server refactor (#1140)

This PR contains a refactoring to make adding new features easier.

The new features include supporting the tiledb format, and the multi dataset application.

The refactoring includes

Simplifying the directory structure and files.
a class structure to handle annotations (currently one type: AnnotationsLocalFile).
a class to handle application configuration
a class structure to handle matrix data (currently AnndataAdaptor and CxgAdaptor). CxgAdaptor uses tiledb.
Algorithms that were previously dependent on the scanpy anndata object are now generalized to work with an abstract interface.
The multi dataset option is not fully supported yet, and so the option to use it is hidden.
Use "cli launch --dataroot ..."
To access this feature.

All combinations of app single dataset/ app multi dataset and AnndataAdaptor/CxgAdaptor work with all the features, such as annotations, ontologies, diffexp.

server/data_common/fbs/NetEncoding/JSONEncodedArray.py

@@ -0,0 +1,46 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: NetEncoding
+
+import flatbuffers
+
+class JSONEncodedArray(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAsJSONEncodedArray(cls, buf, offset):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = JSONEncodedArray()
+        x.Init(buf, n + offset)
+        return x
+
+    # JSONEncodedArray
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # JSONEncodedArray
+    def Data(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.Get(flatbuffers.number_types.Uint8Flags, a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 1))
+        return 0
+
+    # JSONEncodedArray
+    def DataAsNumpy(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.GetVectorAsNumpy(flatbuffers.number_types.Uint8Flags, o)
+        return 0
+
+    # JSONEncodedArray
+    def DataLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+def JSONEncodedArrayStart(builder): builder.StartObject(1)
+def JSONEncodedArrayAddData(builder, data): builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(data), 0)
+def JSONEncodedArrayStartDataVector(builder, numElems): return builder.StartVector(1, numElems, 1)
+def JSONEncodedArrayEnd(builder): return builder.EndObject()