from fastapi import APIRouter
from pydantic import BaseModel
from typing import List, Any
from problems.flower_planting.problem import FlowerPlantingProblem

router = APIRouter(
    prefix="/flower_planting",
    tags=["flower_planting"],
    responses={404: {"description": "Not found"}},
)

problem_solver = FlowerPlantingProblem()

class GenerateRequest(BaseModel):
    length: int = 10
    n: int = 0 # 0 means auto-generate challenging N

class SolveRequest(BaseModel):
    flowerbed: List[int]
    n: int
    algorithms: List[str] = ["greedy", "brute_force"]

class BenchmarkRequest(BaseModel):
    sizes: List[int] = [10, 15, 20, 25]
    algorithms: List[str] = ["greedy", "brute_force"]

@router.post("/generate")
async def generate_case(req: GenerateRequest):
    return problem_solver.generate_case(length=req.length, n=req.n)

@router.post("/solve")
async def solve_case(req: SolveRequest):
    input_data = {"flowerbed": req.flowerbed, "n": req.n}
    results = []
    
    for algo in req.algorithms:
        try:
            if algo == "brute_force" and len(req.flowerbed) > 25:
                 results.append({
                    "algorithm": algo,
                    "error": "Input too large for Brute Force (limit 25)",
                    "skipped": True
                })
                 continue

            res = problem_solver.solve(input_data, algo)
            results.append(res)
        except Exception as e:
            results.append({"algorithm": algo, "error": str(e)})
    return results

@router.post("/benchmark")
async def benchmark(req: BenchmarkRequest):
    benchmark_results = []
    for size in req.sizes:
        input_data = problem_solver.generate_case(length=size)
        
        size_result = {"size": size, "algorithms": []}
        for algo in req.algorithms:
            try:
                if algo == "brute_force" and size > 25:
                     size_result["algorithms"].append({
                        "algorithm": algo,
                        "time_seconds": None,
                        "skipped": True
                    })
                     continue
                
                res = problem_solver.solve(input_data, algo)
                size_result["algorithms"].append(res)
            except Exception as e:
                size_result["algorithms"].append({"algorithm": algo, "error": str(e)})
        
        benchmark_results.append(size_result)
    return benchmark_results