846 lines
27 KiB
Python
846 lines
27 KiB
Python
# """
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# Viewflow workflows for analytics app.
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# Provides report generation, dashboard management, and data analysis workflows.
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# """
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#
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# from viewflow import Flow, lock
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# from viewflow.base import this, flow_func
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# from viewflow.contrib import celery
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# from viewflow.decorators import flow_view
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# from viewflow.fields import CharField, ModelField
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# from viewflow.forms import ModelForm
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# from viewflow.views import CreateProcessView, UpdateProcessView
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# from viewflow.models import Process, Task
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# from django.contrib.auth.models import User
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# from django.urls import reverse_lazy
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# from django.utils import timezone
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# from django.db import transaction
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# from django.core.mail import send_mail
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#
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# from .models import Dashboard, DashboardWidget, DataSource, Report, ReportExecution, MetricDefinition, MetricValue
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# from .views import (
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# ReportGenerationView, DashboardCreationView, DataSourceConfigurationView,
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# MetricCalculationView, AnalysisView, VisualizationView, DistributionView,
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# SchedulingView, QualityAssuranceView, PerformanceOptimizationView
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# )
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#
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#
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# class ReportGenerationProcess(Process):
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# """
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# Viewflow process model for report generation
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# """
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# report = ModelField(Report, help_text='Associated report')
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#
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# # Process status tracking
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# report_requested = models.BooleanField(default=False)
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# data_extracted = models.BooleanField(default=False)
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# data_processed = models.BooleanField(default=False)
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# report_generated = models.BooleanField(default=False)
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# quality_checked = models.BooleanField(default=False)
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# report_distributed = models.BooleanField(default=False)
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# generation_completed = models.BooleanField(default=False)
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#
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# class Meta:
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# verbose_name = 'Report Generation Process'
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# verbose_name_plural = 'Report Generation Processes'
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#
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#
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# class ReportGenerationFlow(Flow):
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# """
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# Report Generation Workflow
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#
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# This flow manages automated report generation including
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# data extraction, processing, quality checks, and distribution.
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# """
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#
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# process_class = ReportGenerationProcess
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#
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# # Flow definition
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# start = (
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# flow_func(this.start_report_generation)
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# .Next(this.request_report)
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# )
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#
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# request_report = (
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# flow_view(ReportGenerationView)
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# .Permission('analytics.can_generate_reports')
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# .Next(this.extract_data)
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# )
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#
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# extract_data = (
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# flow_func(this.perform_data_extraction)
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# .Next(this.process_data)
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# )
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#
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# process_data = (
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# flow_func(this.perform_data_processing)
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# .Next(this.generate_report)
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# )
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#
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# generate_report = (
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# flow_func(this.create_report_output)
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# .Next(this.check_quality)
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# )
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#
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# check_quality = (
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# flow_view(QualityAssuranceView)
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# .Permission('analytics.can_check_quality')
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# .Next(this.distribute_report)
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# )
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#
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# distribute_report = (
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# flow_view(DistributionView)
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# .Permission('analytics.can_distribute_reports')
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# .Next(this.complete_generation)
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# )
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#
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# complete_generation = (
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# flow_func(this.finalize_report_generation)
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# .Next(this.end)
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# )
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#
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# end = flow_func(this.end_report_generation)
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#
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# # Flow functions
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# def start_report_generation(self, activation):
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# """Initialize the report generation process"""
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# process = activation.process
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# report = process.report
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#
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# # Create report execution record
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# execution = ReportExecution.objects.create(
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# report=report,
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# execution_type='MANUAL',
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# status='PENDING'
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# )
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#
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# # Send generation notification
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# self.notify_generation_start(report, execution)
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#
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# def perform_data_extraction(self, activation):
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# """Extract data from configured sources"""
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# process = activation.process
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# report = process.report
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#
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# # Extract data from all configured sources
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# extracted_data = self.extract_report_data(report)
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#
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# # Mark data extracted
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# process.data_extracted = True
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# process.save()
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#
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# # Store extracted data
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# self.store_extracted_data(report, extracted_data)
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#
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# def perform_data_processing(self, activation):
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# """Process and transform extracted data"""
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# process = activation.process
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# report = process.report
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#
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# # Process data according to report configuration
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# processed_data = self.process_report_data(report)
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#
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# # Mark data processed
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# process.data_processed = True
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# process.save()
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#
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# # Store processed data
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# self.store_processed_data(report, processed_data)
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#
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# def create_report_output(self, activation):
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# """Generate report output in specified format"""
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# process = activation.process
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# report = process.report
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#
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# # Generate report in configured format
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# report_output = self.generate_report_output(report)
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#
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# # Mark report generated
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# process.report_generated = True
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# process.save()
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#
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# # Store report output
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# self.store_report_output(report, report_output)
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#
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# def finalize_report_generation(self, activation):
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# """Finalize the report generation process"""
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# process = activation.process
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# report = process.report
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#
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# # Update report execution status
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# execution = ReportExecution.objects.filter(
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# report=report,
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# status='RUNNING'
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# ).first()
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#
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# if execution:
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# execution.status = 'COMPLETED'
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# execution.completed_at = timezone.now()
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# execution.save()
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#
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# # Mark generation completed
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# process.generation_completed = True
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# process.save()
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#
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# # Send completion notifications
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# self.notify_generation_completion(report)
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#
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# # Schedule next execution if recurring
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# self.schedule_next_execution(report)
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#
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# def end_report_generation(self, activation):
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# """End the report generation workflow"""
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# process = activation.process
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#
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# # Generate generation summary
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# self.generate_generation_summary(process.report)
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#
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# # Helper methods
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# def notify_generation_start(self, report, execution):
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# """Notify report generation start"""
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# analytics_team = User.objects.filter(groups__name='Analytics Team')
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# for staff in analytics_team:
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# send_mail(
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# subject=f'Report Generation Started: {report.name}',
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# message=f'Report generation process started for "{report.name}".',
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# from_email='analytics@hospital.com',
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# recipient_list=[staff.email],
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# fail_silently=True
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# )
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#
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# def extract_report_data(self, report):
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# """Extract data from report sources"""
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# # This would implement data extraction logic
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# return {'status': 'extracted', 'records': 1000}
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#
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# def store_extracted_data(self, report, data):
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# """Store extracted data"""
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# # This would store extracted data
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# pass
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#
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# def process_report_data(self, report):
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# """Process and transform report data"""
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# # This would implement data processing logic
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# return {'status': 'processed', 'records': 1000}
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#
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# def store_processed_data(self, report, data):
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# """Store processed data"""
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# # This would store processed data
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# pass
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#
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# def generate_report_output(self, report):
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# """Generate report output"""
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# # This would generate report in specified format
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# return {'status': 'generated', 'file_path': '/reports/output.pdf'}
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#
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# def store_report_output(self, report, output):
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# """Store report output"""
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# # This would store report output
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# pass
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#
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# def notify_generation_completion(self, report):
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# """Notify report generation completion"""
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# # Notify report subscribers
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# for subscriber in report.subscribers.all():
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# if subscriber.email:
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# send_mail(
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# subject=f'Report Ready: {report.name}',
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# message=f'Your report "{report.name}" is ready for download.',
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# from_email='analytics@hospital.com',
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# recipient_list=[subscriber.email],
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# fail_silently=True
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# )
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#
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# def schedule_next_execution(self, report):
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# """Schedule next report execution if recurring"""
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# if report.is_scheduled and report.schedule_config:
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# # Schedule next execution
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# schedule_report_execution.apply_async(
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# args=[report.report_id],
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# countdown=report.schedule_config.get('interval', 86400)
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# )
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#
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# def generate_generation_summary(self, report):
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# """Generate report generation summary"""
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# # This would generate generation summary
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# pass
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#
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#
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# class DashboardManagementProcess(Process):
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# """
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# Viewflow process model for dashboard management
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# """
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# dashboard = ModelField(Dashboard, help_text='Associated dashboard')
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#
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# # Process status tracking
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# dashboard_requested = models.BooleanField(default=False)
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# data_sources_configured = models.BooleanField(default=False)
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# widgets_created = models.BooleanField(default=False)
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# layout_configured = models.BooleanField(default=False)
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# permissions_set = models.BooleanField(default=False)
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# dashboard_tested = models.BooleanField(default=False)
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# dashboard_deployed = models.BooleanField(default=False)
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# management_completed = models.BooleanField(default=False)
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#
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# class Meta:
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# verbose_name = 'Dashboard Management Process'
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# verbose_name_plural = 'Dashboard Management Processes'
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#
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#
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# class DashboardManagementFlow(Flow):
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# """
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# Dashboard Management Workflow
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#
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# This flow manages dashboard creation, configuration,
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# and deployment including widgets and data sources.
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# """
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#
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# process_class = DashboardManagementProcess
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#
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# # Flow definition
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# start = (
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# flow_func(this.start_dashboard_management)
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# .Next(this.request_dashboard)
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# )
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#
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# request_dashboard = (
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# flow_view(DashboardCreationView)
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# .Permission('analytics.can_create_dashboards')
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# .Next(this.configure_data_sources)
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# )
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#
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# configure_data_sources = (
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# flow_view(DataSourceConfigurationView)
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# .Permission('analytics.can_configure_data_sources')
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# .Next(this.create_widgets)
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# )
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#
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# create_widgets = (
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# flow_func(this.setup_dashboard_widgets)
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# .Next(this.configure_layout)
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# )
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#
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# configure_layout = (
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# flow_func(this.setup_dashboard_layout)
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# .Next(this.set_permissions)
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# )
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#
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# set_permissions = (
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# flow_func(this.configure_dashboard_permissions)
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# .Next(this.test_dashboard)
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# )
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#
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# test_dashboard = (
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# flow_func(this.perform_dashboard_testing)
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# .Next(this.deploy_dashboard)
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# )
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#
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# deploy_dashboard = (
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# flow_func(this.deploy_dashboard_to_production)
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# .Next(this.complete_management)
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# )
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#
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# complete_management = (
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# flow_func(this.finalize_dashboard_management)
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# .Next(this.end)
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# )
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#
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# end = flow_func(this.end_dashboard_management)
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#
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# # Flow functions
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# def start_dashboard_management(self, activation):
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# """Initialize the dashboard management process"""
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# process = activation.process
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# dashboard = process.dashboard
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#
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# # Send dashboard creation notification
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# self.notify_dashboard_creation(dashboard)
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#
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# def setup_dashboard_widgets(self, activation):
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# """Setup dashboard widgets"""
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# process = activation.process
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# dashboard = process.dashboard
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#
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# # Create default widgets based on dashboard type
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# self.create_default_widgets(dashboard)
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#
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# # Mark widgets created
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# process.widgets_created = True
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# process.save()
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#
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# def setup_dashboard_layout(self, activation):
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# """Setup dashboard layout"""
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# process = activation.process
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# dashboard = process.dashboard
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#
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# # Configure dashboard layout
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# self.configure_layout_settings(dashboard)
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#
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# # Mark layout configured
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# process.layout_configured = True
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# process.save()
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#
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# def configure_dashboard_permissions(self, activation):
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# """Configure dashboard permissions"""
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# process = activation.process
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# dashboard = process.dashboard
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#
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# # Set up access permissions
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# self.setup_access_permissions(dashboard)
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#
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# # Mark permissions set
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# process.permissions_set = True
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# process.save()
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#
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# def perform_dashboard_testing(self, activation):
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# """Perform dashboard testing"""
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# process = activation.process
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# dashboard = process.dashboard
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#
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# # Test dashboard functionality
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# test_results = self.test_dashboard_functionality(dashboard)
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#
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# # Mark dashboard tested
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# process.dashboard_tested = True
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# process.save()
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#
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# # Store test results
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# self.store_test_results(dashboard, test_results)
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#
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# def deploy_dashboard_to_production(self, activation):
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# """Deploy dashboard to production"""
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# process = activation.process
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# dashboard = process.dashboard
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#
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# # Deploy dashboard
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# self.deploy_dashboard(dashboard)
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#
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# # Mark dashboard deployed
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# process.dashboard_deployed = True
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# process.save()
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#
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# # Activate dashboard
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# dashboard.is_active = True
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# dashboard.save()
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#
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# def finalize_dashboard_management(self, activation):
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# """Finalize the dashboard management process"""
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# process = activation.process
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# dashboard = process.dashboard
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#
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# # Mark management completed
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# process.management_completed = True
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# process.save()
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#
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# # Send completion notifications
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# self.notify_dashboard_completion(dashboard)
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#
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# # Schedule dashboard refresh
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# self.schedule_dashboard_refresh(dashboard)
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#
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# def end_dashboard_management(self, activation):
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# """End the dashboard management workflow"""
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# process = activation.process
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#
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# # Generate dashboard summary
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# self.generate_dashboard_summary(process.dashboard)
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#
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# # Helper methods
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# def notify_dashboard_creation(self, dashboard):
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# """Notify dashboard creation"""
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# analytics_team = User.objects.filter(groups__name='Analytics Team')
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# for staff in analytics_team:
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# send_mail(
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# subject=f'Dashboard Creation: {dashboard.name}',
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# message=f'Dashboard creation process started for "{dashboard.name}".',
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# from_email='analytics@hospital.com',
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# recipient_list=[staff.email],
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# fail_silently=True
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# )
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#
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# def create_default_widgets(self, dashboard):
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# """Create default widgets for dashboard"""
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# # This would create default widgets based on dashboard type
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# pass
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#
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# def configure_layout_settings(self, dashboard):
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# """Configure dashboard layout settings"""
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# # This would configure layout settings
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# pass
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#
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# def setup_access_permissions(self, dashboard):
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# """Setup dashboard access permissions"""
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# # This would configure access permissions
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# pass
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#
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# def test_dashboard_functionality(self, dashboard):
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# """Test dashboard functionality"""
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# # This would test dashboard functionality
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# return {'status': 'passed', 'issues': []}
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#
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# def store_test_results(self, dashboard, results):
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# """Store dashboard test results"""
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# # This would store test results
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# pass
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#
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# def deploy_dashboard(self, dashboard):
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# """Deploy dashboard to production"""
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# # This would deploy dashboard
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# pass
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#
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# def notify_dashboard_completion(self, dashboard):
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# """Notify dashboard completion"""
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# # Notify dashboard users
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# for user in dashboard.allowed_users.all():
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# if user.email:
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# send_mail(
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# subject=f'Dashboard Available: {dashboard.name}',
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# message=f'Dashboard "{dashboard.name}" is now available.',
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# from_email='analytics@hospital.com',
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# recipient_list=[user.email],
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# fail_silently=True
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# )
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#
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# def schedule_dashboard_refresh(self, dashboard):
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# """Schedule dashboard refresh"""
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# # Schedule dashboard refresh task
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# refresh_dashboard.apply_async(
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# args=[dashboard.dashboard_id],
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# countdown=dashboard.refresh_interval
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# )
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#
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# def generate_dashboard_summary(self, dashboard):
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# """Generate dashboard summary"""
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# # This would generate dashboard summary
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# pass
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#
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#
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# class MetricCalculationProcess(Process):
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# """
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# Viewflow process model for metric calculation
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# """
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# metric_definition = ModelField(MetricDefinition, help_text='Associated metric definition')
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#
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# # Process status tracking
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# calculation_triggered = models.BooleanField(default=False)
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# data_collected = models.BooleanField(default=False)
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# metrics_calculated = models.BooleanField(default=False)
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# quality_validated = models.BooleanField(default=False)
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# thresholds_checked = models.BooleanField(default=False)
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# alerts_sent = models.BooleanField(default=False)
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# calculation_completed = models.BooleanField(default=False)
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#
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# class Meta:
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# verbose_name = 'Metric Calculation Process'
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|
# verbose_name_plural = 'Metric Calculation Processes'
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#
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#
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# class MetricCalculationFlow(Flow):
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# """
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# Metric Calculation Workflow
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#
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# This flow manages automated metric calculation including
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# data collection, calculation, validation, and alerting.
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# """
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#
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# process_class = MetricCalculationProcess
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#
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# # Flow definition
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# start = (
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# flow_func(this.start_metric_calculation)
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# .Next(this.trigger_calculation)
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# )
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#
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# trigger_calculation = (
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# flow_func(this.initiate_calculation)
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# .Next(this.collect_data)
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# )
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#
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# collect_data = (
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# flow_func(this.gather_metric_data)
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# .Next(this.calculate_metrics)
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# )
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#
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# calculate_metrics = (
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# flow_view(MetricCalculationView)
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# .Permission('analytics.can_calculate_metrics')
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# .Next(this.validate_quality)
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# )
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#
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# validate_quality = (
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# flow_func(this.perform_quality_validation)
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# .Next(this.check_thresholds)
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# )
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#
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# check_thresholds = (
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# flow_func(this.evaluate_thresholds)
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# .Next(this.send_alerts)
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# )
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#
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# send_alerts = (
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# flow_func(this.dispatch_threshold_alerts)
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# .Next(this.complete_calculation)
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# )
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#
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# complete_calculation = (
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# flow_func(this.finalize_metric_calculation)
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# .Next(this.end)
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# )
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#
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# end = flow_func(this.end_metric_calculation)
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#
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# # Flow functions
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# def start_metric_calculation(self, activation):
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# """Initialize the metric calculation process"""
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# process = activation.process
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# metric = process.metric_definition
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#
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# # Send calculation notification
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# self.notify_calculation_start(metric)
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#
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# def initiate_calculation(self, activation):
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# """Initiate metric calculation"""
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# process = activation.process
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# metric = process.metric_definition
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#
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# # Mark calculation triggered
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# process.calculation_triggered = True
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# process.save()
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#
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# # Prepare calculation environment
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# self.prepare_calculation_environment(metric)
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#
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# def gather_metric_data(self, activation):
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# """Gather data for metric calculation"""
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# process = activation.process
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# metric = process.metric_definition
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#
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# # Collect data from configured sources
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# collected_data = self.collect_calculation_data(metric)
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#
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# # Mark data collected
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# process.data_collected = True
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# process.save()
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#
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# # Store collected data
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# self.store_calculation_data(metric, collected_data)
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#
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# def perform_quality_validation(self, activation):
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# """Perform data quality validation"""
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# process = activation.process
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# metric = process.metric_definition
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#
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# # Validate data quality
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# quality_results = self.validate_data_quality(metric)
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#
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# # Mark quality validated
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# process.quality_validated = True
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# process.save()
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#
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# # Store quality results
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# self.store_quality_results(metric, quality_results)
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#
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# def evaluate_thresholds(self, activation):
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# """Evaluate metric thresholds"""
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# process = activation.process
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# metric = process.metric_definition
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#
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# # Check threshold violations
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# threshold_results = self.check_metric_thresholds(metric)
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#
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# # Mark thresholds checked
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# process.thresholds_checked = True
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# process.save()
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#
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# # Store threshold results
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# self.store_threshold_results(metric, threshold_results)
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#
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# def dispatch_threshold_alerts(self, activation):
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# """Dispatch threshold alerts"""
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# process = activation.process
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# metric = process.metric_definition
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#
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# # Send threshold alerts if needed
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# self.send_threshold_alerts(metric)
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#
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# # Mark alerts sent
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# process.alerts_sent = True
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# process.save()
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#
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# def finalize_metric_calculation(self, activation):
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# """Finalize the metric calculation process"""
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# process = activation.process
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# metric = process.metric_definition
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#
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# # Mark calculation completed
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# process.calculation_completed = True
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# process.save()
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#
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# # Send completion notifications
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# self.notify_calculation_completion(metric)
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#
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# # Schedule next calculation
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# self.schedule_next_calculation(metric)
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#
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# def end_metric_calculation(self, activation):
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# """End the metric calculation workflow"""
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# process = activation.process
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#
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# # Generate calculation summary
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# self.generate_calculation_summary(process.metric_definition)
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#
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# # Helper methods
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# def notify_calculation_start(self, metric):
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# """Notify metric calculation start"""
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# # This would notify relevant parties
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# pass
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#
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# def prepare_calculation_environment(self, metric):
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# """Prepare calculation environment"""
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# # This would prepare calculation environment
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# pass
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#
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# def collect_calculation_data(self, metric):
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# """Collect data for calculation"""
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# # This would collect data from configured sources
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# return {'status': 'collected', 'records': 1000}
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#
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# def store_calculation_data(self, metric, data):
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# """Store calculation data"""
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# # This would store calculation data
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# pass
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#
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# def validate_data_quality(self, metric):
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# """Validate data quality"""
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# # This would validate data quality
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# return {'quality_score': 95, 'issues': []}
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#
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# def store_quality_results(self, metric, results):
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# """Store quality validation results"""
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# # This would store quality results
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# pass
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#
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# def check_metric_thresholds(self, metric):
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# """Check metric thresholds"""
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# # This would check threshold violations
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# return {'violations': [], 'status': 'normal'}
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#
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# def store_threshold_results(self, metric, results):
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# """Store threshold check results"""
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# # This would store threshold results
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# pass
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#
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# def send_threshold_alerts(self, metric):
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# """Send threshold violation alerts"""
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# # This would send alerts for threshold violations
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# pass
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#
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# def notify_calculation_completion(self, metric):
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# """Notify calculation completion"""
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# # This would notify completion
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# pass
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#
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# def schedule_next_calculation(self, metric):
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# """Schedule next metric calculation"""
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# # Schedule next calculation based on aggregation period
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# if metric.aggregation_period == 'HOURLY':
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# countdown = 3600
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# elif metric.aggregation_period == 'DAILY':
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# countdown = 86400
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# else:
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# countdown = 3600 # Default to hourly
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#
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# calculate_metric.apply_async(
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# args=[metric.metric_id],
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# countdown=countdown
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# )
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#
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# def generate_calculation_summary(self, metric):
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# """Generate calculation summary"""
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# # This would generate calculation summary
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# pass
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#
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#
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# # Celery tasks for background processing
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# @celery.job
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# def schedule_report_execution(report_id):
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# """Background task to schedule report execution"""
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# try:
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# report = Report.objects.get(report_id=report_id)
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#
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# # Create report execution
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# execution = ReportExecution.objects.create(
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# report=report,
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# execution_type='SCHEDULED',
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# status='PENDING'
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# )
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#
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# # Start report generation workflow
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# # This would start the report generation workflow
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#
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# return True
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# except Exception:
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# return False
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#
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#
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# @celery.job
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# def refresh_dashboard(dashboard_id):
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# """Background task to refresh dashboard data"""
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# try:
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# dashboard = Dashboard.objects.get(dashboard_id=dashboard_id)
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#
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# # Refresh all dashboard widgets
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# for widget in dashboard.widgets.all():
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# refresh_widget_data(widget)
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#
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# # Schedule next refresh
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# refresh_dashboard.apply_async(
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# args=[dashboard_id],
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# countdown=dashboard.refresh_interval
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# )
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#
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# return True
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# except Exception:
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# return False
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#
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#
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# @celery.job
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# def calculate_metric(metric_id):
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# """Background task to calculate metric values"""
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# try:
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# metric = MetricDefinition.objects.get(metric_id=metric_id)
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#
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# # Start metric calculation workflow
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# # This would start the metric calculation workflow
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#
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# return True
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# except Exception:
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# return False
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#
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#
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# @celery.job
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# def cleanup_old_reports():
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# """Background task to cleanup old report files"""
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# try:
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# # This would cleanup old report files
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# return True
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# except Exception:
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# return False
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#
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#
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# @celery.job
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# def generate_analytics_summary():
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# """Background task to generate analytics summary"""
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# try:
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# # This would generate periodic analytics summary
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# return True
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# except Exception:
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# return False
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#
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#
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# def refresh_widget_data(widget):
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# """Helper function to refresh widget data"""
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# # This would refresh widget data
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# pass
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#
|