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https://github.com/chanzuckerberg/cellxgene.git
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fb61bd6e9c
This splits the backend into two parts: the local backend for desktop cellxgene and the AWS backend for hosted cellxgene. The local backend is in local_server while the hosted remains in server. The general idea is to copy everything from server to local_server, pull unneeded stuff out of local_server, and keep server as-is for this PR. Not touching server means all the infra and deployment code will continue working just as it did before so we can make those changes incrementally.
56 lines
2.1 KiB
Python
56 lines
2.1 KiB
Python
from enum import Enum
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from local_server.common.errors import DatasetAccessError
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from local_server.common.data_locator import DataLocator
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from http import HTTPStatus
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class MatrixDataType(Enum):
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H5AD = "h5ad"
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UNKNOWN = "unknown"
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class MatrixDataLoader(object):
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def __init__(self, location, matrix_data_type=None, app_config=None):
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""" location can be a string or DataLocator """
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region_name = None if app_config is None else app_config.server_config.data_locator__s3__region_name
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self.location = DataLocator(location, region_name=region_name)
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if not self.location.exists():
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raise DatasetAccessError("Dataset does not exist.", HTTPStatus.NOT_FOUND)
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# matrix_data_type is an enum value of type MatrixDataType
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self.matrix_data_type = matrix_data_type
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# matrix_type is a DataAdaptor type, which corresonds to the matrix_data_type
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self.matrix_type = None
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if matrix_data_type is None:
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self.matrix_data_type = self.__matrix_data_type()
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if not self.__matrix_data_type_allowed(app_config):
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raise DatasetAccessError("Dataset does not have an allowed type.")
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if self.matrix_data_type == MatrixDataType.H5AD:
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from local_server.data_anndata.anndata_adaptor import AnndataAdaptor
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self.matrix_type = AnndataAdaptor
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def __matrix_data_type(self):
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if self.location.path.endswith(".h5ad"):
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return MatrixDataType.H5AD
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else:
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return MatrixDataType.UNKNOWN
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def __matrix_data_type_allowed(self, app_config):
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return self.matrix_data_type != MatrixDataType.UNKNOWN
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def pre_load_validation(self):
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if self.matrix_data_type == MatrixDataType.UNKNOWN:
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raise DatasetAccessError("Dataset does not have a recognized type: .h5ad")
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self.matrix_type.pre_load_validation(self.location)
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def file_size(self):
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return self.matrix_type.file_size(self.location)
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def open(self, app_config, dataset_config=None):
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# create and return a DataAdaptor object
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return self.matrix_type.open(self.location, app_config, dataset_config)
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