Building the Bulk Upload System¶

Our bulk upload system combines efficient client-side processing with intuitive user interaction. Here's how we've architected the solution to handle large-scale delivery processing effectively, ensuring both performance and reliability.

System Architecture¶

The heart of our system lies in its carefully orchestrated components, each playing a crucial role in the delivery management process:

graph TD
    subgraph Client Side
    A[File Upload] --> B[CSV Parser]
    B --> C[Validator]
    C --> D[Route Optimizer]
    D --> E[Map View]
    end

    subgraph API Layer
    F[Geocoding API] --> G[Address Validator]
    H[Provider API] --> I[Route Calculator]
    end

    C --> F
    D --> H

    style A fill:#9cf,stroke:#333,stroke-width:2px
    style B fill:#9cf,stroke:#333,stroke-width:2px
    style C fill:#9cf,stroke:#333,stroke-width:2px
    style D fill:#9cf,stroke:#333,stroke-width:2px
    style E fill:#9cf,stroke:#333,stroke-width:2px

This architecture reflects our commitment to responsive user experience. Notice how the client-side components handle immediate user interactions, while the API layer provides essential services without blocking the interface. The flow from file upload through to map view creates a seamless experience, with each step building on the validation and processing of the previous one.

Core Components¶

File Upload System¶

interface FileUploadProps {
  onUpload: (file: File) => Promise<void>;
  onValidate: (data: OrderData[]) => ValidationResult;
  maxFileSize: number;
}

The file upload component is the user's first point of interaction. We've designed it to provide immediate feedback and validation, following a clear state progression:

stateDiagram-v2
    [*] --> Idle
    Idle --> Validating: File Selected
    Validating --> Processing: Valid
    Validating --> Error: Invalid
    Processing --> Complete: Success
    Processing --> Error: Failure
    Error --> Idle: Reset
    Complete --> Idle: New Upload

This state machine ensures users always know where they are in the process. Notice how we handle both success and error paths gracefully, providing clear routes back to the initial state. This design prevents users from getting stuck in error states and maintains a smooth upload flow.

Route Grouping Engine¶

interface RouteGroupProps {
  orders: Order[];
  groupingStrategy: GroupingStrategy;
  onGroupingComplete: (groups: OrderGroup[]) => void;
}

Our routing system transforms raw delivery data into optimized routes through a sophisticated process:

graph LR
    A[Raw Orders] -->|Distance Matrix| B[Initial Groups]
    B -->|Optimization| C[Refined Groups]
    C -->|Constraints| D[Final Routes]

    style A fill:#bbf,stroke:#333,stroke-width:2px
    style B fill:#bbf,stroke:#333,stroke-width:2px
    style C fill:#bbf,stroke:#333,stroke-width:2px
    style D fill:#bbf,stroke:#333,stroke-width:2px

The progression from raw orders to final routes involves multiple optimization steps. We start with basic distance calculations to form initial groups, then refine these based on various constraints such as time windows and vehicle capacity. The final routes represent the optimal balance between efficiency and practical constraints.

Map Visualization¶

interface MapVisualizationProps {
  groups: OrderGroup[];
  onGroupEdit: (groupId: string, orders: Order[]) => void;
}

The map component brings our route groups to life with interactive visualization:

graph TD
    subgraph Map Features
    A[Route Display] --> B[Group Colors]
    A --> C[Interactive Markers]
    A --> D[Distance Indicators]
    end

    subgraph User Actions
    E[Drag & Drop] --> F[Group Editing]
    G[Click] --> H[Order Details]
    end

    style A fill:#f96,stroke:#333,stroke-width:2px
    style E fill:#f96,stroke:#333,stroke-width:2px
    style G fill:#f96,stroke:#333,stroke-width:2px

This visualization system combines clear visual feedback with powerful interaction capabilities. Color-coded groups help users quickly understand route assignments, while drag-and-drop functionality enables easy manual adjustments when needed. The distance indicators provide immediate feedback about the impact of any changes.

Implementation Progress¶

Our development timeline shows how we're methodically building out these features:

gantt
    title Development Timeline
    dateFormat  YYYY-MM-DD
    section Core Features
    File Upload     :done,    des1, 2024-12-01, 2024-12-10
    CSV Processing  :done,    des2, 2024-12-05, 2024-12-15
    Route Grouping  :active,  des3, 2024-12-10, 2024-12-25
    Map Integration :         des4, 2024-12-20, 2024-12-30

Notice how we've prioritized the foundational features first. The file upload and CSV processing systems are complete, providing the essential base for our route grouping work. Map integration will follow, building on the stable foundation we've established.

Performance Optimization¶

To handle large datasets efficiently, we've implemented a comprehensive optimization strategy:

graph TD
    subgraph "Processing Strategy"
    A[Chunked Processing] --> B[Web Workers]
    B --> C[Memory Management]
    end

    subgraph "Optimization Techniques"
    D[Distance Caching] --> E[Marker Clustering]
    E --> F[Progressive Loading]
    end

    style A fill:#9f9,stroke:#333,stroke-width:2px
    style D fill:#9f9,stroke:#333,stroke-width:2px

This dual approach to performance combines smart processing strategies with efficient data handling. Chunked processing and web workers keep the interface responsive even during heavy calculations, while our optimization techniques ensure smooth visualization of large datasets. The memory management system prevents performance degradation over time.

Error Handling¶

Our error management system ensures reliability through comprehensive error detection and recovery:

graph LR
    subgraph "Error Types"
    A[Validation] --> D[User Feedback]
    B[Processing] --> D
    C[System] --> D
    end

    subgraph "Recovery Actions"
    D --> E[Guided Correction]
    D --> F[Auto Recovery]
    D --> G[Manual Override]
    end

    style A fill:#f99,stroke:#333,stroke-width:2px
    style B fill:#f99,stroke:#333,stroke-width:2px
    style C fill:#f99,stroke:#333,stroke-width:2px

This system categorizes errors into three main types and provides appropriate recovery paths for each. Validation errors receive immediate feedback with correction guidance, processing errors trigger automatic recovery attempts, and system errors offer manual override options when necessary. This layered approach ensures users can always progress with their tasks.

Implementation Details¶

CSV Upload¶

Detailed information about CSV processing and validation.

Route Grouping¶

Overview of route optimization strategies.

User Experience¶

Brief notes on UX considerations.

Last Updated: 2024-12-20T06:45:46+08:00