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URL: http://github.com/allmonday/rapid-development-pattern/tree/master/benchmark

rapid-development-pattern/benchmark at master · allmonday/rapid-development-pattern · GitHub
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README.md

GraphQL Benchmark: pydantic-resolve vs Strawberry

Performance comparison between pydantic-resolve GraphQL and Strawberry GraphQL.

Quick Start

# Install dependencies
pip install strawberry-graphql[fastapi] matplotlib jinja2

# Run full benchmark
python benchmark/run_benchmark.py

# Run quick test (10 iterations)
python benchmark/run_benchmark.py --quick

Output

  • benchmark/results/benchmark_report.html - Interactive HTML report
  • benchmark/results/charts/*.png - Comparison charts

Test Scenarios

Scenario Description
simple_* Single table queries
one_to_one Task -> Owner relationship
one_to_many Team -> Sprints/Users
nested_2_layers Team -> Sprints -> Stories
nested_3_layers Team -> Sprints -> Stories -> Tasks
nested_4_layers Deep nesting with owners
concurrent_* Parallel request handling

Metrics

  • Response Time: Mean, Median, P95, P99 (ms)
  • Memory Usage: Peak memory (MB)
  • Throughput: Requests/second (concurrent tests)

Implementation Details

pydantic-resolve

  • Uses GraphQLHandler from pydantic_resolve.graphql
  • DataLoader via aiodataloader
  • Entity-First architecture

Strawberry

  • Uses strawberry.Schema with strawberry.dataloader
  • FastAPI integration via strawberry.fastapi.GraphQLRouter
  • Field-level resolvers
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