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Service class for managing DataSection entities, providing CRUD operations and specialized update methods for analysis sessions, plots, and conclusions.

Purpose

DataSectionService acts as a business logic layer for DataSection management, encapsulating database operations and providing a clean API for creating, retrieving, updating, and deleting data sections. It handles automatic ID generation, timestamp management, and provides specialized methods for updating specific fields like analysis sessions, generated plots, and analysis conclusions. This service is designed to be used in applications that manage data analysis workflows where sections need to be tracked, linked to analysis sessions, and updated with results.

Source Code

class DataSectionService:
    """Service for managing DataSections"""
    
    def __init__(self, db_manager: DatabaseManager):
        self.db = db_manager
    
    def create_data_section(
        self,
        owner: str,
        title: str,
        description: str = ""
    ) -> DataSection:
        """Create a new data section"""
        section_id = str(uuid.uuid4())
        
        data_section = DataSection(
            id=section_id,
            owner=owner,
            title=title,
            description=description
        )
        
        # Save the data section
        self.db.save_data_section(data_section)
        
        return data_section
    
    def get_data_section(self, section_id: str) -> Optional[DataSection]:
        """Get a data section by ID"""
        return self.db.get_data_section(section_id)
    
    def update_data_section(self, data_section: DataSection) -> bool:
        """Update a data section"""
        data_section.updated_at = datetime.now()
        return self.db.save_data_section(data_section)
    
    def get_user_data_sections(self, owner: str) -> List[DataSection]:
        """Get all data sections for a user"""
        return self.db.get_user_data_sections(owner)
    
    def update_analysis_session(self, section_id: str, session_id: str) -> bool:
        """Link a data section to an analysis session"""
        data_section = self.get_data_section(section_id)
        if data_section:
            data_section.analysis_session_id = session_id
            return self.update_data_section(data_section)
        return False
    
    def update_plots(self, section_id: str, plots: List[str]) -> bool:
        """Update the generated plots for a data section"""
        data_section = self.get_data_section(section_id)
        if data_section:
            data_section.generated_plots = plots
            return self.update_data_section(data_section)
        return False
    
    def update_conclusions(self, section_id: str, conclusions: str) -> bool:
        """Update the analysis conclusions for a data section"""
        data_section = self.get_data_section(section_id)
        if data_section:
            data_section.analysis_conclusions = conclusions
            data_section.current_content = conclusions  # Also update main content
            return self.update_data_section(data_section)
        return False
    
    def delete_data_section(self, section_id: str) -> bool:
        """Delete a data section"""
        return self.db.delete_data_section(section_id)

Parameters

Name	Type	Default	Kind
bases	-	-

Parameter Details

db_manager: An instance of DatabaseManager that handles all database persistence operations. This is the only required dependency for instantiation and must implement methods like save_data_section, get_data_section, get_user_data_sections, and delete_data_section.

Return Value

Instantiation returns a DataSectionService object. Methods return various types: create_data_section returns a DataSection object with generated UUID; get_data_section returns Optional[DataSection] (None if not found); update methods return bool indicating success/failure; get_user_data_sections returns List[DataSection]; delete_data_section returns bool indicating success.

Class Interface

Methods

Attributes

Name	Type	Description	Scope
db	DatabaseManager	Database manager instance used for all persistence operations	instance

Dependencies

• uuid
• typing
• datetime

Required Imports

import uuid
from typing import List, Optional
from datetime import datetime
from models import DataSection, DatabaseManager

Usage Example

from models import DatabaseManager, DataSection
from data_section_service import DataSectionService

# Initialize the service
db_manager = DatabaseManager()
service = DataSectionService(db_manager)

# Create a new data section
section = service.create_data_section(
    owner='user123',
    title='Sales Analysis Q1',
    description='Quarterly sales data analysis'
)

# Retrieve a data section
retrieved = service.get_data_section(section.id)

# Update analysis session
success = service.update_analysis_session(section.id, 'session_456')

# Update plots
plots = ['plot1.png', 'plot2.png']
service.update_plots(section.id, plots)

# Update conclusions
service.update_conclusions(section.id, 'Sales increased by 15%')

# Get all sections for a user
user_sections = service.get_user_data_sections('user123')

# Delete a section
service.delete_data_section(section.id)

Best Practices

• Always instantiate with a valid DatabaseManager instance that implements all required database methods
• The service automatically generates UUIDs for new sections - do not provide custom IDs
• Update methods automatically set the updated_at timestamp, so manual timestamp management is not needed
• Check return values from update and delete methods to verify operation success
• Use get_data_section before update operations to ensure the section exists
• The update_conclusions method updates both analysis_conclusions and current_content fields simultaneously
• All update methods follow a pattern: retrieve, modify, save - they handle None checks internally
• The service is stateless except for the db_manager reference, making it safe for concurrent use if the DatabaseManager is thread-safe
• Consider implementing transaction support in DatabaseManager for atomic operations across multiple updates

Tags

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class DataSectionService:
    """Service for managing DataSections"""
    
    def __init__(self, db_manager: DatabaseManager):
        self.db = db_manager
    
    def create_data_section(
        self,
        owner: str,
        title: str,
        description: str = ""
    ) -> DataSection:
        """Create a new data section"""
        section_id = str(uuid.uuid4())
        
        data_section = DataSection(
            id=section_id,
            owner=owner,
            title=title,
            description=description
        )
        
        # Save the data section
        self.db.save_data_section(data_section)
        
        return data_section
    
    def get_data_section(self, section_id: str) -> Optional[DataSection]:
        """Get a data section by ID"""
        return self.db.get_data_section(section_id)
    
    def update_data_section(self, data_section: DataSection) -> bool:
        """Update a data section"""
        data_section.updated_at = datetime.now()
        return self.db.save_data_section(data_section)
    
    def get_user_data_sections(self, owner: str) -> List[DataSection]:
        """Get all data sections for a user"""
        return self.db.get_user_data_sections(owner)
    
    def update_analysis_session(self, section_id: str, session_id: str) -> bool:
        """Link a data section to an analysis session"""
        data_section = self.get_data_section(section_id)
        if data_section:
            data_section.analysis_session_id = session_id
            return self.update_data_section(data_section)
        return False
    
    def update_plots(self, section_id: str, plots: List[str]) -> bool:
        """Update the generated plots for a data section"""
        data_section = self.get_data_section(section_id)
        if data_section:
            data_section.generated_plots = plots
            return self.update_data_section(data_section)
        return False
    
    def update_conclusions(self, section_id: str, conclusions: str) -> bool:
        """Update the analysis conclusions for a data section"""
        data_section = self.get_data_section(section_id)
        if data_section:
            data_section.analysis_conclusions = conclusions
            data_section.current_content = conclusions  # Also update main content
            return self.update_data_section(data_section)
        return False
    
    def delete_data_section(self, section_id: str) -> bool:
        """Delete a data section"""
        return self.db.delete_data_section(section_id)