A .NET 9.0 implementation of a simulated Hub Service for testing gRPC clients. This simulator provides an in-memory implementation of the Minimal Hub Service API for testing purposes. The primary purpose of this simulator is to assist in profiling and stress testing client integrations.

The Hub Service Simulator implements the core functionality described in the Minimal Hub Service protocol buffer definitions, including:

• Message submission and validation
• Event handling
• Cast/message retrieval by various criteria
• User data management

All data is stored in-memory, making it ideal for performance testing and client development without needing a full production deployment.

The simulator is organized into several projects:

• HubSimulator.Domain: Core domain models and interfaces
• HubSimulator.Service: gRPC service implementation
• HubSimulator.DataGeneration: Test data generation components

• Complete implementation of the Minimal Hub Service gRPC API
• In-memory storage for fast response times
• Realistic test data generation
• Support for pagination in queries
• Thread-safe implementation using concurrent collections
• Time-based data generation with realistic social network growth patterns

• .NET 9.0 SDK (RC2 or higher)

1. Clone the repository
2. Navigate to the root directory of the simulator
3. Build the solution:

cd HubSimulator
dotnet build

To run the simulator, you must specify the correct project to run (the Service project):

cd HubSimulator
dotnet run --project src/HubSimulator.Service

Important: You must specify the --project parameter pointing to the HubSimulator.Service project, not the solution file.

The server will start on http://localhost:5293 by default.

On startup, the simulator will generate a realistic dataset of 50,000 users over 18 months of activity. This process may take several minutes to complete. The console will display progress updates during this generation:

info: Program[0]
      Data generation: Generated user 31528/50000 - 1% complete

You can modify the data generation parameters in Program.cs if you need a smaller dataset for faster startup.

You can connect to the simulator using any gRPC client that supports the protocol buffer definitions. The simulator provides endpoints for all methods defined in the MinimalHubService interface.

1. "Couldn't find a project to run"

   • Make sure to use dotnet run --project src/HubSimulator.Service instead of just dotnet run
   • Running from the solution file (dotnet run --project HubSimulator.sln) won't work

2. Build Errors

   • Ensure you're using .NET 9.0 SDK
   • Make sure all dependencies are properly restored with dotnet restore

3. Slow Startup

   • The default configuration generates 50,000 users and their activity
   • For faster testing, modify the parameters in Program.cs to reduce the data size

4. Memory Issues

   • The simulator stores all data in memory
   • For large datasets, ensure your machine has sufficient RAM

The simulator is designed to be fast and efficient, with the following optimizations:

• Concurrent collections for thread-safe access
• Indexed lookups for common query patterns
• Efficient pagination implementation
• Minimal object copying

The simulator automatically generates test data on startup, including:

• User profiles with display names, bios, and profile pictures
• Messages (casts) from each user
• Replies to messages, forming conversation threads
• User mentions in messages
• Realistic time-based growth patterns simulating 18 months of social network activity

You can customize the test data generation by modifying the parameters in the Program.cs file.

The simulator implements the following gRPC methods:

• SubmitMessage: Submit a new message to the hub
• ValidateMessage: Validate a message without storing it
• GetEvent: Get a hub event by ID
• GetCast: Get a cast by ID
• GetCastsByFid: Get casts by user FID
• GetCastsByParent: Get cast replies
• GetUserDataByFid: Get user profile data
• GetInfo: Get hub information

Contributions are welcome! Please feel free to submit a Pull Request.

This project is licensed under the MIT License - see the LICENSE file for details.