mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-10-01 23:48:11 +08:00
Flatbuffer cleanup (#598)
* dead code and route removal * more dead code cleanup * fix scanpy_engine tests * lint * add missing catch in filter parsing * update scanpy NaN tests * more fbs tests and dead test removal * remove forced default for content type negotiation * bit of cleanup * more fbs test cleanup * lint * remove swagger * swagger cleanup * lint * correctly handle lack of templates * more dead code removal * remove unused files * fix dev build * lint
This commit is contained in:
Bruce Martin
@@ -1,86 +0,0 @@
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import json
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from collections import defaultdict
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from numpy import float32, int32
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from server.app.util.constants import Axis
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class QueryStringError(Exception):
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def __init__(self, key, message):
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self.key = key
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self.message = message
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def _convert_variable(datatype, variable):
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"""
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Convert variable to number (float/int)
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Used for dataset metadata and for query string
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:param datatype: type to convert to
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:param variable (string or None): value of variable
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:return: converted variable
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:raises: AssertionError
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"""
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assert datatype in ["boolean", "categorical", "float32", "int32", "string"]
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if variable is None:
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return variable
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if datatype == "int32":
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variable = int32(variable)
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elif datatype == "float32":
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variable = float32(variable)
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elif datatype == "boolean":
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variable = json.loads(variable)
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assert isinstance(variable, bool)
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return variable
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def parse_filter(query_filter, schema):
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"""
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The filter comes in as arguments from a GET request
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For categorical metadata keys filter based on axis:key=value
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For continuous metadata keys filter by axis:key=min,max
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Either value can be replaced by a * To have only a minimum
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value axis:key=min,* To have only a maximum value axis:key=*,max
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They combine via AND so a cell's metadata would have to match every filter
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The results is a matrix with the cells the pass the filter and at this point all the genes
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:param query_filter: flask's request.args
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:param schema: dictionary schema
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:raises QueryStringError
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:return:
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"""
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query = defaultdict(lambda: defaultdict(list))
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for key in query_filter:
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axis, annotation = key.split(":", 1)
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try:
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Axis(axis)
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except ValueError:
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raise QueryStringError(key, f"Error: key {key} not in metadata schema")
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ann_filter = {"name": annotation}
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for ann in schema[axis]:
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if ann["name"] == annotation:
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dtype = ann["type"]
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break
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else:
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raise QueryStringError(key, f"Error: {annotation} not a valid annotation name")
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if dtype in ["string", "categorical", "boolean"]:
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ann_filter["values"] = [_convert_variable(dtype, i) for i in query_filter.getlist(key)]
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else:
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value = query_filter.get(key)
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try:
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min_, max_ = value.split(",")
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except ValueError:
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raise QueryStringError(key, f"Error: min,max format required for range for {annotation}, got {value}")
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if min_ == "*":
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min_ = None
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if max_ == "*":
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max_ = None
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try:
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ann_filter["min"] = _convert_variable(dtype, min_)
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ann_filter["max"] = _convert_variable(dtype, max_)
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except ValueError:
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raise QueryStringError(key, f"Error: expected type {query[key]['type']} for key {key}, got {value}")
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query[axis]["annotation_value"].append(ann_filter)
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return query
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@@ -1,34 +0,0 @@
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from flask_restful_swagger_2 import Schema
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class AnnotationModel(Schema):
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type = "object"
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description = "Filter by annotation key: value"
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properties = {
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"name": {"type": "string"},
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# TODO update to OpenAPI v3.0 when a library is available that supports it
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# Unfortunately 2.0 doesn't have a way to have a schema that accepts multiple types
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# Overloading the type key with a list seems to work ok and makes it to the page
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"values": {"type": "array", "items": {"type": ["float32", "string", "int32", "bool"]}},
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"min": {"type": ["int32", "float32"]},
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"max": {"type": ["int32", "float32"]},
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}
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required = ["name"]
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class IndexModel(Schema):
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type = "object"
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description = "Filter by index of observation/variable ex. [0, 5, 15]"
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properties = {"index": {"type": "array", "items": {"format": "int32", "type": "integer"}}}
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class AxisModel(Schema):
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type = "object"
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description = "Axis of data -- obs or var"
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properties = {"index": IndexModel, "annotation_value": AnnotationModel.array()}
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class FilterModel(Schema):
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type = "object"
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description = "Complex filter"
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properties = {"filter": {"type": "object", "properties": {"obs": AxisModel, "var": AxisModel}}}
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@@ -1,10 +1,6 @@
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import json
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from argparse import ArgumentTypeError
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from numpy import float32, integer
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from server.app.util.errors import MimeTypeError
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class Float32JSONEncoder(json.JSONEncoder):
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def __init__(self, *args, **kwargs):
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@@ -30,31 +26,5 @@ def custom_format_warning(msg, *args, **kwargs):
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return f"[cellxgene] Warning: {msg} \n"
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def get_mime_type(
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default="application/json", acceptable_types=["application/json", "text/csv"], query_param=None, header=None
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):
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mime_type = default
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if query_param:
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if query_param in acceptable_types:
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mime_type = query_param
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else:
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raise MimeTypeError(f"Unsupported mime type {query_param} specified in query parameter 'accept-type'")
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elif len(header):
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mime_type = header.best_match(acceptable_types)
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if not mime_type:
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raise MimeTypeError(f"Unsupported mime type(s) {header} in HTTP Accept header")
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return mime_type
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def whole_number(value):
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try:
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value = int(value)
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except ValueError as e:
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raise ArgumentTypeError(f"{value} is not type int") from e
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if value < 0:
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raise ArgumentTypeError(f"{value} is not >= 0")
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return value
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def jsonify_scanpy(data):
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return json.dumps(data, cls=Float32JSONEncoder, allow_nan=False)
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