202 lines
6.3 KiB
JavaScript
202 lines
6.3 KiB
JavaScript
import mongoose from "mongoose";
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import { Product } from "../Products/ProductModel.js";
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import { PDStock } from "../Stock/PdStockModel.js";
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import { RDStock } from "../Stock/RdStockModel.js";
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export const getProductsWithOpenInventoryInfo = async (req, res) => {
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try {
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const { page = 1, show = 10, name, category, brand } = req.query;
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// Pagination setup
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const limit = parseInt(show, 10);
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const skip = (parseInt(page, 10) - 1) * limit;
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// Search filters
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const searchCriteria = {};
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if (name) searchCriteria.name = { $regex: name, $options: "i" };
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if (category) searchCriteria.category = mongoose.Types.ObjectId(category);
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if (brand) searchCriteria.brand = mongoose.Types.ObjectId(brand);
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// Step 1: Fetch filtered products with population
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const products = await Product.find(searchCriteria)
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.skip(skip)
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.limit(limit)
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.populate("brand", "brandName") // Populate brandName
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.populate("category", "categoryName") // Populate categoryName
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.exec();
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// Step 2: Collect all product SKUs to find corresponding PDs and RDs with stock
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const productSKUs = products.map((product) => product.SKU);
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// Step 3: Fetch all PDs with non-zero opening inventory for these products using SKU
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const pdOIs = await PDStock.aggregate([
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{ $unwind: "$products" },
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{
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$match: {
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"products.openingInventory": { $gt: 0 },
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"products.SKU": { $in: productSKUs },
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},
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},
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{
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$group: {
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_id: "$products.SKU",
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totalPdOpeningInventory: { $sum: "$products.openingInventory" },
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},
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},
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]);
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// Step 4: Fetch all RDs with non-zero opening inventory for these products using SKU
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const rdOIs = await RDStock.aggregate([
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{ $unwind: "$products" },
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{
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$match: {
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"products.openingInventory": { $gt: 0 },
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"products.SKU": { $in: productSKUs },
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},
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},
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{
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$group: {
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_id: "$products.SKU",
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totalRdOpeningInventory: { $sum: "$products.openingInventory" },
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},
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},
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]);
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// Step 5: Prepare a mapping of PD and RD copening inventories by SKU
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const pdMap = {};
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pdOIs.forEach((pd) => {
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pdMap[pd._id] = pd.totalPdOpeningInventory;
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});
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const rdMap = {};
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rdOIs.forEach((rd) => {
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rdMap[rd._id] = rd.totalRdOpeningInventory;
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});
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// Step 6: Combine product info with PD/RD counts using SKU
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const productData = products.map((product) => ({
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SKU: product.SKU,
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name: product.name,
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brand: product.brand?.brandName || "N/A", // Access brandName here
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category: product.category?.categoryName || "N/A", // Access categoryName here
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allPDs: pdMap[product.SKU] || 0,
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allRDs: rdMap[product.SKU] || 0,
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allPdAndRd: (pdMap[product.SKU] || 0) + (rdMap[product.SKU] || 0),
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}));
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// Step 7: Get total count for pagination
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const totalCount = await Product.countDocuments(searchCriteria);
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// Step 8: Respond with paginated results and total count
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res.status(200).json({
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success: true,
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data: productData,
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pagination: {
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total: totalCount,
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page: parseInt(page, 10),
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pages: Math.ceil(totalCount / limit),
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},
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});
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} catch (error) {
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res.status(500).json({ success: false, message: error.message });
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}
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};
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export const getProductsWithStockInfo = async (req, res) => {
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try {
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const { page = 1, show = 10, name, category, brand } = req.query;
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// Pagination setup
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const limit = parseInt(show, 10);
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const skip = (parseInt(page, 10) - 1) * limit;
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// Search filters
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const searchCriteria = {};
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if (name) searchCriteria.name = { $regex: name, $options: "i" };
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if (category) searchCriteria.category = mongoose.Types.ObjectId(category);
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if (brand) searchCriteria.brand = mongoose.Types.ObjectId(brand);
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// Step 1: Fetch filtered products with population
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const products = await Product.find(searchCriteria)
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.skip(skip)
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.limit(limit)
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.populate("brand", "brandName") // Populate brandName
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.populate("category", "categoryName") // Populate categoryName
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.exec();
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// Step 2: Collect all product SKUs to find corresponding PDs and RDs with stock
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const productSKUs = products.map((product) => product.SKU);
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// Step 3: Fetch all PDs with non-zero Stock for these products using SKU
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const pdStocks = await PDStock.aggregate([
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{ $unwind: "$products" },
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{
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$match: {
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"products.Stock": { $gt: 0 },
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"products.SKU": { $in: productSKUs },
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},
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},
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{
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$group: {
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_id: "$products.SKU",
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totalpdStock: { $sum: "$products.Stock" },
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},
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},
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]);
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// Step 4: Fetch all RDs with non-zero Stock for these products using SKU
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const rdStocks = await RDStock.aggregate([
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{ $unwind: "$products" },
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{
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$match: {
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"products.Stock": { $gt: 0 },
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"products.SKU": { $in: productSKUs },
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},
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},
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{
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$group: {
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_id: "$products.SKU",
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totalrdStock: { $sum: "$products.Stock" },
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},
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},
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]);
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// Step 5: Prepare a mapping of PD and RD Stocks by SKU
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const pdMap = {};
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pdStocks.forEach((pd) => {
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pdMap[pd._id] = pd.totalpdStock;
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});
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const rdMap = {};
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rdStocks.forEach((rd) => {
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rdMap[rd._id] = rd.totalrdStock;
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});
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// Step 6: Combine product info with PD/RD counts using SKU
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const productData = products.map((product) => ({
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SKU: product.SKU,
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name: product.name,
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brand: product.brand?.brandName || "N/A", // Access brandName here
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category: product.category?.categoryName || "N/A", // Access categoryName here
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allPDs: pdMap[product.SKU] || 0,
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allRDs: rdMap[product.SKU] || 0,
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allPdAndRd: (pdMap[product.SKU] || 0) + (rdMap[product.SKU] || 0),
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}));
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// Step 7: Get total count for pagination
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const totalCount = await Product.countDocuments(searchCriteria);
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// Step 8: Respond with paginated results and total count
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res.status(200).json({
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success: true,
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data: productData,
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pagination: {
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total: totalCount,
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page: parseInt(page, 10),
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pages: Math.ceil(totalCount / limit),
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},
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});
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} catch (error) {
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res.status(500).json({ success: false, message: error.message });
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}
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}; |