This project contains performance benchmarks for the FSharp.Data library using BenchmarkDotNet.

• ParseSimpleJson - Parse a small simple JSON document
• ParseNestedJson - Parse a nested JSON document
• ParseGitHubJson - Parse GitHub API response (~75KB)
• ParseTwitterJson - Parse Twitter API response (~74KB)
• ParseWorldBankJson - Parse World Bank API response (~20KB)
• ToStringGitHubJson - JSON parsing + ToString()
• ToStringTwitterJson - JSON parsing + ToString()

• AccessProperties - Access JSON object properties
• GetArrayElements - Extract array elements from JSON

1. Build the project in Release mode:

   dotnet build -c Release

dotnet run -c Release

# JSON parsing benchmarks only
dotnet run -c Release -- json

# JSON conversion benchmarks only
dotnet run -c Release -- conversions

# Run only simple JSON parsing
dotnet run -c Release -- --filter "*ParseSimpleJson*"

# Run only GitHub JSON benchmarks
dotnet run -c Release -- --filter "*GitHub*"

dotnet run -c Release -- --job dry --filter "*ParseSimpleJson*"

BenchmarkDotNet will show:

• Mean: Average execution time per operation
• StdErr: Standard error of the mean
• Min/Max: Fastest and slowest execution times
• Memory: Memory allocations (when [MemoryDiagnoser] is used)

Results are saved to BenchmarkDotNet.Artifacts/ folder.

These benchmarks provide baseline measurements for:

1. JSON Parsing Performance: How fast can we parse different sizes/types of JSON?
2. Memory Allocation: How much memory is allocated during operations?
3. Regression Testing: Detect performance regressions in changes
4. Optimization Validation: Measure impact of performance improvements

1. Add new benchmark methods to existing classes or create new benchmark classes
2. Mark methods with [<Benchmark>] attribute
3. Add [<GlobalSetup>] for initialization if needed
4. Use [<Params>] for parameterized benchmarks
5. Add appropriate diagnostics like [<MemoryDiagnoser>]

Example:

[<Benchmark>]
member this.MyNewBenchmark() =
    // Your code to benchmark here
    SomeOperation()