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https://github.com/GSA/notifications-api.git
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648490bf62
We are starting to see lots of 100.0%s in the current table and we think this looks suspiciously too good so think it is beneficial to change it to be 2dp such that we get a few more non 100.0% values. For the admin app to be able to show things to 2dp, we need to give at least 2dp of accuracy otherwise we are losing 1dp of granularity. The approach is to just give all the granularity available by returning the exact result from the DB and then the admin can choose how many dps to use.
93 lines
3.4 KiB
Python
93 lines
3.4 KiB
Python
from datetime import datetime
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from flask import Blueprint, jsonify, request
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from app.dao.fact_notification_status_dao import (
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get_total_notifications_for_date_range,
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)
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from app.dao.fact_processing_time_dao import (
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get_processing_time_percentage_for_date_range,
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)
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from app.dao.services_dao import get_live_services_with_organisation
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from app.errors import register_errors
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from app.performance_dashboard.performance_dashboard_schema import (
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performance_dashboard_request,
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)
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from app.schema_validation import validate
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performance_dashboard_blueprint = Blueprint('performance_dashboard', __name__, url_prefix='/performance-dashboard')
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register_errors(performance_dashboard_blueprint)
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@performance_dashboard_blueprint.route('')
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def get_performance_dashboard():
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# All statistics are as of last night this matches the existing performance platform
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# and avoids the need to query notifications.
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if request.args:
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# Is it ok to reuse this? - should probably create a new one
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validate(request.args, performance_dashboard_request)
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# If start and end date are not set, we are expecting today's stats.
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today = str(datetime.utcnow().date())
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start_date = datetime.strptime(request.args.get('start_date', today), '%Y-%m-%d').date()
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end_date = datetime.strptime(request.args.get('end_date', today), '%Y-%m-%d').date()
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total_for_all_time = get_total_notifications_for_date_range(start_date=None, end_date=None)
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total_notifications, emails, sms, letters = transform_results_into_totals(total_for_all_time)
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totals_for_date_range = get_total_notifications_for_date_range(start_date=start_date, end_date=end_date)
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processing_time_results = get_processing_time_percentage_for_date_range(start_date=start_date, end_date=end_date)
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services = get_live_services_with_organisation()
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stats = {
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"total_notifications": total_notifications,
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"email_notifications": emails,
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"sms_notifications": sms,
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"letter_notifications": letters,
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"notifications_by_type": transform_into_notification_by_type_json(totals_for_date_range),
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"processing_time": transform_processing_time_results_to_json(processing_time_results),
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"live_service_count": len(services),
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"services_using_notify": transform_services_to_json(services)
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}
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return jsonify(stats)
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def transform_results_into_totals(total_notifications_results):
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total_notifications = 0
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emails = 0
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sms = 0
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letters = 0
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for x in total_notifications_results:
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total_notifications += x.emails
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total_notifications += x.sms
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total_notifications += x.letters
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emails += x.emails
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sms += x.sms
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letters += x.letters
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return total_notifications, emails, sms, letters
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def transform_into_notification_by_type_json(total_notifications):
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j = []
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for x in total_notifications:
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j.append({"date": x.bst_date, "emails": x.emails, "sms": x.sms, "letters": x.letters})
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return j
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def transform_processing_time_results_to_json(processing_time_results):
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j = []
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for x in processing_time_results:
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j.append({"date": x.date, "percentage_under_10_seconds": x.percentage})
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return j
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def transform_services_to_json(services_results):
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j = []
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for x in services_results:
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j.append({"service_id": x.service_id, "service_name": x.service_name,
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"organisation_id": x.organisation_id, "organisation_name": x.organisation_name}
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)
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return j
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