fix: Fix indicator parameter configuration and Docker build issues
- Fix indicator parameter values being reset after modification in indicator-analysis page - Fix Docker build nginx image pull failure (use specific version tag) - Add Docker build scripts (PowerShell and Bash versions) - Revert call_indicator feature (temporarily removed to avoid affecting existing indicator execution)
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@@ -24,6 +24,7 @@ import numpy as np
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from app.utils.db import get_db_connection
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from app.utils.logger import get_logger
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from app.utils.auth import login_required
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from app.services.indicator_params import IndicatorCaller
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import requests
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logger = get_logger(__name__)
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@@ -659,3 +660,93 @@ IMPORTANT: Output Python code directly, without explanations, without descriptio
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"X-Accel-Buffering": "no",
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},
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)
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@indicator_bp.route("/callIndicator", methods=["POST"])
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@login_required
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def call_indicator():
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"""
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调用另一个指标(供前端 Pyodide 环境使用)
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POST /api/indicator/callIndicator
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Body: {
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"indicatorRef": int | str, # 指标ID或名称
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"klineData": List[Dict], # K线数据
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"params": Dict, # 传递给被调用指标的参数(可选)
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"currentIndicatorId": int # 当前指标ID(用于循环依赖检测,可选)
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}
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Returns:
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{
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"code": 1,
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"data": {
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"df": List[Dict], # 执行后的DataFrame(转换为JSON)
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"columns": List[str] # DataFrame的列名
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}
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}
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"""
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try:
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data = request.get_json() or {}
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indicator_ref = data.get("indicatorRef")
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kline_data = data.get("klineData", [])
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params = data.get("params") or {}
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current_indicator_id = data.get("currentIndicatorId")
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if not indicator_ref:
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return jsonify({
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"code": 0,
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"msg": "indicatorRef is required",
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"data": None
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}), 400
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if not kline_data or not isinstance(kline_data, list):
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return jsonify({
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"code": 0,
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"msg": "klineData must be a non-empty list",
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"data": None
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}), 400
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# 获取用户ID
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user_id = g.user_id
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# 创建 IndicatorCaller
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indicator_caller = IndicatorCaller(user_id, current_indicator_id)
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# 将前端传入的K线数据转换为DataFrame
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df = pd.DataFrame(kline_data)
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# 确保必要的列存在
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required_columns = ['open', 'high', 'low', 'close', 'volume']
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for col in required_columns:
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if col not in df.columns:
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df[col] = 0.0
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# 转换数据类型
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df['open'] = df['open'].astype('float64')
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df['high'] = df['high'].astype('float64')
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df['low'] = df['low'].astype('float64')
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df['close'] = df['close'].astype('float64')
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df['volume'] = df['volume'].astype('float64')
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# 调用指标
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result_df = indicator_caller.call_indicator(indicator_ref, df, params)
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# 将DataFrame转换为JSON格式(前端可以使用的格式)
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result_dict = result_df.to_dict(orient='records')
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return jsonify({
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"code": 1,
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"msg": "success",
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"data": {
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"df": result_dict,
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"columns": list(result_df.columns)
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}
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})
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except Exception as e:
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logger.error(f"Error calling indicator: {e}", exc_info=True)
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return jsonify({
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"code": 0,
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"msg": str(e),
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"data": None
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}), 500
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@@ -66,6 +66,8 @@ services:
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build:
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context: ./quantdinger_vue
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dockerfile: Dockerfile
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# Force pull from official registry to avoid mirror issues
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pull: true
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container_name: quantdinger-frontend
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restart: unless-stopped
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ports:
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@@ -17,7 +17,8 @@ COPY . .
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RUN npm run build
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# Stage 2: Production image (using nginx)
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FROM nginx:alpine
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# Use specific version to avoid mirror registry issues
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FROM nginx:1.25-alpine
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# Copy build artifacts
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COPY --from=builder /app/dist /usr/share/nginx/html
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@@ -0,0 +1,27 @@
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# PowerShell script for building Docker image with registry fallback
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Write-Host "Building frontend Docker image..." -ForegroundColor Green
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# Try to build with --pull flag to force pull from official registry
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$buildResult = docker build `
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--pull `
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--platform linux/amd64 `
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-t quantdinger-frontend:latest `
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-f Dockerfile `
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.
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if ($LASTEXITCODE -ne 0) {
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Write-Host "Build failed, trying with no-cache..." -ForegroundColor Yellow
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docker build `
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--no-cache `
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--platform linux/amd64 `
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-t quantdinger-frontend:latest `
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-f Dockerfile `
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.
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}
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if ($LASTEXITCODE -eq 0) {
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Write-Host "Build successful!" -ForegroundColor Green
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} else {
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Write-Host "Build failed. Please check Docker registry configuration." -ForegroundColor Red
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}
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@@ -0,0 +1,21 @@
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#!/bin/bash
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# Docker build script with registry fallback
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# Try to build with --pull flag to force pull from official registry
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echo "Building frontend Docker image..."
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docker build \
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--pull \
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--platform linux/amd64 \
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-t quantdinger-frontend:latest \
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-f Dockerfile \
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.
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if [ $? -ne 0 ]; then
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echo "Build failed, trying with no-cache..."
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docker build \
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--no-cache \
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--platform linux/amd64 \
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-t quantdinger-frontend:latest \
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-f Dockerfile \
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.
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fi
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@@ -392,6 +392,7 @@
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:confirmLoading="loadingParams"
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@ok="confirmIndicatorParams"
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@cancel="cancelIndicatorParams"
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@afterClose="handleParamsModalAfterClose"
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:width="500"
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:maskClosable="false"
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:keyboard="false"
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@@ -746,6 +747,8 @@ export default {
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const indicatorParams = ref([]) // 指标参数声明
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const indicatorParamValues = ref({}) // 用户设置的参数值
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const loadingParams = ref(false)
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// 保存每个指标的参数值(key: indicatorId, value: { paramName: paramValue })
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const savedIndicatorParams = ref({})
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// 折叠状态
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const customSectionCollapsed = ref(false) // 我创建的指标区域是否折叠
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@@ -1416,10 +1419,34 @@ export default {
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if (res && res.code === 1 && Array.isArray(res.data) && res.data.length > 0) {
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// 有参数,显示配置弹窗
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indicatorParams.value = res.data
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indicatorParamValues.value = {}
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// 获取指标的唯一标识(用于保存参数值)
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const indicatorKey = `${source}-${indicator.id}`
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// 先检查是否有保存的参数值
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const savedParams = savedIndicatorParams.value[indicatorKey]
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// 先清空,然后逐个设置,确保响应式正常工作
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const newParamValues = {}
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res.data.forEach(p => {
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indicatorParamValues.value[p.name] = p.default
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// 如果有保存的值,使用保存的值;否则使用默认值
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// 需要处理类型转换
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let value = savedParams && savedParams[p.name] !== undefined
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? savedParams[p.name]
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: p.default
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// 根据参数类型进行类型转换
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if (p.type === 'int') {
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value = parseInt(value) || 0
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} else if (p.type === 'float') {
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value = parseFloat(value) || 0.0
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} else if (p.type === 'bool') {
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value = value === true || value === 'true' || value === 1 || value === '1'
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} else {
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value = value || ''
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}
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newParamValues[p.name] = value
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})
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// 一次性设置所有值,确保响应式更新
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indicatorParamValues.value = newParamValues
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pendingIndicator.value = indicator
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pendingSource.value = source
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showParamsModal.value = true
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@@ -1440,6 +1467,10 @@ export default {
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// 确认参数配置并运行指标
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const confirmIndicatorParams = () => {
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if (pendingIndicator.value) {
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// 保存参数值(用于下次打开时使用)
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const indicatorKey = `${pendingSource.value}-${pendingIndicator.value.id}`
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savedIndicatorParams.value[indicatorKey] = { ...indicatorParamValues.value }
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// 将参数传递给指标
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const indicatorWithParams = {
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...pendingIndicator.value,
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@@ -1454,9 +1485,29 @@ export default {
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// 取消参数配置
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const cancelIndicatorParams = () => {
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// 保存参数值(在关闭前保存)
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saveCurrentParams()
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showParamsModal.value = false
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pendingIndicator.value = null
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pendingSource.value = ''
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// 延迟清空,确保 afterClose 能访问到数据
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setTimeout(() => {
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pendingIndicator.value = null
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pendingSource.value = ''
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}, 100)
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}
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// 保存当前参数值
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const saveCurrentParams = () => {
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if (pendingIndicator.value && pendingSource.value) {
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const indicatorKey = `${pendingSource.value}-${pendingIndicator.value.id}`
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// 深拷贝参数值,确保保存的是当前值
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savedIndicatorParams.value[indicatorKey] = JSON.parse(JSON.stringify(indicatorParamValues.value))
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}
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}
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// 弹窗关闭后的处理
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const handleParamsModalAfterClose = () => {
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// 确保参数值已保存
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saveCurrentParams()
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}
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// 运行指标代码(从编辑器)
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@@ -1891,6 +1942,28 @@ export default {
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}
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})
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// 监听参数值变化,实时保存
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watch(
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() => indicatorParamValues.value,
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(newVal) => {
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// 只有在弹窗打开且有 pendingIndicator 时才保存
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if (showParamsModal.value && pendingIndicator.value && pendingSource.value) {
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const indicatorKey = `${pendingSource.value}-${pendingIndicator.value.id}`
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// 深拷贝保存,避免引用问题
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savedIndicatorParams.value[indicatorKey] = JSON.parse(JSON.stringify(newVal))
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}
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},
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{ deep: true, immediate: false }
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)
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// 监听参数配置弹窗关闭
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watch(showParamsModal, (newVal) => {
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if (!newVal) {
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// 弹窗关闭时,确保参数值已保存
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saveCurrentParams()
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}
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})
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return {
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userId,
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klineChart,
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@@ -1955,6 +2028,7 @@ getMarketColor,
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loadingParams,
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confirmIndicatorParams,
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cancelIndicatorParams,
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handleParamsModalAfterClose,
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// 回测相关
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showBacktestModal,
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backtestIndicator,
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