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aidanaidan
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Add dual category support to tables
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‎metrics/api/serializers/__init__.py‎

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from .charts import ChartsSerializer
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from .dual_category_tables import (
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DualCategoryTablesSerializer,
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DualCategoryTablesResponseSerializer,
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)
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from .headlines import HeadlinesQuerySerializer, CoreHeadlineSerializer
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from .trends import TrendsQuerySerializer, TrendsResponseSerializer
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from .downloads import (

‎metrics/api/serializers/dual_category_tables.py‎

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import contextlib
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from django.db.utils import OperationalError
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from rest_framework import serializers
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from rest_framework.request import Request
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from metrics.api.serializers import help_texts
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from metrics.api.serializers.plots import PlotSerializer
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from metrics.domain.common.utils import (
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DEFAULT_CHART_HEIGHT,
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DEFAULT_CHART_WIDTH,
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DEFAULT_X_AXIS,
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DEFAULT_Y_AXIS,
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ChartAxisFields,
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)
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from metrics.domain.models import ChartRequestParams
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class DualCategoryTableSegmentSerializer(serializers.Serializer):
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colour = serializers.CharField(
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required=False,
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allow_blank=True,
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allow_null=True,
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default="",
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help_text=help_texts.LABEL_FIELD,
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)
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secondary_field_value = serializers.CharField(
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required=False,
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allow_blank=True,
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allow_null=True,
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default="",
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help_text=help_texts.LABEL_FIELD,
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)
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label = serializers.CharField(
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required=False,
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allow_blank=True,
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allow_null=True,
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default="",
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help_text=help_texts.LABEL_FIELD,
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)
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class DualCategoryTableSegmentListSerializer(serializers.ListSerializer):
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child = DualCategoryTableSegmentSerializer()
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class DualCategoryTablesSerializer(serializers.Serializer):
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segments = DualCategoryTableSegmentListSerializer()
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static_fields = PlotSerializer()
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x_axis = serializers.ChoiceField(
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choices=ChartAxisFields.choices(),
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required=False,
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allow_blank=True,
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allow_null=True,
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help_text=help_texts.CHART_X_AXIS,
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default=DEFAULT_X_AXIS,
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)
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y_axis = serializers.ChoiceField(
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choices=ChartAxisFields.choices(),
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required=False,
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allow_blank=True,
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allow_null=True,
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help_text=help_texts.CHART_Y_AXIS,
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default=DEFAULT_Y_AXIS,
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)
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primary_field_values = serializers.ListField(
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child=serializers.CharField(),
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help_text="List of primary field values for this segment",
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required=True,
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allow_empty=False,
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)
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secondary_category = serializers.CharField(
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help_text="Secondary category field for the chart",
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required=True,
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)
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def __init__(self, *args, **kwargs):
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with contextlib.suppress(OperationalError):
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super().__init__(*args, **kwargs)
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def to_models(self, request: Request) -> ChartRequestParams:
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groups_plots = []
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primary_field_values = self.data.get("primary_field_values")
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x_axis = self.data.get("x_axis") or DEFAULT_X_AXIS
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y_axis = self.data.get("y_axis") or DEFAULT_Y_AXIS
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static_fields = self.data.get("static_fields")
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print(f"AIDAN static_fields {static_fields}")
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topic = static_fields.get("topic")
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for primary_field_value in primary_field_values:
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for segment in self.data["segments"]:
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plot = {
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"y_axis": y_axis,
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"x_axis": primary_field_value,
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self.data.get("secondary_category"): segment[
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"secondary_field_value"
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],
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**static_fields,
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}
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groups_plots.append(plot)
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print(f"AIDAN: plots {groups_plots}")
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return ChartRequestParams(
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chart_height=DEFAULT_CHART_HEIGHT,
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chart_width=DEFAULT_CHART_WIDTH,
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file_format="svg",
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plots=groups_plots,
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request=request,
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x_axis=x_axis,
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y_axis=y_axis,
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)
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class DualCategoryTablesResponseValueSerializer(serializers.Serializer):
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label = serializers.CharField()
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value = serializers.CharField()
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in_reporting_delay_period = serializers.BooleanField()
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# Confidence intervals aren't implemented for dual category charts
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class DualCategoryTablesResponseValuesListSerializer(serializers.ListSerializer):
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child = DualCategoryTablesResponseValueSerializer()
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class DualCategoryTablesResponsePlotsListSerializer(serializers.Serializer):
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reference = serializers.CharField()
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values = DualCategoryTablesResponseValuesListSerializer()
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class DualCategoryTablesResponseSerializer(serializers.ListSerializer):
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child = DualCategoryTablesResponsePlotsListSerializer()

‎metrics/api/urls_construction.py‎

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BulkDownloadsView,
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ChartsView,
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ColdAlertViewSet,
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DualCategoryTablesView,
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DownloadsView,
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EncodedChartsView,
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HeadlinesView,
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re_path(f"^{API_PREFIX}maps/v1", MapsView.as_view()),
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re_path(f"^{API_PREFIX}tables/v4", TablesView.as_view()),
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re_path(f"^{API_PREFIX}tables/subplot/v1", TablesSubplotView.as_view()),
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re_path(f"^{API_PREFIX}tables/dual-category/v1", DualCategoryTablesView.as_view()),
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re_path(f"^{API_PREFIX}trends/v3", TrendsView.as_view()),
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]
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‎metrics/api/views/__init__.py‎

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from .headlines import HeadlinesView
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from .downloads import DownloadsView, BulkDownloadsView, SubplotDownloadsView
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from .health import HealthView
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from .tables import TablesView, TablesSubplotView
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from .tables import DualCategoryTablesView, TablesView, TablesSubplotView
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from .trends import TrendsView
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from .audit import (
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AuditAPITimeSeriesViewSet,

‎metrics/api/views/tables/__init__.py‎

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from .dual_category_tables import DualCategoryTablesView
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from .single_category_tables import TablesView
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from .subplot_tables.api_view import TablesSubplotView

‎metrics/api/views/tables/dual_category_tables.py‎

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from http import HTTPStatus
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from drf_spectacular.utils import extend_schema
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from rest_framework.response import Response
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from rest_framework.views import APIView
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from caching.private_api.decorators import cache_response
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from metrics.api.decorators.auth import require_authorisation
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from metrics.api.serializers.dual_category_tables import (
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DualCategoryTablesResponseSerializer,
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DualCategoryTablesSerializer,
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)
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from metrics.api.views.tables.common import TABLES_API_TAG
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from metrics.interfaces.plots.access import (
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DataNotFoundForAnyPlotError,
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InvalidPlotParametersError,
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)
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from metrics.interfaces.tables import access
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class DualCategoryTablesView(APIView):
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permission_classes = []
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@classmethod
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@extend_schema(
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request=DualCategoryTablesSerializer,
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responses={HTTPStatus.OK.value: DualCategoryTablesResponseSerializer},
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tags=[TABLES_API_TAG],
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)
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@require_authorisation
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def post(cls, request, *args, **kwargs):
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"""This endpoint can be used to generate chart data in tabular format.
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Multiple plots can be added as an array of objects from the request body.
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This payload takes the following set of parameters for each plot:
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| Parameter name | Description | Example | Mandatory |
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|------------------|----------------------------------------------------------------------------|--------------------------|-----------|
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| `topic` | The name of the disease/threat | COVID-19 | Yes |
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| `metric` | The name of the metric being queried for | COVID-19_deaths_ONSByDay | Yes |
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| `stratum` | The smallest subgroup a metric can be broken down into | default | No |
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| `geography` | The geography constraints to apply any data filtering to | London | No |
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| `geography_type` | The type of geographical categorisation to apply any data filtering to | Nation | No |
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| `age` | The patient age band | 0_4 | No |
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| `date_from` | The date from which to start the data slice from. In the format YYYY-MM-DD | 2023-01-01 | No |
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| `date_to` | The date to end the data slice to. In the format YYYY-MM-DD | 2023-05-01 | No |
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| `label` | The label to assign on the legend for this individual plot | Daily Covid deaths | No |
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---
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# Main errors
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There are certain combination of `topic / metric` which do not make sense.
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This is primarily because a set of `metric` values are not available for every `topic`.
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As well as this, certain `metric` names reference data of a certain profile.
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---
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## Selected metric not available for topic
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In these cases, this endpoint will return an HTTP 400 BAD REQUEST.
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For example, if a metric like `COVID-19_deaths_ONSByDay` (which is only used for `COVID-19`)
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is being asked for with a topic of `Influenza`.
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Then an HTTP 400 BAD REQUEST is returned with the following error message:
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`Influenza` does not have a corresponding metric of `COVID-19`
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---
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## Ordering of data
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Note that for tables which are `date` based i.e. where the `x_axis` field is set to `date`.
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Then the data will be returned in descending order from newest -> oldest:
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```
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| 2023-09-29 | 1 |
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| 2023-09-28 | 2 |
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| 2023-09-27 | 3 |
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```
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For tables which **not** `date` based i.e. where the `x_axis` field is set to something like `age`.
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Then the data will be returned in ascending order:
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```
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| 00 - 04 | 1 |
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| 05 - 09 | 2 |
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| 10 - 14 | 3 |
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```
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"""
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print(f"AIDAN: serialising {request.data}")
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request_serializer = DualCategoryTablesSerializer(data=request.data)
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print(f"AIDAN: validating serialiser")
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request_serializer.is_valid(raise_exception=True)
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print(f"AIDAN: converting to models")
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request_params = request_serializer.to_models(request=request)
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try:
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print(f"AIDAN: generating table")
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tabular_data: list[dict[str, str]] = access.generate_table_for_full_plots(
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request_params=request_params
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)
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except (InvalidPlotParametersError, DataNotFoundForAnyPlotError) as error:
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print(f"AIDAN: error due to {error}")
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return Response(
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status=HTTPStatus.BAD_REQUEST, data={"error_message": str(error)}
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)
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return Response(tabular_data)

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