mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-09-20 03:18:12 +08:00
1621d20bc4
Checkpointing. This is a minimum working version using the iterator. I basically hacked consuming the iterator since I want to switch directions, but this is a good place to come back to.
219 lines
9.4 KiB
Python
219 lines
9.4 KiB
Python
from flask import (
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Blueprint, request
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)
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from flask_restful_swagger_2 import Api, swagger, Resource
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from ..util.utils import make_payload
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from ..util.filter import parse_filter
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class InitializeAPI(Resource):
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@swagger.doc({
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'summary': 'get metadata schema, ranges for values, and cell count to initialize cellxgene app',
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'tags': ['initialize'],
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'parameters': [],
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'responses': {
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'200': {
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'description': 'initialization data for UI',
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'examples': {
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'application/json': {
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"data": {
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"cellcount": 3589,
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"options": {
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"Sample.type": {
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"options": {
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"Glioblastoma": 3589
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}
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},
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"Selection": {
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"options": {
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"Astrocytes(HEPACAM)": 714,
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"Endothelial(BSC)": 123,
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"Microglia(CD45)": 1108,
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"Neurons(Thy1)": 685,
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"Oligodendrocytes(GC)": 294,
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"Unpanned": 665
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}
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},
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"Splice_sites_AT.AC": {
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"range": {
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"max": 1025,
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"min": 152
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}
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},
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"Splice_sites_Annotated": {
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"range": {
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"max": 1075869,
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"min": 26
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}
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}
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},
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"schema": {
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"CellName": {
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"displayname": "Name",
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"type": "string",
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"variabletype": "categorical"
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},
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"Class": {
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"displayname": "Class",
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"type": "string",
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"variabletype": "categorical"
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},
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"ERCC_reads": {
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"displayname": "ERCC Reads",
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"type": "int",
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"variabletype": "continuous"
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},
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"ERCC_to_non_ERCC": {
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"displayname": "ERCC:Non-ERCC",
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"type": "float",
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"variabletype": "continuous"
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},
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"Genes_detected": {
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"displayname": "Genes Detected",
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"type": "int",
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"variabletype": "continuous"
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}
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},
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"genes": ["1/2-SBSRNA4", "A1BG", "A1BG-AS1"]
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},
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"status": {
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"error": False,
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"errormessage": ""
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}
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}
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}
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}
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}
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})
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def get(self):
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from app import data, REACTIVE_LIMIT
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return make_payload({
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"schema": data.schema,
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"cellcount": data.cell_count,
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"reactivelimit": REACTIVE_LIMIT,
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"genes": data.genes(),
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"ranges": data.metadata_ranges(),
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})
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class CellsAPI(Resource):
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@swagger.doc({
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'summary': 'filter based on metadata fields to get a subset cells, expression data, and metadata',
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'tags': ['cells'],
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'description': "Cells takes query parameters defined in the schema retrieved from the /initialize enpoint. "
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"<br>For categorical metadata keys filter based on `key=value` <br>"
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" For continuous metadata keys filter by `key=min,max`<br> Either value "
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"can be replaced by a \*. To have only a minimum value `key=min,\*` To have only a maximum "
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"value `key=\*,max` <br>Graph data (if retrieved) is normalized"
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" To only retrieve cells that don't have a value for the key filter by `key`",
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'parameters': [],
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'responses': {
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'200': {
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'description': 'initialization data for UI',
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'examples': {
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'application/json': {
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"data": {
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"badmetadatacount": 0,
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"cellcount": 0,
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"cellids": ["..."],
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"metadata": [
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{
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"CellName": "1001000173.G8",
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"Class": "Neoplastic",
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"Cluster_2d": "11",
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"Cluster_2d_color": "#8C564B",
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"Cluster_CNV": "1",
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"Cluster_CNV_color": "#1F77B4",
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"ERCC_reads": "152104",
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"ERCC_to_non_ERCC": "0.562454470489481",
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"Genes_detected": "1962",
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"Location": "Tumor",
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"Location.color": "#FF7F0E",
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"Multimapping_reads_percent": "2.67",
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"Neoplastic": "Neoplastic",
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"Non_ERCC_reads": "270429",
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"Sample.name": "BT_S2",
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"Sample.name.color": "#AEC7E8",
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"Sample.type": "Glioblastoma",
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"Sample.type.color": "#1F77B4",
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"Selection": "Unpanned",
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"Selection.color": "#98DF8A",
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"Splice_sites_AT.AC": "102",
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"Splice_sites_Annotated": "122397",
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"Splice_sites_GC.AG": "761",
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"Splice_sites_GT.AG": "125741",
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"Splice_sites_non_canonical": "56",
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"Splice_sites_total": "126660",
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"Total_reads": "1741039",
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"Unique_reads": "1400382",
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"Unique_reads_percent": "80.43",
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"Unmapped_mismatch": "2.15",
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"Unmapped_other": "0.18",
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"Unmapped_short": "14.56",
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"housekeeping_cluster": "2",
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"housekeeping_cluster_color": "#AEC7E8",
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"recluster_myeloid": "NA",
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"recluster_myeloid_color": "NA"
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},
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],
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"reactive": True,
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"graph": [
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[
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"1001000173.G8",
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0.93836,
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0.28623
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],
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[
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"1001000173.D4",
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0.1662,
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0.79438
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]
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],
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"status": {
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"error": False,
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"errormessage": ""
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}
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},
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}
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},
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},
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'400': {
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'description': 'bad query params',
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}
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}
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})
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def get(self):
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from app import data
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payload = {
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"cellids": [],
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"metadata": [],
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"cellcount": 0,
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"graph": [],
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"ranges": {},
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}
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# get query params
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filter = parse_filter(request.args, data.schema)
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filtered_data = list(data.filter_cells(filter))
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payload["metadata"] = list(data.metadata(filtered_data))
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payload["ranges"] = list(data.metadata_ranges(filtered_data))
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payload["cellids"] = filtered_data
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payload["cellcount"] = len(payload["cellids"])
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payload["graph"] = list(data.create_graph(filtered_data))
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return make_payload(payload)
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def get_api_resources():
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bp = Blueprint('api', __name__, url_prefix='/api/v2.0')
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api = Api(bp, add_api_spec_resource=False)
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api.add_resource(InitializeAPI, "/initialize")
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api.add_resource(CellsAPI, "/cells")
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return api |