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