: string to parse :return: nmdc.OntologyClass """ - match = re.fullmatch("_*([^\[]+)(?:\[([^\]]+)\])", raw_value) + match = re.match("_*([^\[]+)(?:\[([^\]]+)\])", raw_value) if not match or not match.group(2): logging.warning( f'Could not infer OntologyClass id from value "{raw_value}"' @@ -315,13 +325,13 @@ def _translate_study( alternative_names=self._get_from( metadata_submission, ["multiOmicsForm", "alternativeNames"] ), + dataset_dois=self._get_doi(metadata_submission), description=self._get_from( metadata_submission, ["studyForm", "description"] ), - doi=self._get_doi(metadata_submission), - emsl_proposal_identifier=self._get_from( - metadata_submission, ["multiOmicsForm", "studyNumber"] - ), + # emsl_proposal_identifier=self._get_from( + # metadata_submission, ["multiOmicsForm", "studyNumber"] + # ), gold_study_identifiers=self._get_gold_study_identifiers( metadata_submission ), @@ -364,6 +374,39 @@ def _transform_value_for_slot(self, value: Any, slot: SlotDefinition): return transformed_value + def _transform_dict_for_class(self, raw_values: dict, class_name: str) -> dict: + """Transform a dict of values according to class slots. + + raw_values is a dict where the keys are slot names and the values are plain strings. + Each of the items in this dict will be transformed by the _transform_value_for_slot + method. If the slot is multivalued each individual value will be transformed. If the + slot is multivalued and the value is a string it will be split at pipe characters + before transforming. + """ + slot_names = self.schema_view.class_slots(class_name) + transformed_values = {} + for column, value in raw_values.items(): + if column not in slot_names: + logging.warning(f"No slot '{column}' on class '{class_name}'") + continue + + slot_definition = self.schema_view.induced_slot(column, class_name) + if slot_definition.multivalued: + value_list = value + if isinstance(value, str): + value_list = [v.strip() for v in value.split("|")] + transformed_value = [ + self._transform_value_for_slot(item, slot_definition) + for item in value_list + ] + else: + transformed_value = self._transform_value_for_slot( + value, slot_definition + ) + + transformed_values[column] = transformed_value + return transformed_values + def _translate_biosample( self, sample_data: List[JSON_OBJECT], nmdc_biosample_id: str, nmdc_study_id: str ) -> nmdc.Biosample: @@ -387,23 +430,9 @@ def _translate_biosample( "part_of": nmdc_study_id, "name": sample_data[0].get("samp_name"), } - biosample_slot_names = self.schema_view.class_slots("Biosample") for tab in sample_data: - for column, value in tab.items(): - if column not in biosample_slot_names: - logging.warning(f"No slot {column} on nmdc:Biosample") - continue - slot = self.schema_view.induced_slot(column, "Biosample") - - transformed_value = None - if slot.multivalued: - transformed_value = [ - self._transform_value_for_slot(item, slot) for item in value - ] - else: - transformed_value = self._transform_value_for_slot(value, slot) - - slots[column] = transformed_value + transformed_tab = self._transform_dict_for_class(tab, "Biosample") + slots.update(transformed_tab) return nmdc.Biosample(**slots) @@ -444,4 +473,87 @@ def get_database(self) -> nmdc.Database: if sample_data ] + if self.omics_processing_mapping: + # If there is data from an OmicsProcessing mapping file, process it now. This part + # assumes that there is a column in that file with the header __biosample_source_mat_id + # that can be used to join with the sample data from the submission portal. The + # biosample identified by that `source_mat_id` will be referenced in the `has_input` + # slot of the OmicsProcessing object. If a DataObject mapping file was also provided, + # those objects will also be generated and referenced in the `has_output` slot of the + # OmicsProcessing object. By keying off of the `source_mat_id` slot of the submission's + # sample data there is an implicit 1:1 relationship between Biosample objects and + # OmicsProcessing objects generated here. + join_key = "__biosample_source_mat_id" + database.omics_processing_set = [] + database.data_object_set = [] + data_objects_by_sample_data_id = {} + today = datetime.now().strftime("%Y-%m-%d") + + if self.data_object_mapping: + # If DataObject mapping data was provided, group it by the sample ID key and then + # strip that key out of the resulting grouped data. + grouped = groupby(join_key, self.data_object_mapping) + data_objects_by_sample_data_id = valmap( + lambda data_objects: [ + dissoc(data_object, join_key) for data_object in data_objects + ], + grouped, + ) + + for omics_processing_row in self.omics_processing_mapping: + # For each row in the OmicsProcessing mapping file, first grab the minted Biosample + # id that corresponds to the sample ID from the submission + sample_data_id = omics_processing_row.pop(join_key) + if ( + not sample_data_id + or sample_data_id not in sample_data_to_nmdc_biosample_ids + ): + logging.warning( + f"Unrecognized biosample source_mat_id: {sample_data_id}" + ) + continue + nmdc_biosample_id = sample_data_to_nmdc_biosample_ids[sample_data_id] + + # Transform the raw row data according to the OmicsProcessing class's slots, and + # generate an instance. A few key slots do not come from the mapping file, but + # instead are defined here. + omics_processing_slots = { + "id": self._id_minter("nmdc:OmicsProcessing", 1)[0], + "has_input": [nmdc_biosample_id], + "has_output": [], + "part_of": nmdc_study_id, + "add_date": today, + "mod_date": today, + "type": "nmdc:OmicsProcessing", + } + omics_processing_slots.update( + self._transform_dict_for_class( + omics_processing_row, "OmicsProcessing" + ) + ) + omics_processing = nmdc.OmicsProcessing(**omics_processing_slots) + + for data_object_row in data_objects_by_sample_data_id.get( + sample_data_id, [] + ): + # For each row in the DataObject mapping file that corresponds to the sample ID, + # transform the raw row data according to the DataObject class's slots, generate + # an instance, and connect that instance's minted ID to the OmicsProcessing + # instance + data_object_id = self._id_minter("nmdc:DataObject", 1)[0] + data_object_slots = { + "id": data_object_id, + "type": "nmdc:DataObject", + } + data_object_slots.update( + self._transform_dict_for_class(data_object_row, "DataObject") + ) + data_object = nmdc.DataObject(**data_object_slots) + + omics_processing.has_output.append(data_object_id) + + database.data_object_set.append(data_object) + + database.omics_processing_set.append(omics_processing) + return database diff --git a/nmdc_runtime/test.Dockerfile b/nmdc_runtime/test.Dockerfile index 68e5e8b0..c738061e 100644 --- a/nmdc_runtime/test.Dockerfile +++ b/nmdc_runtime/test.Dockerfile @@ -28,10 +28,10 @@ RUN pip install --no-cache-dir -r /code/requirements.txt COPY . /code RUN pip install --no-cache-dir --editable . -# Ensure wait-for-it +## Ensure wait-for-it RUN chmod +x wait-for-it.sh # Best practices: Prepare for C crashes. ENV PYTHONFAULTHANDLER=1 -ENTRYPOINT [ "./wait-for-it.sh" , "fastapi:8000" , "--strict" , "--timeout=300" , "--" , "pytest", "-x"] \ No newline at end of file +ENTRYPOINT [ "./wait-for-it.sh", "fastapi:8000" , "--strict" , "--timeout=300" , "--" , "pytest", "-x"] \ No newline at end of file diff --git a/nmdc_runtime/util.py b/nmdc_runtime/util.py index 316cccdd..23e94dd1 100644 --- a/nmdc_runtime/util.py +++ b/nmdc_runtime/util.py @@ -17,13 +17,14 @@ from jsonschema.validators import Draft7Validator from nmdc_schema.nmdc_schema_accepting_legacy_ids import Database as NMDCDatabase from nmdc_schema.get_nmdc_view import ViewGetter -from pydantic import conint, BaseModel +from pydantic import Field, BaseModel from pymongo.database import Database as MongoDatabase from pymongo.errors import OperationFailure from toolz import merge, unique from nmdc_runtime.api.core.util import sha256hash_from_file from nmdc_runtime.api.models.object import DrsObjectIn +from typing_extensions import Annotated @lru_cache @@ -354,7 +355,7 @@ class UpdateStatement(BaseModel): class DeleteStatement(BaseModel): q: dict - limit: conint(ge=0, le=1) = 1 + limit: Annotated[int, Field(ge=0, le=1)] = 1 class OverlayDBError(Exception): diff --git a/requirements/dev.txt b/requirements/dev.txt index ab707734..029c5a12 100644 --- a/requirements/dev.txt +++ b/requirements/dev.txt @@ -9,7 +9,7 @@ attrs==23.1.0 # -c requirements/main.txt # cattrs # requests-cache -black==23.9.1 +black==23.10.1 # via # -c requirements/main.txt # -r requirements/dev.in @@ -23,7 +23,7 @@ certifi==2023.7.22 # via # -c requirements/main.txt # requests -charset-normalizer==3.2.0 +charset-normalizer==3.3.1 # via # -c requirements/main.txt # requests @@ -32,7 +32,7 @@ click==8.1.7 # -c requirements/main.txt # black # pip-tools -coverage==7.3.1 +coverage==7.3.2 # via # -r requirements/dev.in # pytest-cov @@ -84,7 +84,7 @@ mypy-extensions==1.0.0 # black nh3==0.2.14 # via readme-renderer -packaging==23.1 +packaging==23.2 # via # -c requirements/main.txt # black @@ -99,7 +99,7 @@ pip-tools==7.3.0 # via -r requirements/dev.in pkginfo==1.9.6 # via twine -platformdirs==3.10.0 +platformdirs==3.11.0 # via # -c requirements/main.txt # black @@ -108,7 +108,7 @@ pluggy==1.3.0 # via # -c requirements/main.txt # pytest -pycodestyle==2.11.0 +pycodestyle==2.11.1 # via flake8 pyflakes==3.1.0 # via @@ -121,13 +121,13 @@ pygments==2.16.1 # rich pyproject-hooks==1.0.0 # via build -pytest==7.4.2 +pytest==7.4.3 # via # -c requirements/main.txt # -r requirements/dev.in # pytest-asyncio # pytest-cov -pytest-asyncio==0.21.1 +pytest-asyncio==0.22.0 # via -r requirements/dev.in pytest-cov==4.1.0 # via -r requirements/dev.in @@ -152,9 +152,9 @@ requests-toolbelt==0.10.1 # twine rfc3986==2.0.0 # via twine -rich==13.5.3 +rich==13.6.0 # via twine -setuptools-scm==8.0.3 +setuptools-scm==8.0.4 # via -r requirements/dev.in six==1.16.0 # via @@ -183,13 +183,13 @@ url-normalize==1.4.3 # via # -c requirements/main.txt # requests-cache -urllib3==1.26.16 +urllib3==1.26.18 # via # -c requirements/main.txt # requests # requests-cache # twine -wheel==0.41.2 +wheel==0.41.3 # via pip-tools zipp==3.17.0 # via @@ -197,7 +197,7 @@ zipp==3.17.0 # importlib-metadata # The following packages are considered to be unsafe in a requirements file: -pip==23.2.1 +pip==23.3.1 # via # -r requirements/dev.in # pip-tools diff --git a/requirements/main.in b/requirements/main.in index 25e6d3a6..487c608e 100644 --- a/requirements/main.in +++ b/requirements/main.in @@ -9,7 +9,7 @@ dagster-graphql dagster-postgres dependency-injector dotted-dict -fastapi>=0.85.0 # using starlette >=0.20.3 for working colon-containing URL paths. +fastapi>=0.104.1 # Pins Swagger UI version to 5.9.0 temporarily to handle a bug crashing it in 5.9.1 fastjsonschema fnc frozendict diff --git a/requirements/main.txt b/requirements/main.txt index bd3164a3..b2ae0d97 100644 --- a/requirements/main.txt +++ b/requirements/main.txt @@ -6,10 +6,12 @@ # alabaster==0.7.13 # via sphinx -alembic==1.12.0 +alembic==1.12.1 # via dagster aniso8601==9.0.1 # via graphene +annotated-types==0.6.0 + # via pydantic antlr4-python3-runtime==4.9.3 # via # linkml @@ -29,9 +31,9 @@ argon2-cffi==23.1.0 # via jupyter-server argon2-cffi-bindings==21.2.0 # via argon2-cffi -arrow==1.2.3 +arrow==1.3.0 # via isoduration -asttokens==2.4.0 +asttokens==2.4.1 # via stack-data async-lru==2.0.4 # via jupyterlab @@ -43,33 +45,31 @@ attrs==23.1.0 # requests-cache autoflake==2.2.1 # via shed -babel==2.12.1 +babel==2.13.1 # via # jupyterlab-server # mkdocs-material # sphinx -backcall==0.2.0 - # via ipython backoff==2.2.1 # via gql base32-lib==1.0.2 # via -r requirements/main.in bcrypt==4.0.1 # via passlib -beanie==1.22.6 +beanie==1.23.1 # via -r requirements/main.in beautifulsoup4==4.12.2 # via # -r requirements/main.in # mkdocs-mermaid2-plugin # nbconvert -black==23.9.1 +black==23.10.1 # via shed -bleach==6.0.0 +bleach==6.1.0 # via nbconvert -boto3==1.28.57 +boto3==1.28.74 # via -r requirements/main.in -botocore==1.31.57 +botocore==1.31.74 # via # boto3 # s3transfer @@ -87,7 +87,7 @@ chardet==5.2.0 # via # pyshex # pyshexc -charset-normalizer==3.2.0 +charset-normalizer==3.3.1 # via requests click==8.1.7 # via @@ -117,29 +117,29 @@ comm==0.1.4 # via # ipykernel # ipywidgets -croniter==1.4.1 +croniter==2.0.1 # via dagster -cryptography==41.0.4 +cryptography==41.0.5 # via python-jose -curies==0.6.4 +curies==0.6.7 # via linkml-runtime -dagit==1.4.17 +dagit==1.5.5 # via -r requirements/main.in -dagster==1.4.17 +dagster==1.5.5 # via # -r requirements/main.in # dagster-graphql # dagster-postgres # dagster-webserver -dagster-ext-process==1.4.17 - # via dagster -dagster-graphql==1.4.17 +dagster-graphql==1.5.5 # via # -r requirements/main.in # dagster-webserver -dagster-postgres==0.20.17 +dagster-pipes==1.5.5 + # via dagster +dagster-postgres==0.21.5 # via -r requirements/main.in -dagster-webserver==1.4.17 +dagster-webserver==1.5.5 # via dagit debugpy==1.8.0 # via ipykernel @@ -165,7 +165,7 @@ ecdsa==0.18.0 # via python-jose editorconfig==0.12.3 # via jsbeautifier -email-validator==2.0.0.post2 +email-validator==2.1.0.post1 # via pydantic et-xmlfile==1.1.0 # via openpyxl @@ -175,11 +175,11 @@ exceptiongroup==1.1.3 # cattrs # ipython # pytest -executing==1.2.0 +executing==2.0.1 # via stack-data -fastapi==0.103.2 +fastapi==0.104.1 # via -r requirements/main.in -fastjsonschema==2.18.0 +fastjsonschema==2.18.1 # via # -r requirements/main.in # nbformat @@ -189,14 +189,16 @@ fqdn==1.5.1 # via jsonschema frozendict==2.3.8 # via -r requirements/main.in -fsspec==2023.9.2 +fsspec==2023.10.0 # via universal-pathlib ghp-import==2.1.0 # via mkdocs git-root==0.1 # via -r requirements/main.in gql==3.4.1 - # via dagster-graphql + # via + # dagster-graphql + # gql graphene==3.3 # via dagster-graphql graphql-core==3.2.3 @@ -210,11 +212,11 @@ graphviz==0.20.1 # via linkml greenlet==2.0.1 # via prefixmaps -grpcio==1.58.0 +grpcio==1.59.2 # via # dagster # grpcio-health-checking -grpcio-health-checking==1.58.0 +grpcio-health-checking==1.59.2 # via dagster h11==0.14.0 # via uvicorn @@ -223,7 +225,7 @@ hbreader==0.9.1 # jsonasobj2 # linkml # linkml-runtime -httptools==0.6.0 +httptools==0.6.1 # via uvicorn humanfriendly==10.0 # via coloredlogs @@ -240,14 +242,14 @@ importlib-metadata==6.8.0 # via prefixmaps iniconfig==2.0.0 # via pytest -ipykernel==6.25.2 +ipykernel==6.26.0 # via # jupyter # jupyter-console # jupyterlab # mkdocs-jupyter # qtconsole -ipython==8.15.0 +ipython==8.17.2 # via # ipykernel # ipywidgets @@ -264,7 +266,7 @@ isoduration==20.11.0 # via jsonschema isort==5.12.0 # via shed -jedi==0.19.0 +jedi==0.19.1 # via ipython jinja2==3.1.2 # via @@ -308,8 +310,9 @@ jsonpointer==2.4 # via # jsonpatch # jsonschema -jsonschema==4.19.1 +jsonschema==4.19.2 # via + # jsonschema # jupyter-events # jupyterlab-server # linkml @@ -319,7 +322,7 @@ jsonschema-specifications==2023.7.1 # via jsonschema jupyter==1.0.0 # via -r requirements/main.in -jupyter-client==8.3.1 +jupyter-client==8.5.0 # via # ipykernel # jupyter-console @@ -328,7 +331,7 @@ jupyter-client==8.3.1 # qtconsole jupyter-console==6.6.3 # via jupyter -jupyter-core==5.3.2 +jupyter-core==5.5.0 # via # ipykernel # jupyter-client @@ -339,11 +342,11 @@ jupyter-core==5.3.2 # nbconvert # nbformat # qtconsole -jupyter-events==0.7.0 +jupyter-events==0.8.0 # via jupyter-server jupyter-lsp==2.2.0 # via jupyterlab -jupyter-server==2.7.3 +jupyter-server==2.9.1 # via # jupyter-lsp # jupyterlab @@ -352,7 +355,7 @@ jupyter-server==2.7.3 # notebook-shim jupyter-server-terminals==0.4.4 # via jupyter-server -jupyterlab==4.0.6 +jupyterlab==4.0.7 # via # -r requirements/main.in # notebook @@ -368,9 +371,9 @@ jupytext==1.15.2 # via mkdocs-jupyter lazy-model==0.2.0 # via beanie -libcst==1.0.1 +libcst==1.1.0 # via shed -linkml==1.5.8 +linkml==1.6.1 # via # -r requirements/main.in # nmdc-schema @@ -384,7 +387,7 @@ linkml-runtime==1.6.0 # nmdc-schema mako==1.2.4 # via alembic -markdown==3.4.4 +markdown==3.5 # via # mkdocs # mkdocs-material @@ -409,20 +412,20 @@ mdurl==0.1.2 # via markdown-it-py mergedeep==1.3.4 # via mkdocs -mistune==3.0.1 +mistune==3.0.2 # via nbconvert mkdocs==1.5.3 # via # mkdocs-jupyter # mkdocs-material # mkdocs-mermaid2-plugin -mkdocs-jupyter==0.24.5 +mkdocs-jupyter==0.24.6 # via -r requirements/main.in -mkdocs-material==9.4.2 +mkdocs-material==9.4.7 # via # -r requirements/main.in # mkdocs-jupyter -mkdocs-material-extensions==1.2 +mkdocs-material-extensions==1.3 # via mkdocs-material mkdocs-mermaid2-plugin==1.1.1 # via -r requirements/main.in @@ -438,7 +441,7 @@ mypy-extensions==1.0.0 # typing-inspect nbclient==0.8.0 # via nbconvert -nbconvert==7.8.0 +nbconvert==7.10.0 # via # jupyter # jupyter-server @@ -453,13 +456,13 @@ nest-asyncio==1.5.8 # via ipykernel nmdc-schema==8.0.0 # via -r requirements/main.in -notebook==7.0.4 +notebook==7.0.6 # via jupyter notebook-shim==0.2.3 # via # jupyterlab # notebook -numpy==1.26.0 +numpy==1.26.1 # via pandas numpydoc==1.6.0 # via terminusdb-client @@ -469,7 +472,7 @@ openpyxl==3.1.2 # linkml overrides==7.4.0 # via jupyter-server -packaging==23.1 +packaging==23.2 # via # black # dagster @@ -485,7 +488,7 @@ packaging==23.1 # sphinx paginate==0.5.6 # via mkdocs-material -pandas==2.1.1 +pandas==2.1.2 # via -r requirements/main.in pandocfilters==1.5.0 # via nbconvert @@ -503,9 +506,7 @@ pendulum==2.1.2 # via dagster pexpect==4.8.0 # via ipython -pickleshare==0.7.5 - # via ipython -platformdirs==3.10.0 +platformdirs==3.11.0 # via # black # jupyter-core @@ -523,19 +524,19 @@ prefixmaps==0.1.5 # via # linkml # linkml-runtime -prometheus-client==0.17.1 +prometheus-client==0.18.0 # via jupyter-server prompt-toolkit==3.0.39 # via # ipython # jupyter-console -protobuf==4.24.3 +protobuf==4.24.4 # via # dagster # grpcio-health-checking -psutil==5.9.5 +psutil==5.9.6 # via ipykernel -psycopg2-binary==2.9.8 +psycopg2-binary==2.9.9 # via dagster-postgres ptyprocess==0.7.0 # via @@ -549,7 +550,7 @@ pyasn1==0.5.0 # rsa pycparser==2.21 # via cffi -pydantic==1.10.13 +pydantic==2.4.2 # via # -r requirements/main.in # beanie @@ -559,6 +560,9 @@ pydantic==1.10.13 # lazy-model # linkml # linkml-runtime + # pydantic +pydantic-core==2.10.1 + # via pydantic pyflakes==3.1.0 # via autoflake pygments==2.16.1 @@ -575,7 +579,7 @@ pyjsg==0.11.10 # linkml # pyshexc # shexjsg -pymdown-extensions==10.3 +pymdown-extensions==10.3.1 # via # mkdocs-material # mkdocs-mermaid2-plugin @@ -591,7 +595,7 @@ pyshexc==0.9.1 # via # linkml # pyshex -pytest==7.4.2 +pytest==7.4.3 # via pytest-logging pytest-logging==2015.11.4 # via prefixcommons @@ -620,11 +624,12 @@ pytrie==0.4.0 # via curies pytz==2023.3.post1 # via + # croniter # dagster # pandas pytzdata==2020.1 # via pendulum -pyupgrade==3.13.0 +pyupgrade==3.15.0 # via shed pyyaml==6.0.1 # via @@ -653,7 +658,7 @@ pyzmq==25.1.1 # qtconsole qtconsole==5.4.4 # via jupyter -qtpy==2.4.0 +qtpy==2.4.1 # via qtconsole rdflib==7.0.0 # via @@ -676,7 +681,7 @@ referencing==0.30.2 # jsonschema # jsonschema-specifications # jupyter-events -regex==2023.8.8 +regex==2023.10.3 # via mkdocs-material requests==2.31.0 # via @@ -710,19 +715,19 @@ rfc3986-validator==0.1.1 # jupyter-events rfc3987==1.3.8 # via jsonschema -rpds-py==0.10.3 +rpds-py==0.10.6 # via # jsonschema # referencing rsa==4.9 # via python-jose -ruamel-yaml==0.17.33 +ruamel-yaml==0.18.3 # via linkml-dataops -ruamel-yaml-clib==0.2.7 +ruamel-yaml-clib==0.2.8 # via ruamel-yaml s3transfer==0.7.0 # via boto3 -semver==3.0.1 +semver==3.0.2 # via -r requirements/main.in send2trash==1.8.2 # via jupyter-server @@ -778,12 +783,12 @@ sphinxcontrib-qthelp==1.0.6 # via sphinx sphinxcontrib-serializinghtml==1.1.9 # via sphinx -sqlalchemy==2.0.21 +sqlalchemy==2.0.22 # via # alembic # dagster # linkml -stack-data==0.6.2 +stack-data==0.6.3 # via ipython starlette==0.27.0 # via @@ -835,7 +840,7 @@ tqdm==4.66.1 # -r requirements/main.in # dagster # terminusdb-client -traitlets==5.10.1 +traitlets==5.13.0 # via # comm # ipykernel @@ -854,6 +859,8 @@ traitlets==5.10.1 # qtconsole typeguard==2.13.3 # via terminusdb-client +types-python-dateutil==2.8.19.14 + # via arrow typing-extensions==4.8.0 # via # alembic @@ -866,6 +873,7 @@ typing-extensions==4.8.0 # libcst # prefixmaps # pydantic + # pydantic-core # sqlalchemy # typing-inspect # uvicorn @@ -873,13 +881,13 @@ typing-inspect==0.9.0 # via libcst tzdata==2023.3 # via pandas -universal-pathlib==0.1.3 +universal-pathlib==0.1.4 # via dagster uri-template==1.3.0 # via jsonschema url-normalize==1.4.3 # via requests-cache -urllib3==1.26.16 +urllib3==1.26.18 # via # botocore # gql @@ -890,16 +898,16 @@ uvicorn==0.23.2 # via # -r requirements/main.in # dagster-webserver -uvloop==0.17.0 +uvloop==0.19.0 # via uvicorn watchdog==3.0.0 # via # dagster # linkml # mkdocs -watchfiles==0.20.0 +watchfiles==0.21.0 # via uvicorn -wcwidth==0.2.7 +wcwidth==0.2.9 # via prompt-toolkit webcolors==1.13 # via jsonschema @@ -907,9 +915,9 @@ webencodings==0.5.1 # via # bleach # tinycss2 -websocket-client==1.6.3 +websocket-client==1.6.4 # via jupyter-server -websockets==11.0.3 +websockets==12.0 # via uvicorn widgetsnbextension==4.0.9 # via ipywidgets @@ -917,7 +925,7 @@ wrapt==1.15.0 # via deprecated xlrd==2.0.1 # via -r requirements/main.in -xlsxwriter==3.1.5 +xlsxwriter==3.1.9 # via -r requirements/main.in yarl==1.9.2 # via gql diff --git a/tests/files/nmdc_bsm-12-7mysck21.json b/tests/files/nmdc_bsm-12-7mysck21.json new file mode 100644 index 00000000..d0571f47 --- /dev/null +++ b/tests/files/nmdc_bsm-12-7mysck21.json @@ -0,0 +1,48 @@ +{ + "analysis_type": [ + "metagenomics" + ], + "biosample_categories": [ + "NEON" + ], + "collection_date": { + "has_raw_value": "2014-07-15T18:00Z" + }, + "depth": { + "has_maximum_numeric_value": 1, + "has_minimum_numeric_value": 0, + "has_unit": "meters" + }, + "elev": 1179.5, + "env_broad_scale": { + "term": { + "id": "ENVO:01000253", + "name": "freshwater river biome" + } + }, + "env_local_scale": { + "term": { + "id": "ENVO:03600095", + "name": "stream run" + } + }, + "env_medium": { + "term": { + "id": "ENVO:01001057", + "name": "environment associated with a plant part or small plant" + } + }, + "geo_loc_name": { + "has_raw_value": "USA: Colorado, Arikaree River" + }, + "id": "nmdc:bsm-12-7mysck21", + "lat_lon": { + "latitude": 39.758206, + "longitude": -102.447148 + }, + "name": "ARIK.20140715.AMC.EPIPHYTON.5", + "part_of": [ + "nmdc:sty-11-34xj1150" + ], + "type": "nmdc:Biosample" +} diff --git a/tests/files/nmdc_sty-11-pzmd0x14.json b/tests/files/nmdc_sty-11-pzmd0x14.json new file mode 100644 index 00000000..114437c0 --- /dev/null +++ b/tests/files/nmdc_sty-11-pzmd0x14.json @@ -0,0 +1,65 @@ +{ + "id": "nmdc:sty-11-pzmd0x14", + "name": "National Ecological Observatory Network: benthic metagenomes (DP1.20279.001)", + "type": "nmdc:Study", + "title": "National Ecological Observatory Network: benthic metagenomes (DP1.20279.001)", + "description": "The National Science Foundation's National Ecological Observatory Network (NEON) is a continental-scale observation facility operated by Battelle and designed to collect long-term open access ecological data to better understand how U.S. ecosystems are changing.", + "websites": [ + "https://www.neonscience.org/", + "https://data.neonscience.org/data-products/DP1.20279.001", + "https://data.neonscience.org/api/v0/documents/NEON_metagenomes_userGuide_vE.pdf" + ], + "funding_sources": [ + "NSF#1724433 National Ecological Observatory Network: Operations Activities" + ], + "principal_investigator": { + "name": "Kate Thibault", + "email": "kthibault@battelleecology.org", + "orcid": "orcid:0000-0003-3477-6424", + "has_raw_value": "Kate Thibault" + }, + "has_credit_associations": [ + { + "applies_to_person": { + "name": "Hugh Cross", + "email": "crossh@battelleecology.org", + "orcid": "orcid:0000-0002-6745-9479" + }, + "applied_roles": [ + "Methodology", + "Data curation" + ] + }, + { + "applies_to_person": { + "name": "Kate Thibault", + "email": "kthibault@battelleecology.org", + "orcid": "orcid:0000-0003-3477-6424" + }, + "applied_roles": [ + "Principal Investigator" + ] + }, + { + "applies_to_person": { + "name": "Stephanie Parker", + "email": "sparker@battelleecology.org", + "orcid": "0000-0002-7180-7245" + }, + "applied_roles": [ + "Methodology", + "Data curation" + ] + } + ], + "study_image": [ + { + "url": "https://portal.nersc.gov/project/m3408/profile_images/nmdc_sty-11-34xj1150.jpg" + } + ], + "gold_study_identifiers": [], + "part_of": [ + "nmdc:sty-11-nxrz9m96" + ], + "study_category": "consortium" +} diff --git a/tests/integration/test_minter_repository.py b/tests/integration/test_minter_repository.py index 96199670..45ad0b56 100644 --- a/tests/integration/test_minter_repository.py +++ b/tests/integration/test_minter_repository.py @@ -29,7 +29,12 @@ def test_mint_and_resolve(): s: InMemoryIDStore = get_test_inmemoryidstore() req_mint = minting_request() id_: Identifier = next(i for i in s.mint(req_mint)) - req_res = ResolutionRequest(id_name=id_.name, **req_mint.dict()) + req_res = ResolutionRequest( + id_name=id_.name, + **req_mint.model_dump( + mode="json", + ), + ) assert s.resolve(req_res) is not None @@ -37,9 +42,23 @@ def test_mint_and_delete(): s: InMemoryIDStore = get_test_inmemoryidstore() req_mint = minting_request() id_: Identifier = next(i for i in s.mint(req_mint)) - req_del = DeleteRequest(id_name=id_.name, **req_mint.dict()) + req_del = DeleteRequest( + id_name=id_.name, + **req_mint.model_dump( + mode="json", + ), + ) s.delete(req_del) - assert s.resolve(ResolutionRequest(**req_del.dict())) is None + assert ( + s.resolve( + ResolutionRequest( + **req_del.model_dump( + mode="json", + ) + ) + ) + is None + ) def test_mongo_mint_one(): @@ -70,7 +89,12 @@ def test_mongo_mint_and_resolve(): req_mint = minting_request() id_: Identifier = next(i for i in s.mint(req_mint)) - req_res = ResolutionRequest(id_name=id_.name, **req_mint.dict()) + req_res = ResolutionRequest( + id_name=id_.name, + **req_mint.model_dump( + mode="json", + ), + ) assert s.resolve(req_res) is not None @@ -80,7 +104,21 @@ def test_mongo_mint_and_delete(): req_mint = minting_request() id_: Identifier = next(i for i in s.mint(req_mint)) - req_del = DeleteRequest(id_name=id_.name, **req_mint.dict()) + req_del = DeleteRequest( + id_name=id_.name, + **req_mint.model_dump( + mode="json", + ), + ) s.delete(req_del) - assert s.resolve(ResolutionRequest(**req_del.dict())) is None + assert ( + s.resolve( + ResolutionRequest( + **req_del.model_dump( + mode="json", + ) + ) + ) + is None + ) assert s.db["minter.id_records"].count_documents({}) == 0 diff --git a/tests/test_api/test_endpoints.py b/tests/test_api/test_endpoints.py index 1dd677cc..387154b0 100644 --- a/tests/test_api/test_endpoints.py +++ b/tests/test_api/test_endpoints.py @@ -1,4 +1,6 @@ +import json import os +import re import pytest import requests @@ -7,13 +9,17 @@ from toolz import get_in from nmdc_runtime.api.core.auth import get_password_hash +from nmdc_runtime.api.core.metadata import df_from_sheet_in, _validate_changesheet from nmdc_runtime.api.core.util import generate_secret, dotted_path_for from nmdc_runtime.api.db.mongo import get_mongo_db +from nmdc_runtime.api.endpoints.util import persist_content_and_get_drs_object from nmdc_runtime.api.models.job import Job, JobOperationMetadata +from nmdc_runtime.api.models.metadata import ChangesheetIn from nmdc_runtime.api.models.site import SiteInDB, SiteClientInDB from nmdc_runtime.api.models.user import UserInDB, UserIn, User from nmdc_runtime.site.repository import run_config_frozen__normal_env from nmdc_runtime.site.resources import get_mongo, RuntimeApiSiteClient +from nmdc_runtime.util import REPO_ROOT_DIR def ensure_test_resources(mdb): @@ -26,7 +32,7 @@ def ensure_test_resources(mdb): username=username, hashed_password=get_password_hash(password), site_admin=[site_id], - ).dict(exclude_unset=True), + ).model_dump(mode="json", exclude_unset=True), upsert=True, ) @@ -42,7 +48,9 @@ def ensure_test_resources(mdb): hashed_secret=get_password_hash(client_secret), ) ], - ).dict(), + ).model_dump( + mode="json", + ), upsert=True, ) wf_id = "test" @@ -50,7 +58,9 @@ def ensure_test_resources(mdb): prev_ops = {"metadata.job.id": job_id, "metadata.site_id": site_id} mdb.operations.delete_many(prev_ops) job = Job(**{"id": job_id, "workflow": {"id": wf_id}, "config": {}, "claims": []}) - mdb.jobs.replace_one({"id": job_id}, job.dict(exclude_unset=True), upsert=True) + mdb.jobs.replace_one( + {"id": job_id}, job.model_dump(mode="json", exclude_unset=True), upsert=True + ) return { "site_client": { "site_id": site_id, @@ -58,7 +68,7 @@ def ensure_test_resources(mdb): "client_secret": client_secret, }, "user": {"username": username, "password": password}, - "job": job.dict(exclude_unset=True), + "job": job.model_dump(mode="json", exclude_unset=True), } @@ -114,7 +124,7 @@ def get_token(): "POST", url=(base_url + "/users"), headers=headers, - json=user_in.dict(exclude_unset=True), + json=user_in.model_dump(mode="json", exclude_unset=True), ) try: @@ -181,3 +191,41 @@ def test_metadata_validate_json_with_unknown_collection(api_site_client): {"studi_set": []}, ) assert rv.json()["result"] == "errors" + + +def test_submit_changesheet(): + sheet_in = ChangesheetIn( + name="sheet", + content_type="text/tab-separated-values", + text="id\taction\tattribute\tvalue\nnmdc:bsm-12-7mysck21\tupdate\tpart_of\tnmdc:sty-11-pzmd0x14\n", + ) + mdb = get_mongo_db() + rs = ensure_test_resources(mdb) + if not mdb.biosample_set.find_one({"id": "nmdc:bsm-12-7mysck21"}): + mdb.biosample_set.insert_one( + json.loads( + ( + REPO_ROOT_DIR / "tests" / "files" / "nmdc_bsm-12-7mysck21.json" + ).read_text() + ) + ) + if not mdb.study_set.find_one({"id": "nmdc:sty-11-pzmd0x14"}): + mdb.study_set.insert_one( + json.loads( + ( + REPO_ROOT_DIR / "tests" / "files" / "nmdc_sty-11-pzmd0x14.json" + ).read_text() + ) + ) + df_change = df_from_sheet_in(sheet_in, mdb) + _ = _validate_changesheet(df_change, mdb) + drs_obj_doc = persist_content_and_get_drs_object( + content=sheet_in.text, + username=rs["user"]["username"], + filename=re.sub(r"[^A-Za-z0-9._\-]", "_", sheet_in.name), + content_type=sheet_in.content_type, + description="changesheet", + id_ns="changesheets", + ) + mdb.objects.delete_one({"id": drs_obj_doc["id"]}) + assert True diff --git a/tests/test_api/test_metadata.py b/tests/test_api/test_metadata.py index 9fc63254..82b6e70f 100644 --- a/tests/test_api/test_metadata.py +++ b/tests/test_api/test_metadata.py @@ -7,6 +7,8 @@ import pytest from nmdc_runtime.api.db.mongo import get_mongo_db +from nmdc_runtime.api.endpoints.util import persist_content_and_get_drs_object +from nmdc_runtime.api.models.metadata import ChangesheetIn from nmdc_runtime.util import get_nmdc_jsonschema_dict from toolz import dissoc @@ -15,6 +17,8 @@ update_mongo_db, mongo_update_command_for, copy_docs_in_update_cmd, + df_from_sheet_in, + _validate_changesheet, ) from nmdc_runtime.site.ops import ensure_data_object_type from nmdc_runtime.site.repository import run_config_frozen__normal_env diff --git a/tests/test_data/conftest.py b/tests/test_data/conftest.py index 331183bd..04781788 100644 --- a/tests/test_data/conftest.py +++ b/tests/test_data/conftest.py @@ -1,17 +1,23 @@ +import string + import pytest -import uuid import random +from nmdc_runtime.minter.config import typecodes + @pytest.fixture def test_minter(): + typecode_list = typecodes() + def mint(type, how_many=1): + typecode = next(t for t in typecode_list if t["schema_class"] == type) return [ - "fake:" - + str( - uuid.UUID( - bytes=bytes(random.getrandbits(8) for _ in range(16)), version=4 - ) + "nmdc:" + + typecode["name"] + + "-00-" + + "".join( + random.choice(string.ascii_lowercase + string.digits) for _ in range(8) ) for _ in range(how_many) ] diff --git a/tests/test_data/test_submission_portal_translator.py b/tests/test_data/test_submission_portal_translator.py index ec9b7182..533455e7 100644 --- a/tests/test_data/test_submission_portal_translator.py +++ b/tests/test_data/test_submission_portal_translator.py @@ -1,12 +1,18 @@ +import datetime from pathlib import Path import random import yaml +from linkml_runtime.dumpers import json_dumper + from nmdc_runtime.site.translation.submission_portal_translator import ( SubmissionPortalTranslator, ) from nmdc_schema import nmdc +from nmdc_runtime.util import validate_json +from tests.conftest import get_mongo_test_db + def test_get_pi(): translator = SubmissionPortalTranslator() @@ -31,7 +37,7 @@ def test_get_doi(): translator = SubmissionPortalTranslator() doi = translator._get_doi({"contextForm": {"datasetDoi": "1234"}}) assert doi is not None - assert doi.has_raw_value == "1234" + assert doi == ["1234"] doi = translator._get_doi({"contextForm": {"datasetDoi": ""}}) assert doi is None @@ -234,14 +240,32 @@ def test_get_from(): assert translator._get_from(metadata, ["one", "some_empty"]) == ["one", "three"] -def test_get_dataset(test_minter): - random.seed(0) +def test_get_dataset(test_minter, monkeypatch): + # OmicsProcess objects have an add_date and a mod_date slot that are populated with the + # current date. In order to compare with a static expected output we need to patch + # the datetime.now() call to return a predefined date. + the_time = datetime.datetime(2023, 10, 17, 9, 0, 0) + + class FrozenDatetime(datetime.datetime): + @classmethod + def now(cls, **kwargs): + return the_time + + monkeypatch.setattr( + "nmdc_runtime.site.translation.submission_portal_translator.datetime", + FrozenDatetime, + ) + + mongo_db = get_mongo_test_db() with open( Path(__file__).parent / "test_submission_portal_translator_data.yaml" ) as f: test_datasets = yaml.safe_load_all(f) for test_data in test_datasets: + # Reset the random number seed here so that fake IDs generated by the `test_minter` + # fixture are stable across test runs + random.seed(0) translator = SubmissionPortalTranslator( **test_data["input"], id_minter=test_minter ) @@ -249,3 +273,6 @@ def test_get_dataset(test_minter): expected = nmdc.Database(**test_data["output"]) actual = translator.get_database() assert actual == expected + + validation_result = validate_json(json_dumper.to_dict(actual), mongo_db) + assert validation_result == {"result": "All Okay!"} diff --git a/tests/test_data/test_submission_portal_translator_data.yaml b/tests/test_data/test_submission_portal_translator_data.yaml index b7562096..779a9d46 100644 --- a/tests/test_data/test_submission_portal_translator_data.yaml +++ b/tests/test_data/test_submission_portal_translator_data.yaml @@ -4,7 +4,7 @@ input: metadata_submission: packageName: plant-associated contextForm: - datasetDoi: 10.46936/10.25585/60000818 + datasetDoi: doi:10.46936/10.25585/60000818 dataGenerated: true facilityGenerated: true facilities: [] @@ -287,12396 +287,20 @@ input: ecosystem_subtype: Leaf ecosystem_category: Terrestrial specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_MAIN_09MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:c54a1438-713a-4b6f-9e44-ecddbd27e974 - ecosystem_type: Plant-associated - collection_date: '2016-05-09' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_MAIN_09MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:8e0225d6-f7a0-469b-a747-8f5f4d65dc69 - ecosystem_type: Plant-associated - collection_date: '2016-05-09' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_NF_09MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:1d20602f-3a0a-4d58-96cf-16135467ba14 - ecosystem_type: Plant-associated - collection_date: '2016-05-09' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_NF_09MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:f13b1234-886c-4f8f-9663-850f5daff8e1 - ecosystem_type: Plant-associated - collection_date: '2016-05-09' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_NF_09MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:45c11d1c-4a00-4162-9cdb-1020966507c6 - ecosystem_type: Plant-associated - collection_date: '2016-05-09' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_NF_09MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:76a6a11e-5e25-4270-8d0d-1701bd12517a - ecosystem_type: Plant-associated - collection_date: '2016-05-09' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_MAIN_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:bac125d1-f295-4728-a7fd-e4911a985b44 - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_MAIN_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:13d073fa-b45a-4e47-a570-71a8a5726ac7 - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_MAIN_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:7a7c2686-18fc-4a3c-8c2c-e2a195cd0a28 - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_MAIN_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:7325ce99-4347-4728-b5aa-dda21a760a07 - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_NF_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:8a7956e3-0f51-4e60-8aa0-380285878c86 - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_NF_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:df9a0e6b-28c6-490b-aae9-559126dcd31a - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_NF_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:f1d3e678-eaa9-4e36-ae17-c8bed8133825 - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_NF_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:d43c6831-cafe-4674-9e56-adf20da087f6 - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_MAIN_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:a2e9ab67-4112-447e-82a1-2c674769ef3e - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_MAIN_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:1083f373-69b8-4ca1-9f5e-406d34781d9d - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_MAIN_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:20ec38cc-8e1d-4b16-a08a-5e75881701d5 - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_MAIN_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:f408f2c4-5c6f-43b1-b1d5-dc264317f826 - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_NF_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:78c5bfe7-2e39-4419-aae5-cc60ac5c6b80 - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_NF_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:4bcd56e0-dc05-46f4-b93c-2c548ffd0f48 - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_NF_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:090aa36b-b82e-4ff4-9c01-b3de17bd7720 - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_NF_31MAY2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:03aaf489-f1cc-43e4-b537-9cfd2d5fe7b6 - ecosystem_type: Plant-associated - collection_date: '2016-05-31' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_MAIN_20JUN2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:b16cb1c2-def5-45b3-aeee-1de1762fac8c - ecosystem_type: Plant-associated - collection_date: '2016-06-20' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_MAIN_20JUN2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:7635e9bf-db34-4211-abb3-53df9119fdfa - ecosystem_type: Plant-associated - collection_date: '2016-06-20' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_MAIN_20JUN2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:3558ef40-a322-4ea0-89c3-afb0cfba3199 - ecosystem_type: Plant-associated - collection_date: '2016-06-20' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_MAIN_20JUN2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:96c80952-f26a-4014-8ebc-72648e90e2bb - ecosystem_type: Plant-associated - collection_date: '2016-06-20' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_NF_20JUN2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:d0b85994-73f5-43f0-97c1-ef0ce27cae7f - ecosystem_type: Plant-associated - collection_date: '2016-06-20' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_NF_20JUN2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:0e8e63b0-b2ce-4f4a-af1f-a6242b44a205 - ecosystem_type: Plant-associated - collection_date: '2016-06-20' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_NF_20JUN2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:346b2bf3-3899-44b7-88b7-38cd157a78ac - ecosystem_type: Plant-associated - collection_date: '2016-06-20' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_NF_20JUN2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:0e337fca-5bdc-41b9-9c2c-9c043af02850 - ecosystem_type: Plant-associated - collection_date: '2016-06-20' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_MAIN_20JUN2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:d43031d6-4949-4af4-ab93-0d4a52ddc41b - ecosystem_type: Plant-associated - collection_date: '2016-06-20' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_MAIN_20JUN2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:247e0564-3ba0-4aed-bc73-237038d0f273 - ecosystem_type: Plant-associated - collection_date: '2016-06-20' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_MAIN_20JUN2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:99841196-4418-47c7-941a-475272baa537 - ecosystem_type: Plant-associated - collection_date: '2016-06-20' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_MAIN_20JUN2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:71ce7bb9-1267-4cfd-9437-42cac3175456 - ecosystem_type: Plant-associated - collection_date: '2016-06-20' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_NF_20JUN2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:7908e2ad-6c33-40ec-b00a-0b054560e5e3 - ecosystem_type: Plant-associated - collection_date: '2016-06-20' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_NF_20JUN2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:5efa5fcd-8ad5-488c-9684-91a2c5dfeb21 - ecosystem_type: Plant-associated - collection_date: '2016-06-20' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_NF_20JUN2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - 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specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_MAIN_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:95f249ad-1b54-4c8f-900e-c2abf32e3836 - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_MAIN_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:b7f2fece-413f-43ea-83f3-80c01fc218c1 - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_MAIN_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:dae06229-433f-45fd-a2ef-d82712dcb14d - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_MAIN_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:6a50b37a-10fc-4370-b2eb-c4ba33685a9e - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_NF_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:99d5ad42-73d2-4eaa-a603-63e3e823ba8c - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_NF_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:80fe230b-e255-4df6-875a-51dae2bfc222 - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_NF_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:f1e2af4b-e345-4878-9cc9-b24e1007c85f - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_NF_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:4a9a58de-6cb1-489d-95a6-86df4adffb23 - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_MAIN_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:9f55830a-9871-4a8a-b872-f6b8d5513a65 - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_MAIN_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:cecc6251-2151-49e2-9f55-fb5b9409cd4c - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_MAIN_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:79d6bc42-19e6-4cbc-b394-26fff15492e5 - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_MAIN_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:93486fde-e381-4aac-86eb-2387dd44f138 - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_NF_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:7d9c0233-a597-407c-bdad-1c4f79a4cc6e - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_NF_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:f8b5663d-3322-475b-880a-29377f37f346 - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_NF_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:c07f456e-d797-437c-9b79-11e16494e90d - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_NF_12JUL2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:913a098d-20e6-4581-b657-fc07701d5d44 - ecosystem_type: Plant-associated - collection_date: '2016-07-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_MAIN_01AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:726e08ab-b898-4237-961a-ffea7e3a3623 - ecosystem_type: Plant-associated - collection_date: '2016-08-01' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - 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specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_NF_01AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:e1ca31f8-6836-4955-9f68-a9f315a16552 - ecosystem_type: Plant-associated - collection_date: '2016-08-01' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_MAIN_01AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:a8cde33e-b56e-44de-9f37-34e39c1718b7 - ecosystem_type: Plant-associated - collection_date: '2016-08-01' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_MAIN_01AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:21a2b2be-515d-4fbe-a41d-624aff4f8a38 - ecosystem_type: Plant-associated - collection_date: '2016-08-01' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_MAIN_01AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:657ad6ac-4500-4f27-abc6-72deb60d1675 - ecosystem_type: Plant-associated - collection_date: '2016-08-01' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_MAIN_01AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:b4ef37eb-319f-4e9a-aee7-a617a3ff1ce8 - ecosystem_type: Plant-associated - collection_date: '2016-08-01' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_NF_01AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:c612cec1-0592-4304-98a8-58f8a925216c - ecosystem_type: Plant-associated - collection_date: '2016-08-01' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_NF_01AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:602148a4-f4b9-40af-bfab-75228be3ae36 - ecosystem_type: Plant-associated - collection_date: '2016-08-01' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_NF_01AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:94700929-aa94-4ef7-a6a9-0b295b54ddfa - ecosystem_type: Plant-associated - collection_date: '2016-08-01' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_NF_01AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:94afd1d3-9540-489e-b0b7-fc2da34d0417 - ecosystem_type: Plant-associated - collection_date: '2016-08-01' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_MAIN_22AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:824f96a7-9df4-41c9-85e1-a4cea1523f59 - ecosystem_type: Plant-associated - collection_date: '2016-08-22' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_MAIN_22AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:b78f7d73-16a4-4f6c-9bb8-94007fc35202 - ecosystem_type: Plant-associated - collection_date: '2016-08-22' - env_broad_scale: agricultural biome [ENVO:01001442] - 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analysis_type: - - metagenomics - source_mat_id: UUID:08251a0c-f982-4ec6-8c0b-bb0177f3410b - ecosystem_type: Plant-associated - collection_date: '2016-08-22' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_MAIN_22AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:862b862b-e694-4348-a4ba-3b434b67440a - ecosystem_type: Plant-associated - collection_date: '2016-08-22' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_MAIN_22AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:b78cf581-f8e9-4194-aaa4-7062d35298d5 - ecosystem_type: Plant-associated - collection_date: '2016-08-22' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_NF_22AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:53d7d022-896b-4803-b5fc-4003bc023af8 - ecosystem_type: Plant-associated - collection_date: '2016-08-22' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_NF_22AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:63a6d110-3766-4e21-ac0b-62d613c36152 - ecosystem_type: Plant-associated - collection_date: '2016-08-22' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_NF_22AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:ec6a2efb-da59-4b56-98bb-3705b73d3474 - ecosystem_type: Plant-associated - collection_date: '2016-08-22' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_NF_22AUG2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:f5faf681-beb8-4d82-b036-22ca261381b1 - ecosystem_type: Plant-associated - collection_date: '2016-08-22' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_MAIN_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:0a7ccc91-f79d-4ef6-b625-20ee412ca032 - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_MAIN_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:7ec7a3d2-60ac-4c43-829e-a2459351eaf8 - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_MAIN_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:86598228-4d5d-44c1-8a20-c2b384b2d6d1 - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_MAIN_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:f18cbbaa-2f56-492f-8b1e-ab79c76b4d83 - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_NF_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:e2dcb077-16e1-4540-a7a3-261c9492e60c - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_NF_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:1eadb7fb-7168-4b37-a018-8b7928316726 - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_NF_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:17679294-55de-4b9b-86da-9fe3d9fdb890 - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_NF_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:6aa94584-37ae-42cc-af29-31ccd73b56bd - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_MAIN_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:e7b25f00-b6b2-4d22-8c4a-f608fd5474f7 - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_MAIN_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:862a50b3-5d7a-4065-bf3d-6e423b055c99 - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_MAIN_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:a4ad7b54-56fe-49dd-a09d-1a2b369b4f5f - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_MAIN_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:f2e320bd-7868-453d-9850-234c47b72719 - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_NF_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:f6ca2bc7-5573-4512-9bf5-fb389fcbb8ef - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_NF_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:4954c20b-a444-4649-88f8-9e399143d3f5 - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_NF_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:fa0e2a99-040d-4ec6-be7a-fe6d8ba90c5d - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_NF_12SEP2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:c8270368-e522-483f-8190-8c302bcaa140 - ecosystem_type: Plant-associated - collection_date: '2016-09-12' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_MAIN_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:132e3aec-eb1a-438d-bcbc-ca4511fdf2a8 - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_MAIN_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:ad43ccc5-c709-4dac-b598-be10a5bb4217 - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_MAIN_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:a94c0efe-e560-4524-b5d7-8ac1d7a8a153 - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_MAIN_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:c262276b-9011-4a02-8971-ec137979ebf7 - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_NF_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:d53f3e07-9ad2-42a9-ae39-d920129112ac - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_NF_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:f27f0840-4aff-4d94-93b5-e2b30b434927 - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_NF_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:df66adfe-09fe-471c-a900-f3b208341da7 - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_NF_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:b334ad62-f5dc-48d3-b7f0-b89788581244 - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_MAIN_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:cbb88571-b9a9-4876-ad35-ba0b82b41c0d - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_MAIN_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:ee7f1272-14ff-4c20-bed2-dc5528d4f39d - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_MAIN_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:451aad09-d814-4e69-b384-c43aa45e480d - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_MAIN_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:2c9efdf4-68c3-4085-98a4-2c9efc52d1ef - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_NF_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:5f524de7-39f2-4573-b42d-e95c60038304 - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_NF_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:49d025c5-94c3-483b-8004-de6a24a63e68 - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_NF_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:bdf36513-e117-4b18-9847-1207e0b35fd5 - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_NF_03OCT2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:3af2c3f9-5822-4d57-8eea-4cf4f3144219 - ecosystem_type: Plant-associated - collection_date: '2016-10-03' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_MAIN_07NOV2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:d71ed350-917a-4a5b-9c4f-e491ad5df486 - ecosystem_type: Plant-associated - collection_date: '2016-11-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_MAIN_07NOV2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:b0226577-426e-47a0-a57a-14a4b8cb35b5 - ecosystem_type: Plant-associated - collection_date: '2016-11-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_MAIN_07NOV2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:5e45f92d-cb69-4059-be53-09074642e9ab - ecosystem_type: Plant-associated - collection_date: '2016-11-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_MAIN_07NOV2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:423d877e-f692-447f-852b-ca476101c2cd - ecosystem_type: Plant-associated - collection_date: '2016-11-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R1_NF_07NOV2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:bcdd3bb7-f1f3-4336-b7da-0d2153af08f2 - ecosystem_type: Plant-associated - collection_date: '2016-11-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R2_NF_07NOV2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:ce222def-a322-4cd0-9add-618f5abe4688 - ecosystem_type: Plant-associated - collection_date: '2016-11-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R3_NF_07NOV2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:b4a4262e-17fc-4d41-aa7c-c55727a74b25 - ecosystem_type: Plant-associated - collection_date: '2016-11-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G6R4_NF_07NOV2016" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:bd23a3e1-2fee-4023-834a-e4cb9a0571a1 - ecosystem_type: Plant-associated - collection_date: '2016-11-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_MAIN_15MAY2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:037b5f89-42e7-480a-82b9-4b3586890e28 - ecosystem_type: Plant-associated - collection_date: '2017-05-15' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_MAIN_15MAY2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:294adf08-906c-415c-a21e-372facfbda5a - ecosystem_type: Plant-associated - collection_date: '2017-05-15' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_MAIN_15MAY2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:ce94a886-65a2-4c9e-8c65-5a6711ec4551 - ecosystem_type: Plant-associated - collection_date: '2017-05-15' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_MAIN_15MAY2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:5ecc51f9-94a5-4b27-8ef9-27a59d6e8524 - ecosystem_type: Plant-associated - collection_date: '2017-05-15' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_NF_15MAY2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:1fa7ea40-2cf7-49ff-8478-f32239c95f70 - ecosystem_type: Plant-associated - collection_date: '2017-05-15' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_NF_15MAY2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:5cc6cfa9-7087-4c52-a11c-70e23b78f4aa - ecosystem_type: Plant-associated - collection_date: '2017-05-15' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_NF_15MAY2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:59981b52-c78c-465d-ac28-540d16892cc0 - ecosystem_type: Plant-associated - collection_date: '2017-05-15' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_NF_15MAY2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:c9ce3883-2df1-42dd-bee0-4f5edff4918d - ecosystem_type: Plant-associated - collection_date: '2017-05-15' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_MAIN_05JUN2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:c8ed3ef9-c883-423c-8f86-03a21ede6ad8 - ecosystem_type: Plant-associated - collection_date: '2017-06-05' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_MAIN_05JUN2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:cd66a0eb-dee0-4f6e-b58a-08f0b3d83516 - ecosystem_type: Plant-associated - collection_date: '2017-06-05' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_MAIN_05JUN2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - 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ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_NF_05JUN2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:7a9060c2-4fc0-46e4-90d0-e22a188d7a85 - ecosystem_type: Plant-associated - collection_date: '2017-06-05' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_NF_05JUN2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - 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specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_NF_05JUN2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:14c783d2-e362-4714-b9c0-82d543416638 - ecosystem_type: Plant-associated - collection_date: '2017-06-05' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_MAIN_26JUN2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:9c3a480b-4fd0-4da8-823b-8b8a62481511 - ecosystem_type: Plant-associated - collection_date: '2017-06-26' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_MAIN_26JUN2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:a64ab1e2-b9f2-4fb6-8c7d-4b5804daf2c7 - ecosystem_type: Plant-associated - collection_date: '2017-06-26' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_MAIN_26JUN2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:c961d29c-9cbf-40ff-8e76-7d71b305e77a - ecosystem_type: Plant-associated - collection_date: '2017-06-26' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_MAIN_26JUN2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:bf9fdb1e-dc32-4ab0-a21e-dcdce379a46d - ecosystem_type: Plant-associated - collection_date: '2017-06-26' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_NF_26JUN2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:51b34532-a300-4936-a3a6-78a004833c10 - ecosystem_type: Plant-associated - collection_date: '2017-06-26' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_NF_26JUN2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:5e16e42e-fa44-4886-99a2-0327ee277102 - ecosystem_type: Plant-associated - collection_date: '2017-06-26' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_NF_26JUN2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:53d81d4e-31cf-40ae-afbc-7db4e5b6ec45 - ecosystem_type: Plant-associated - collection_date: '2017-06-26' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_NF_26JUN2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:aaababfe-dbd3-4df4-b5e8-c774025756e9 - ecosystem_type: Plant-associated - collection_date: '2017-06-26' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_MAIN_17JUL2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:70710e82-977d-4eb6-9ff9-824b48868741 - ecosystem_type: Plant-associated - collection_date: '2017-07-17' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_MAIN_17JUL2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:f5a9b5a6-7656-4e73-a5a0-c1260a456529 - ecosystem_type: Plant-associated - collection_date: '2017-07-17' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_MAIN_17JUL2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:0c78fda3-1424-4f6c-b4a9-9e07a84713f1 - ecosystem_type: Plant-associated - collection_date: '2017-07-17' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_MAIN_17JUL2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:74de6a27-6271-4338-a246-a51167fb6cd7 - ecosystem_type: Plant-associated - collection_date: '2017-07-17' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_NF_17JUL2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:fc666344-9d65-40f7-926e-d0f3e4056f69 - ecosystem_type: Plant-associated - collection_date: '2017-07-17' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_NF_17JUL2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:48f196f0-9267-42f7-b8ea-343b60b3b4c9 - ecosystem_type: Plant-associated - collection_date: '2017-07-17' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_NF_17JUL2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:4ede3f5e-419c-40e5-a38d-a525a212a918 - ecosystem_type: Plant-associated - collection_date: '2017-07-17' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_NF_17JUL2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:ef6c2246-3fd2-46ca-a744-00ca32d5287a - ecosystem_type: Plant-associated - collection_date: '2017-07-17' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_MAIN_07AUG2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:f2b2ff60-2cdd-4dba-9a3b-1d903a206ca8 - ecosystem_type: Plant-associated - collection_date: '2017-08-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_MAIN_07AUG2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:c0754834-384e-4282-a75c-39728ec343b8 - ecosystem_type: Plant-associated - collection_date: '2017-08-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_MAIN_07AUG2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:99757397-ff6e-4a92-b9ee-6b448a9a944d - ecosystem_type: Plant-associated - collection_date: '2017-08-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_MAIN_07AUG2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:9cc79dd8-95ef-4e8d-aade-6c9ac2216956 - ecosystem_type: Plant-associated - collection_date: '2017-08-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_NF_07AUG2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:d34b5892-b5a2-4392-83f5-53ea1abde7dd - ecosystem_type: Plant-associated - collection_date: '2017-08-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_NF_07AUG2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:41240494-f7e0-4f80-a417-93dfdc094a06 - ecosystem_type: Plant-associated - collection_date: '2017-08-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_NF_07AUG2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:d191dfe3-3845-455c-bfe1-665dbb7c5e8e - ecosystem_type: Plant-associated - collection_date: '2017-08-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_NF_07AUG2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:2ebb7684-ad20-41b0-b7be-ccf7c7210a13 - ecosystem_type: Plant-associated - collection_date: '2017-08-07' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_MAIN_28AUG2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:cb03f98b-1929-426a-b4e8-75c0b7f1208b - ecosystem_type: Plant-associated - collection_date: '2017-08-28' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_MAIN_28AUG2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:bee8b493-f526-4a8a-be59-f93e468a2618 - ecosystem_type: Plant-associated - collection_date: '2017-08-28' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R3_MAIN_28AUG2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:3e2bed09-0d41-4e67-bf73-008a6b3b1073 - ecosystem_type: Plant-associated - collection_date: '2017-08-28' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R4_MAIN_28AUG2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:451b29e2-f2b3-42f8-adfa-3d8e23ad8545 - ecosystem_type: Plant-associated - collection_date: '2017-08-28' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R1_NF_28AUG2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:8e985015-830a-4847-bc78-7723772a45d1 - ecosystem_type: Plant-associated - collection_date: '2017-08-28' - env_broad_scale: agricultural biome [ENVO:01001442] - env_local_scale: phyllosphere biome [ENVO:01001442] - samp_store_temp: "-80 Celsius" - ecosystem_subtype: Leaf - ecosystem_category: Terrestrial - specific_ecosystem: Phyllosphere - - elev: 286 - depth: '0' - lat_lon: 42.39 -85.37 - ecosystem: Environmental - samp_name: "G5R2_NF_28AUG2017" - env_medium: plant-associated biome [ENVO:01001001] - env_package: soil - geo_loc_name: 'USA: Kellogg Biological Station, Michigan' - growth_facil: field - analysis_type: - - metagenomics - source_mat_id: UUID:8fb00ba7-a382-4df2-a1b7-eecd087e000a - ecosystem_type: Plant-associated - collection_date: '2017-08-28' - env_broad_scale: agricultural biome [ENVO:01001442] - 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has_raw_value: 42.39 -85.37 - latitude: 42.39 - longitude: -85.37 - samp_store_temp: - has_raw_value: -80 Celsius - has_unit: Celsius - has_numeric_value: -80.0 - ecosystem: Environmental - ecosystem_category: Terrestrial - ecosystem_type: Plant-associated - ecosystem_subtype: Leaf - specific_ecosystem: Phyllosphere - growth_facil: - has_raw_value: field - source_mat_id: - has_raw_value: UUID:d191dfe3-3845-455c-bfe1-665dbb7c5e8e - analysis_type: - - metagenomics - - id: fake:ebe22b06-d3a4-492a-a0fe-84689ba93570 - part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 - env_broad_scale: - has_raw_value: agricultural biome [ENVO:01001442] - term: - id: ENVO:01001442 - name: agricultural biome - env_local_scale: - has_raw_value: phyllosphere biome [ENVO:01001442] - term: - id: ENVO:01001442 - name: phyllosphere biome - env_medium: - has_raw_value: plant-associated biome [ENVO:01001001] - term: - id: ENVO:01001001 - name: plant-associated biome - samp_name: G5R4_NF_07AUG2017 - collection_date: - has_raw_value: '2017-08-07' - depth: - has_raw_value: '0' - has_numeric_value: 0.0 - elev: 286.0 - env_package: - has_raw_value: soil - geo_loc_name: - has_raw_value: 'USA: Kellogg Biological Station, Michigan' - lat_lon: - has_raw_value: 42.39 -85.37 - latitude: 42.39 - longitude: -85.37 - samp_store_temp: - has_raw_value: -80 Celsius - has_unit: Celsius - has_numeric_value: -80.0 - ecosystem: Environmental - ecosystem_category: Terrestrial - ecosystem_type: Plant-associated - ecosystem_subtype: Leaf - specific_ecosystem: Phyllosphere - growth_facil: - has_raw_value: field - source_mat_id: - has_raw_value: UUID:2ebb7684-ad20-41b0-b7be-ccf7c7210a13 - analysis_type: - - metagenomics - - id: fake:b5af6743-0596-42eb-a32b-e270900dea60 - part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 - env_broad_scale: - has_raw_value: agricultural biome [ENVO:01001442] - term: - id: ENVO:01001442 - name: agricultural biome - env_local_scale: - has_raw_value: phyllosphere biome [ENVO:01001442] - term: - id: ENVO:01001442 - name: phyllosphere biome - env_medium: - has_raw_value: plant-associated biome [ENVO:01001001] - term: - id: ENVO:01001001 - name: plant-associated biome - samp_name: G5R1_MAIN_28AUG2017 - collection_date: - has_raw_value: '2017-08-28' - depth: - has_raw_value: '0' - has_numeric_value: 0.0 - elev: 286.0 - env_package: - has_raw_value: soil - geo_loc_name: - has_raw_value: 'USA: Kellogg Biological Station, Michigan' - lat_lon: - has_raw_value: 42.39 -85.37 - latitude: 42.39 - longitude: -85.37 - samp_store_temp: - has_raw_value: -80 Celsius - has_unit: Celsius - has_numeric_value: -80.0 - ecosystem: Environmental - ecosystem_category: Terrestrial - ecosystem_type: Plant-associated - ecosystem_subtype: Leaf - specific_ecosystem: Phyllosphere - growth_facil: - has_raw_value: field - source_mat_id: - has_raw_value: UUID:cb03f98b-1929-426a-b4e8-75c0b7f1208b - analysis_type: - - metagenomics - - id: fake:edcd16a4-9667-453b-81df-740a7a9e1a44 - part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 - env_broad_scale: - has_raw_value: agricultural biome [ENVO:01001442] - term: - id: ENVO:01001442 - name: agricultural biome - env_local_scale: - has_raw_value: phyllosphere biome [ENVO:01001442] - term: - id: ENVO:01001442 - name: phyllosphere biome - env_medium: - has_raw_value: plant-associated biome [ENVO:01001001] - term: - id: ENVO:01001001 - name: plant-associated biome - samp_name: G5R2_MAIN_28AUG2017 - collection_date: - has_raw_value: '2017-08-28' - depth: - has_raw_value: '0' - has_numeric_value: 0.0 - elev: 286.0 - env_package: - has_raw_value: soil - geo_loc_name: - has_raw_value: 'USA: Kellogg Biological Station, Michigan' - lat_lon: - has_raw_value: 42.39 -85.37 - latitude: 42.39 - longitude: -85.37 - samp_store_temp: - has_raw_value: -80 Celsius - has_unit: Celsius - has_numeric_value: -80.0 - ecosystem: Environmental - ecosystem_category: Terrestrial - ecosystem_type: Plant-associated - ecosystem_subtype: Leaf - specific_ecosystem: Phyllosphere - growth_facil: - has_raw_value: field - source_mat_id: - has_raw_value: UUID:bee8b493-f526-4a8a-be59-f93e468a2618 - analysis_type: - - metagenomics - - id: fake:d5817d8d-a564-4943-ae3a-8a5d284dda9b - part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 - env_broad_scale: - has_raw_value: agricultural biome [ENVO:01001442] - term: - id: ENVO:01001442 - name: agricultural biome - env_local_scale: - has_raw_value: phyllosphere biome [ENVO:01001442] - term: - id: ENVO:01001442 - name: phyllosphere biome - env_medium: - has_raw_value: plant-associated biome [ENVO:01001001] - term: - id: ENVO:01001001 - name: plant-associated biome - samp_name: G5R3_MAIN_28AUG2017 - collection_date: - has_raw_value: '2017-08-28' - depth: - has_raw_value: '0' - has_numeric_value: 0.0 - elev: 286.0 - env_package: - has_raw_value: soil - geo_loc_name: - has_raw_value: 'USA: Kellogg Biological Station, Michigan' - lat_lon: - has_raw_value: 42.39 -85.37 - latitude: 42.39 - longitude: -85.37 - samp_store_temp: - has_raw_value: -80 Celsius - has_unit: Celsius - has_numeric_value: -80.0 - ecosystem: Environmental - ecosystem_category: Terrestrial - ecosystem_type: Plant-associated - ecosystem_subtype: Leaf - specific_ecosystem: Phyllosphere - growth_facil: - has_raw_value: field - source_mat_id: - has_raw_value: UUID:3e2bed09-0d41-4e67-bf73-008a6b3b1073 - analysis_type: - - metagenomics - - id: fake:d4ea2474-11f6-417a-a490-f3688e17437b - part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 - env_broad_scale: - has_raw_value: agricultural biome [ENVO:01001442] - term: - id: ENVO:01001442 - name: agricultural biome - env_local_scale: - has_raw_value: phyllosphere biome [ENVO:01001442] - term: - id: ENVO:01001442 - name: phyllosphere biome - env_medium: - has_raw_value: plant-associated biome [ENVO:01001001] - term: - id: ENVO:01001001 - name: plant-associated biome - samp_name: G5R4_MAIN_28AUG2017 - collection_date: - has_raw_value: '2017-08-28' - depth: - has_raw_value: '0' - has_numeric_value: 0.0 - elev: 286.0 - env_package: - has_raw_value: soil - geo_loc_name: - has_raw_value: 'USA: Kellogg Biological Station, Michigan' - lat_lon: - has_raw_value: 42.39 -85.37 - latitude: 42.39 - longitude: -85.37 - samp_store_temp: - has_raw_value: -80 Celsius - has_unit: Celsius - has_numeric_value: -80.0 - ecosystem: Environmental - ecosystem_category: Terrestrial - ecosystem_type: Plant-associated - ecosystem_subtype: Leaf - specific_ecosystem: Phyllosphere - growth_facil: - has_raw_value: field - source_mat_id: - has_raw_value: UUID:451b29e2-f2b3-42f8-adfa-3d8e23ad8545 - analysis_type: - - metagenomics - - id: fake:3ad01c4b-245c-4f18-a3a8-dd0ed2aa2396 - part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 - env_broad_scale: - has_raw_value: agricultural biome [ENVO:01001442] - term: - id: ENVO:01001442 - name: agricultural biome - env_local_scale: - has_raw_value: phyllosphere biome [ENVO:01001442] - term: - id: ENVO:01001442 - name: phyllosphere biome - env_medium: - has_raw_value: plant-associated biome [ENVO:01001001] - term: - id: ENVO:01001001 - name: plant-associated biome - samp_name: G5R1_NF_28AUG2017 - collection_date: - has_raw_value: '2017-08-28' - depth: - has_raw_value: '0' - has_numeric_value: 0.0 - elev: 286.0 - env_package: - has_raw_value: soil - geo_loc_name: - has_raw_value: 'USA: Kellogg Biological Station, Michigan' - lat_lon: - has_raw_value: 42.39 -85.37 - latitude: 42.39 - longitude: -85.37 - samp_store_temp: - has_raw_value: -80 Celsius - has_unit: Celsius - has_numeric_value: -80.0 - ecosystem: Environmental - ecosystem_category: Terrestrial - ecosystem_type: Plant-associated - ecosystem_subtype: Leaf - specific_ecosystem: Phyllosphere - growth_facil: - has_raw_value: field - source_mat_id: - has_raw_value: UUID:8e985015-830a-4847-bc78-7723772a45d1 - analysis_type: - - metagenomics - - id: fake:8f320108-dc67-4eb3-819a-7db6b01bee79 - part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 - env_broad_scale: - has_raw_value: agricultural biome [ENVO:01001442] - term: - id: ENVO:01001442 - name: agricultural biome - env_local_scale: - has_raw_value: phyllosphere biome [ENVO:01001442] - term: - id: ENVO:01001442 - name: phyllosphere biome - env_medium: - has_raw_value: plant-associated biome [ENVO:01001001] - term: - id: ENVO:01001001 - name: plant-associated biome - samp_name: G5R2_NF_28AUG2017 - collection_date: - has_raw_value: '2017-08-28' - depth: - has_raw_value: '0' - has_numeric_value: 0.0 - elev: 286.0 - env_package: - has_raw_value: soil - geo_loc_name: - has_raw_value: 'USA: Kellogg Biological Station, Michigan' - lat_lon: - has_raw_value: 42.39 -85.37 - latitude: 42.39 - longitude: -85.37 - samp_store_temp: - has_raw_value: -80 Celsius - has_unit: Celsius - has_numeric_value: -80.0 - ecosystem: Environmental - ecosystem_category: Terrestrial - ecosystem_type: Plant-associated - ecosystem_subtype: Leaf - specific_ecosystem: Phyllosphere - growth_facil: - has_raw_value: field - source_mat_id: - has_raw_value: UUID:8fb00ba7-a382-4df2-a1b7-eecd087e000a - analysis_type: - - metagenomics - - id: fake:8f58dfc7-57df-48af-813d-3a7fd6fb4f46 + status: in-progress + id: d32b5eb6-71e8-4c98-8a57-3e64d05718b4 + author_orcid: 0000-0002-7705-343X + created: '2023-04-03T18:31:16.856377' + author: + id: 1bc43cf5-966e-4a44-8ab5-b61905210255 + orcid: 0000-0002-7705-343X + name: Adina Howe + is_admin: false +output: + biosample_set: + - id: nmdc:bsm-00-4wn6isig part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 + - nmdc:sty-00-y0cq65zt env_broad_scale: has_raw_value: agricultural biome [ENVO:01001442] term: @@ -12692,9 +316,10 @@ output: term: id: ENVO:01001001 name: plant-associated biome - samp_name: G5R3_NF_28AUG2017 + samp_name: G5R1_MAIN_09MAY2016 + name: G5R1_MAIN_09MAY2016 collection_date: - has_raw_value: '2017-08-28' + has_raw_value: '2016-05-09' depth: has_raw_value: '0' has_numeric_value: 0.0 @@ -12719,12 +344,12 @@ output: growth_facil: has_raw_value: field source_mat_id: - has_raw_value: UUID:dfee9c57-72a0-4a4d-8df3-743c1c8eb3e4 + has_raw_value: UUID:e8ed34cc-32f4-4fc5-9b9f-c2699e43163c analysis_type: - metagenomics - - id: fake:39027e5a-f2f4-42ed-9717-134e926c39bd + - id: nmdc:bsm-00-q8jtgev4 part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 + - nmdc:sty-00-y0cq65zt env_broad_scale: has_raw_value: agricultural biome [ENVO:01001442] term: @@ -12740,9 +365,10 @@ output: term: id: ENVO:01001001 name: plant-associated biome - samp_name: G5R4_NF_28AUG2017 + samp_name: G5R2_MAIN_09MAY2016 + name: G5R2_MAIN_09MAY2016 collection_date: - has_raw_value: '2017-08-28' + has_raw_value: '2016-05-09' depth: has_raw_value: '0' has_numeric_value: 0.0 @@ -12767,12 +393,12 @@ output: growth_facil: has_raw_value: field source_mat_id: - has_raw_value: UUID:bafedf91-1740-4efe-a542-40f259d68419 + has_raw_value: UUID:774bb4b9-5ebe-48d5-8236-1a60baa6af7a analysis_type: - metagenomics - - id: fake:5ef661dc-c225-4b49-af33-bec67ba8e1c8 + - id: nmdc:bsm-00-9gw1un94 part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 + - nmdc:sty-00-y0cq65zt env_broad_scale: has_raw_value: agricultural biome [ENVO:01001442] term: @@ -12788,9 +414,10 @@ output: term: id: ENVO:01001001 name: plant-associated biome - samp_name: G5R1_MAIN_18SEP2017 + samp_name: G5R3_MAIN_09MAY2016 + name: G5R3_MAIN_09MAY2016 collection_date: - has_raw_value: '2017-09-18' + has_raw_value: '2016-05-09' depth: has_raw_value: '0' has_numeric_value: 0.0 @@ -12815,12 +442,12 @@ output: growth_facil: has_raw_value: field source_mat_id: - has_raw_value: UUID:d3f9dcb9-4f7a-4d7b-8ee7-2fa9447f210d + has_raw_value: UUID:c0bb595b-9992-4475-8019-775189b5250a analysis_type: - metagenomics - - id: fake:5b48629c-21d4-471e-a65a-80de783aa7b5 + - id: nmdc:bsm-00-27qd9afz part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 + - nmdc:sty-00-y0cq65zt env_broad_scale: has_raw_value: agricultural biome [ENVO:01001442] term: @@ -12836,9 +463,10 @@ output: term: id: ENVO:01001001 name: plant-associated biome - samp_name: G5R2_MAIN_18SEP2017 + samp_name: G5R4_MAIN_09MAY2016 + name: G5R4_MAIN_09MAY2016 collection_date: - has_raw_value: '2017-09-18' + has_raw_value: '2016-05-09' depth: has_raw_value: '0' has_numeric_value: 0.0 @@ -12863,12 +491,12 @@ output: growth_facil: has_raw_value: field source_mat_id: - has_raw_value: UUID:a6cbb4e5-6482-4612-bccd-14778313c09b + has_raw_value: UUID:d74181a3-6fb9-406e-89f8-2d4861a4646c analysis_type: - metagenomics - - id: fake:5fa1ea5b-6e47-4bf9-a6c4-c4b6fe48dd1a + - id: nmdc:bsm-00-a5vpuemo part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 + - nmdc:sty-00-y0cq65zt env_broad_scale: has_raw_value: agricultural biome [ENVO:01001442] term: @@ -12884,9 +512,10 @@ output: term: id: ENVO:01001001 name: plant-associated biome - samp_name: G5R3_MAIN_18SEP2017 + samp_name: G5R1_NF_09MAY2016 + name: G5R1_NF_09MAY2016 collection_date: - has_raw_value: '2017-09-18' + has_raw_value: '2016-05-09' depth: has_raw_value: '0' has_numeric_value: 0.0 @@ -12911,12 +540,12 @@ output: growth_facil: has_raw_value: field source_mat_id: - has_raw_value: UUID:fe48a1cc-4184-467b-ae68-5f599c00327b + has_raw_value: UUID:edfd5080-ccc2-495b-b17a-190ad6649291 analysis_type: - metagenomics - - id: fake:7ae74a1e-7227-48ee-bebe-2fedf4567f3a + - id: nmdc:bsm-00-pj82ffu6 part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 + - nmdc:sty-00-y0cq65zt env_broad_scale: has_raw_value: agricultural biome [ENVO:01001442] term: @@ -12932,9 +561,10 @@ output: term: id: ENVO:01001001 name: plant-associated biome - samp_name: G5R4_MAIN_18SEP2017 + samp_name: G5R2_NF_09MAY2016 + name: G5R2_NF_09MAY2016 collection_date: - has_raw_value: '2017-09-18' + has_raw_value: '2016-05-09' depth: has_raw_value: '0' has_numeric_value: 0.0 @@ -12959,12 +589,12 @@ output: growth_facil: has_raw_value: field source_mat_id: - has_raw_value: UUID:ac03bdb2-f5b4-4131-9a9a-6d27e7100f55 + has_raw_value: UUID:483921c0-7fa9-4a31-b281-e09565a0d6f9 analysis_type: - metagenomics - - id: fake:1cae62f9-6376-4376-baef-faff90d49e38 + - id: nmdc:bsm-00-5gt9sh9v part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 + - nmdc:sty-00-y0cq65zt env_broad_scale: has_raw_value: agricultural biome [ENVO:01001442] term: @@ -12980,9 +610,10 @@ output: term: id: ENVO:01001001 name: plant-associated biome - samp_name: G5R1_NF_18SEP2017 + samp_name: G5R3_NF_09MAY2016 + name: G5R3_NF_09MAY2016 collection_date: - has_raw_value: '2017-09-18' + has_raw_value: '2016-05-09' depth: has_raw_value: '0' has_numeric_value: 0.0 @@ -13007,12 +638,12 @@ output: growth_facil: has_raw_value: field source_mat_id: - has_raw_value: UUID:b2890880-d327-4cc3-91eb-5d06f3cad19d + has_raw_value: UUID:3b9aab19-0110-415b-8e29-849f0696de47 analysis_type: - metagenomics - - id: fake:ac66804f-7c3b-4084-af00-17785164e4f3 + - id: nmdc:bsm-00-8n9s2fyu part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 + - nmdc:sty-00-y0cq65zt env_broad_scale: has_raw_value: agricultural biome [ENVO:01001442] term: @@ -13028,9 +659,10 @@ output: term: id: ENVO:01001001 name: plant-associated biome - samp_name: G5R2_NF_18SEP2017 + samp_name: G5R4_NF_09MAY2016 + name: G5R4_NF_09MAY2016 collection_date: - has_raw_value: '2017-09-18' + has_raw_value: '2016-05-09' depth: has_raw_value: '0' has_numeric_value: 0.0 @@ -13055,12 +687,12 @@ output: growth_facil: has_raw_value: field source_mat_id: - has_raw_value: UUID:202eb34b-4d7f-4157-a190-035a4dd907e0 + has_raw_value: UUID:579ec4b9-57c4-4431-8df9-432138233b0b analysis_type: - metagenomics - - id: fake:3ad2f76e-fb0c-43c5-8a68-174333b9532d + - id: nmdc:bsm-00-pslmlcq4 part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 + - nmdc:sty-00-y0cq65zt env_broad_scale: has_raw_value: agricultural biome [ENVO:01001442] term: @@ -13076,9 +708,10 @@ output: term: id: ENVO:01001001 name: plant-associated biome - samp_name: G5R3_NF_18SEP2017 + samp_name: G6R1_MAIN_09MAY2016 + name: G6R1_MAIN_09MAY2016 collection_date: - has_raw_value: '2017-09-18' + has_raw_value: '2016-05-09' depth: has_raw_value: '0' has_numeric_value: 0.0 @@ -13103,12 +736,12 @@ output: growth_facil: has_raw_value: field source_mat_id: - has_raw_value: UUID:178856e7-f799-4f61-a356-d5d2bd098daa + has_raw_value: UUID:69dd84ff-d777-4d1e-ac22-9cdac87074f5 analysis_type: - metagenomics - - id: fake:1c2eccb2-5d07-4bf3-8b02-618801211dd2 + - id: nmdc:bsm-00-efijcf8z part_of: - - fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 + - nmdc:sty-00-y0cq65zt env_broad_scale: has_raw_value: agricultural biome [ENVO:01001442] term: @@ -13124,9 +757,10 @@ output: term: id: ENVO:01001001 name: plant-associated biome - samp_name: G5R4_NF_18SEP2017 + samp_name: G6R2_MAIN_09MAY2016 + name: G6R2_MAIN_09MAY2016 collection_date: - has_raw_value: '2017-09-18' + has_raw_value: '2016-05-09' depth: has_raw_value: '0' has_numeric_value: 0.0 @@ -13151,11 +785,11 @@ output: growth_facil: has_raw_value: field source_mat_id: - has_raw_value: UUID:4720b174-508e-4b35-875f-373fe661a73a + has_raw_value: UUID:c0c4a2b5-0382-450a-8728-a176fa438efe analysis_type: - metagenomics study_set: - - id: fake:d862c2e3-6b0a-42f7-827c-67ebc8d44df7 + - id: nmdc:sty-00-y0cq65zt name: Seasonal activities of the phyllosphere microbiome of perennial crops description: Understanding the interactions between plants and microorganisms can inform microbiome management to enhance crop productivity and resilience to stress. @@ -13176,8 +810,8 @@ output: orcid: 0000-0002-7189-3067 email: shade.ashley@gmail.com name: Ashley Shade - doi: - has_raw_value: 10.46936/10.25585/60000818 + dataset_dois: + - doi:10.46936/10.25585/60000818 title: Seasonal activities of the phyllosphere microbiome of perennial crops websites: - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9950430/ @@ -13201,3 +835,157 @@ output: - Software - Principal Investigator - Funding acquisition +--- +input: + metadata_submission: + id: 00000000-0000-0000-0000-000000000000, + metadata_submission: + contextForm: + datasetDoi: doi:10.12345/10.12345/00000000 + packageName: plant-associated + sampleData: + plant_associated_data: + - analysis_type: + - metagenomics + collection_date: '2016-05-09' + depth: '0' + ecosystem: Environmental + ecosystem_category: Terrestrial + ecosystem_subtype: Leaf + ecosystem_type: Plant-associated + elev: '286' + env_broad_scale: agricultural biome [ENVO:01001442] + env_local_scale: phyllosphere biome [ENVO:01001442] + env_medium: plant-associated biome [ENVO:01001001] + env_package: soil + geo_loc_name: 'USA: Kellogg Biological Station, Michigan' + growth_facil: field + lat_lon: 42.39 -85.37 + samp_name: G5R1_MAIN_09MAY2016 + samp_store_temp: -80 Celsius + source_mat_id: UUID:e8ed34cc-32f4-4fc5-9b9f-c2699e43163c + specific_ecosystem: Phyllosphere + studyForm: + contributors: + - name: Test Testerson + orcid: 0000-0000-0000-0000 + roles: + - Principal Investigator + description: This is a test submission + linkOutWebpage: + - http://www.example.com/submission-test + multiOmicsForm: + GOLDStudyId: '' + JGIStudyId: '' + NCBIBioProjectId: '' + alternativeNames: [ ] + studyNumber: '' + piEmail: test.testerson@example.com + piName: Test Testerson + piOrcid: 0000-0000-0000-0000 + studyName: A test submission + templates: + - plant-associated + omics_processing_mapping: + - __biosample_source_mat_id: UUID:e8ed34cc-32f4-4fc5-9b9f-c2699e43163c + processing_institution: JGI + instrument_name: Some fancy expensive thing + omics_type: Metagenome + data_object_mapping: + - __biosample_source_mat_id: UUID:e8ed34cc-32f4-4fc5-9b9f-c2699e43163c + data_object_type: Metagenome Raw Reads + url: http://example.com/data.fastq.gz + name: Metagenome Raw Reads + description: Metagenome Raw Reads +output: + biosample_set: + - id: nmdc:bsm-00-4wn6isig + name: G5R1_MAIN_09MAY2016 + part_of: + - nmdc:sty-00-y0cq65zt + env_broad_scale: + has_raw_value: agricultural biome [ENVO:01001442] + term: + id: ENVO:01001442 + name: agricultural biome + env_local_scale: + has_raw_value: phyllosphere biome [ENVO:01001442] + term: + id: ENVO:01001442 + name: phyllosphere biome + env_medium: + has_raw_value: plant-associated biome [ENVO:01001001] + term: + id: ENVO:01001001 + name: plant-associated biome + samp_name: G5R1_MAIN_09MAY2016 + collection_date: + has_raw_value: '2016-05-09' + depth: + has_raw_value: '0' + has_numeric_value: 0.0 + ecosystem: Environmental + ecosystem_category: Terrestrial + ecosystem_subtype: Leaf + ecosystem_type: Plant-associated + elev: 286.0 + env_package: + has_raw_value: soil + geo_loc_name: + has_raw_value: 'USA: Kellogg Biological Station, Michigan' + growth_facil: + has_raw_value: field + lat_lon: + has_raw_value: 42.39 -85.37 + latitude: 42.39 + longitude: -85.37 + samp_store_temp: + has_raw_value: -80 Celsius + has_unit: Celsius + has_numeric_value: -80.0 + source_mat_id: + has_raw_value: UUID:e8ed34cc-32f4-4fc5-9b9f-c2699e43163c + specific_ecosystem: Phyllosphere + analysis_type: + - metagenomics + data_object_set: + - id: nmdc:dobj-00-9gw1un94 + name: Metagenome Raw Reads + description: Metagenome Raw Reads + data_object_type: Metagenome Raw Reads + url: http://example.com/data.fastq.gz + type: nmdc:DataObject + omics_processing_set: + - id: nmdc:omprc-00-q8jtgev4 + has_input: + - nmdc:bsm-00-4wn6isig + add_date: '2023-10-17' + has_output: + - nmdc:dobj-00-9gw1un94 + instrument_name: Some fancy expensive thing + mod_date: '2023-10-17' + omics_type: + has_raw_value: Metagenome + part_of: + - nmdc:sty-00-y0cq65zt + processing_institution: JGI + type: nmdc:OmicsProcessing + study_set: + - id: nmdc:sty-00-y0cq65zt + name: A test submission + description: This is a test submission + dataset_dois: + - doi:10.12345/10.12345/00000000 + has_credit_associations: + - applies_to_person: + orcid: 0000-0000-0000-0000 + name: Test Testerson + applied_roles: + - Principal Investigator + principal_investigator: + orcid: 0000-0000-0000-0000 + email: test.testerson@example.com + name: Test Testerson + title: A test submission + websites: + - http://www.example.com/submission-test diff --git a/tests/test_graphs/test_submission_portal_graphs.py b/tests/test_graphs/test_submission_portal_graphs.py index f7972a3c..d6057f89 100644 --- a/tests/test_graphs/test_submission_portal_graphs.py +++ b/tests/test_graphs/test_submission_portal_graphs.py @@ -12,7 +12,7 @@ "id": MOCK_PORTAL_SUBMISSION_ID, "metadata_submission": { "packageName": "plant-associated", - "contextForm": {"datasetDoi": "10.12345/10.12345/00000000"}, + "contextForm": {"datasetDoi": "doi:10.12345/10.12345/00000000"}, "templates": ["plant-associated"], "studyForm": { "studyName": "A test submission", @@ -80,9 +80,11 @@ def test_translate_metadata_submission_to_nmdc_schema_database(): "export_json_to_drs": { "config": {"username": "test"}, }, - "fetch_nmdc_portal_submission_by_id": { + "get_submission_portal_pipeline_inputs": { "config": { "submission_id": MOCK_PORTAL_SUBMISSION_ID, + "omics_processing_mapping_file_url": "", + "data_object_mapping_file_url": "", } }, }, diff --git a/tests/test_normalization/__init__.py b/tests/test_normalization/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/test_normalization/test_gold.py b/tests/test_normalization/test_gold.py new file mode 100644 index 00000000..34c8aa2e --- /dev/null +++ b/tests/test_normalization/test_gold.py @@ -0,0 +1,28 @@ +# nmdc-runtime/tests/test_normalization/test_gold.py +""" +test_gold.py: Tests for nmdc_runtime/site/normalization/gold.py +""" + +from nmdc_runtime.site.normalization.gold import ( + get_gold_biosample_name_suffix, + normalize_gold_id, +) + + +def test_get_gold_biosample_name_suffix(): + biosample_name = "Terrestrial soil microbial communities from Disney Wilderness Preserve, Southeast, FL, USA - DSNY_016-M-37-14-20140409-GEN-DNA1" + assert ( + get_gold_biosample_name_suffix(biosample_name) + == "DSNY_016-M-37-14-20140409-GEN-DNA1" + ) + + +def test_normalize_gold_biosample_id(): + test_inputs = [ + ("GOLD:Gb0356158", "gold:Gb0356158"), + ("Gb0356158", "gold:Gb0356158"), + ("gold:Gb0356158", "gold:Gb0356158"), + ("Gold:Gb0356158", "gold:Gb0356158"), + ] + for test_input, expected_output in test_inputs: + assert normalize_gold_id(test_input) == expected_output diff --git a/tests/test_ops/test_data_api_ops.py b/tests/test_ops/test_data_api_ops.py index 91a97413..b5b301dd 100644 --- a/tests/test_ops/test_data_api_ops.py +++ b/tests/test_ops/test_data_api_ops.py @@ -20,7 +20,6 @@ def op_context(client_config): client_config ) }, - op_config={"submission_id": "353d751f-cff0-4558-9051-25a87ba00d3f"}, ) @@ -31,6 +30,8 @@ def test_metadata_submission(op_context): json={"id": "353d751f-cff0-4558-9051-25a87ba00d3f"}, ) - fetch_nmdc_portal_submission_by_id(op_context) + fetch_nmdc_portal_submission_by_id( + op_context, "353d751f-cff0-4558-9051-25a87ba00d3f" + ) assert len(mock.request_history) == 1 diff --git a/tests/test_ops/test_get_csv_rows_from_url.py b/tests/test_ops/test_get_csv_rows_from_url.py new file mode 100644 index 00000000..087a953f --- /dev/null +++ b/tests/test_ops/test_get_csv_rows_from_url.py @@ -0,0 +1,30 @@ +import pytest +import requests +import requests_mock +from dagster import build_op_context + +from nmdc_runtime.site.ops import get_csv_rows_from_url + + +def test_valid_data(): + context = build_op_context() + with requests_mock.mock() as mock: + mock.get( + "http://www.example.com/data.csv", + text='a,b,c\n1,hello,"apple, banana"\n2,wow,great', + ) + + result = get_csv_rows_from_url(context, "http://www.example.com/data.csv") + assert result == [ + {"a": "1", "b": "hello", "c": "apple, banana"}, + {"a": "2", "b": "wow", "c": "great"}, + ] + + +def test_not_found(): + context = build_op_context() + with requests_mock.mock() as mock: + mock.get("http://www.example.com/data.csv", status_code=404) + + with pytest.raises(requests.HTTPError): + get_csv_rows_from_url(context, "http://www.example.com/data.csv") diff --git a/util/mongorestore-nmdc.sh b/util/mongorestore-nmdc.sh index e0f5f253..aa23ccfb 100755 --- a/util/mongorestore-nmdc.sh +++ b/util/mongorestore-nmdc.sh @@ -4,4 +4,4 @@ # $ ./util/mongorestore-nmdc.sh mongorestore -h $MONGO_HOST -u $MONGO_USERNAME -p $MONGO_PASSWORD --authenticationDatabase=admin \ --gzip --drop \ - $HOME/nmdcdb-mongodump/nmdcdb/2023-05-24T11/ \ No newline at end of file + $HOME/nmdcdb-mongodump/nmdcdb/2023-11-02T11/ \ No newline at end of file