# ═══════════════════════════════════════════════════════════════════
#  JULIA STRATEGY TEMPLATE
#  This is the exact format Claude generates for each strategy.
#  Two functions required. No module/using declarations needed —
#  all Indicators functions are pre-injected by SignalCompiler.jl.
# ═══════════════════════════════════════════════════════════════════

# ── Example: EMA Crossover Strategy ─────────────────────────────────

"""
Return parameter ranges for walk-forward grid search.
Keys must be valid Julia identifiers. Values are Float64 ranges.
"""
function get_param_grid() :: Dict{String, Vector{Float64}}
    return Dict(
        "fast_period" => [10.0, 15.0, 20.0, 25.0],
        "slow_period" => [40.0, 50.0, 60.0, 80.0],
        "atr_filter"  => [14.0],                     # single value = no optimization
    )
end

"""
Generate trading signals from OHLCV arrays.

Arguments (all same length n):
  open_p, high, low, close, volume :: Vector{Float64}
  params :: Dict{String,Float64}   — one value per key from get_param_grid()

Returns Vector{Int} of length n:
  1  = enter/hold long
  -1 = enter/hold short
  0  = flat / no position

Rules:
  - Return 0 for the first ~slow_period bars (warmup / NaN period)
  - Always use isnan() checks before comparisons
  - Signals are position signals, not entry triggers
    (engine manages entries/exits from signal transitions)
"""
function generate_signals(
    open_p :: Vector{Float64},
    high   :: Vector{Float64},
    low    :: Vector{Float64},
    close  :: Vector{Float64},
    volume :: Vector{Float64},
    params :: Dict{String, Float64},
) :: Vector{Int}

    n         = length(close)
    fast_p    = Int(round(get(params, "fast_period", 20.0)))
    slow_p    = Int(round(get(params, "slow_period", 50.0)))
    atr_p     = Int(round(get(params, "atr_filter",  14.0)))

    fast_ema  = ema(close, fast_p)
    slow_ema  = ema(close, slow_p)
    atr_vals  = atr(high, low, close, atr_p)

    signals   = zeros(Int, n)

    for i in (slow_p + 1):n
        # Skip if any indicator is NaN (still in warmup)
        isnan(fast_ema[i]) && continue
        isnan(slow_ema[i]) && continue
        isnan(atr_vals[i]) && continue

        # Optional: ATR volatility filter — only trade when market is moving
        atr_threshold = close[i] * 0.001   # 0.1% of price
        atr_vals[i] < atr_threshold && continue

        if fast_ema[i] > slow_ema[i]
            signals[i] = 1    # bullish: long
        elseif fast_ema[i] < slow_ema[i]
            signals[i] = -1   # bearish: short
        else
            signals[i] = 0    # neutral
        end
    end

    return signals
end

# ═══════════════════════════════════════════════════════════════════
#  Example 2: RSI Mean Reversion
# ═══════════════════════════════════════════════════════════════════

# function get_param_grid()
#     return Dict(
#         "rsi_period"    => [7.0, 10.0, 14.0, 21.0],
#         "oversold"      => [25.0, 30.0, 35.0],
#         "overbought"    => [65.0, 70.0, 75.0],
#         "ma_period"     => [20.0, 50.0],
#     )
# end
#
# function generate_signals(open_p, high, low, close, volume, params)
#     n          = length(close)
#     rsi_p      = Int(round(get(params, "rsi_period",  14.0)))
#     oversold   = get(params, "oversold",  30.0)
#     overbought = get(params, "overbought", 70.0)
#     ma_p       = Int(round(get(params, "ma_period",   50.0)))
#
#     rsi_vals   = rsi(close, rsi_p)
#     trend_ma   = sma(close, ma_p)
#     signals    = zeros(Int, n)
#
#     for i in (ma_p + rsi_p + 1):n
#         isnan(rsi_vals[i]) && continue
#         isnan(trend_ma[i]) && continue
#
#         # Mean reversion: buy oversold in uptrend, sell overbought in downtrend
#         if rsi_vals[i] < oversold && close[i] > trend_ma[i]
#             signals[i] = 1
#         elseif rsi_vals[i] > overbought && close[i] < trend_ma[i]
#             signals[i] = -1
#         end
#     end
#     return signals
# end