From 913e507adc7e5b3f1aecc258dcaa38097772d59e Mon Sep 17 00:00:00 2001 From: consultoria-as Date: Fri, 12 Jun 2026 06:33:48 +0000 Subject: [PATCH] feat(atlas): import catalog, customers and historical sales + viewer - Add scripts/import_atlas_data.py to load Atlas data from Excel files - Import 6,206 inventory items, 251 customers and 4,582 historical sales - Create historical_sales table in tenant DB - Add /pos/historical-sales page and /pos/api/historical-sales endpoint - Link in reports sidebar for easy access --- pos/app.py | 4 + pos/blueprints/pos_bp.py | 77 +++++++ pos/templates/historical_sales.html | 160 +++++++++++++++ pos/templates/reports.html | 10 + scripts/import_atlas_data.py | 299 ++++++++++++++++++++++++++++ 5 files changed, 550 insertions(+) create mode 100644 pos/templates/historical_sales.html create mode 100644 scripts/import_atlas_data.py diff --git a/pos/app.py b/pos/app.py index 7bf6c1d..2005966 100644 --- a/pos/app.py +++ b/pos/app.py @@ -201,6 +201,10 @@ def create_app(): def pos_marketplace_external_callback(): return render_template('marketplace_external.html') + @app.route('/pos/historical-sales') + def pos_historical_sales(): + return render_template('historical_sales.html') + @app.route('/pos/static/') def pos_static(filename): return send_from_directory('static', filename) diff --git a/pos/blueprints/pos_bp.py b/pos/blueprints/pos_bp.py index 4b43c0f..6793439 100644 --- a/pos/blueprints/pos_bp.py +++ b/pos/blueprints/pos_bp.py @@ -232,6 +232,83 @@ def list_sales(): }) +@pos_bp.route('/historical-sales', methods=['GET']) +@require_auth('pos.view') +def list_historical_sales(): + """List imported historical sales (read-only reference). + + Query params: + date_from: YYYY-MM-DD + date_to: YYYY-MM-DD + customer: partial customer name + page: int (default 1) + per_page: int (default 50, max 200) + """ + conn = get_tenant_conn(g.tenant_id) + cur = conn.cursor() + + page = int(request.args.get('page', 1)) + per_page = min(int(request.args.get('per_page', 50)), 200) + + where_clauses = ["1=1"] + params = [] + + date_from = request.args.get('date_from') + date_to = request.args.get('date_to') + customer = request.args.get('customer') + + if date_from: + where_clauses.append("sale_date >= %s") + params.append(date_from) + if date_to: + where_clauses.append("sale_date <= %s") + params.append(date_to) + if customer: + where_clauses.append("customer_name ILIKE %s") + params.append(f"%{customer}%") + + where = " AND ".join(where_clauses) + + cur.execute(f"SELECT count(*) FROM historical_sales WHERE {where}", params) + total = cur.fetchone()[0] + + cur.execute(f""" + SELECT id, external_document_id, document_no, sale_date, customer_name, + total, subtotal, amount_paid, payment_method, discount, balance, + raw_payment_code + FROM historical_sales + WHERE {where} + ORDER BY sale_date DESC, id DESC + LIMIT %s OFFSET %s + """, params + [per_page, (page - 1) * per_page]) + + rows = [] + for r in cur.fetchall(): + rows.append({ + 'id': r[0], + 'external_document_id': r[1], + 'document_no': r[2], + 'sale_date': str(r[3]) if r[3] else None, + 'customer_name': r[4], + 'total': float(r[5]) if r[5] else 0, + 'subtotal': float(r[6]) if r[6] else 0, + 'amount_paid': float(r[7]) if r[7] else 0, + 'payment_method': r[8], + 'discount': float(r[9]) if r[9] else 0, + 'balance': float(r[10]) if r[10] else 0, + 'raw_payment_code': r[11], + }) + + cur.close() + conn.close() + + total_pages = (total + per_page - 1) // per_page + return jsonify({ + 'data': rows, + 'pagination': {'page': page, 'per_page': per_page, 'total': total, 'total_pages': total_pages} + }) + + @pos_bp.route('/sales/', methods=['GET']) @require_auth('pos.view') def get_sale(sale_id): diff --git a/pos/templates/historical_sales.html b/pos/templates/historical_sales.html new file mode 100644 index 0000000..0a4b195 --- /dev/null +++ b/pos/templates/historical_sales.html @@ -0,0 +1,160 @@ + + + + + + Ventas Históricas - Atlas + + + + +
+

📊 Ventas Históricas - Atlas

+ ← Regresar al POS +
+ +
+
+
+ + +
+
+ + +
+
+ + +
+ +
+ +
+
+
Total de ventas
+
-
+
+
+
Total vendido
+
-
+
+
+
Saldo pendiente
+
-
+
+
+ +
+
Cargando...
+
+
+ + + + + diff --git a/pos/templates/reports.html b/pos/templates/reports.html index 9b17b7f..3fab3de 100644 --- a/pos/templates/reports.html +++ b/pos/templates/reports.html @@ -130,6 +130,16 @@ Reportes + + + + + + + + Ventas Históricas + +
Sistema
diff --git a/scripts/import_atlas_data.py b/scripts/import_atlas_data.py new file mode 100644 index 0000000..e8490ae --- /dev/null +++ b/scripts/import_atlas_data.py @@ -0,0 +1,299 @@ +#!/usr/bin/env python3 +""" +Import Atlas data into Nexus POS tenant_refaccionaria_atlas. + +Sources (expected in /home/): + - Articulos Atlas.xlsx -> inventory catalog (stock = 0) + - Clientes.xlsx -> customers + - Historico V.xlsx -> historical_sales (read-only reference) +""" + +import os +import sys +import re +from datetime import datetime +from decimal import Decimal + +import psycopg2 +import pandas as pd + +BASE_DIR = "/home" +TENANT_DB = "tenant_refaccionaria_atlas" + + +def get_tenant_conn(): + dsn = os.environ.get("TENANT_DB_URL", f"postgresql://postgres@localhost/{TENANT_DB}") + return psycopg2.connect(dsn) + + +def normalize_text(val, max_len=None): + if pd.isna(val): + return None + s = str(val).strip() + if s in ("", "nan", "None"): + return None + if max_len: + s = s[:max_len] + return s + + +def normalize_price(val): + if pd.isna(val): + return Decimal("0") + try: + return Decimal(str(float(val))).quantize(Decimal("0.01")) + except (ValueError, TypeError): + return Decimal("0") + + +def clean_part_number(val): + s = normalize_text(val, max_len=100) + if not s: + return None + # Remove problematic chars but keep basic alphanumeric + dash/underscore + s = re.sub(r"[^\w\-./]", "", s) + return s[:100] or None + + +def import_inventory(conn): + path = os.path.join(BASE_DIR, "Articulos Atlas.xlsx") + df = pd.read_excel(path) + print(f"[inventory] Read {len(df)} rows from {path}") + + cur = conn.cursor() + inserted = 0 + skipped_dup = 0 + seen = set() + + for _, row in df.iterrows(): + part_number = clean_part_number(row.get("Clave")) + if not part_number: + continue + if part_number in seen: + skipped_dup += 1 + continue + seen.add(part_number) + + name = normalize_text(row.get("Producto"), max_len=300) or part_number + description = normalize_text(row.get("Nombre Alterno"), max_len=500) + category = normalize_text(row.get("Categoría 1"), max_len=100) + subcategory = normalize_text(row.get("Categoría 2"), max_len=100) + unit = normalize_text(row.get("Unidad"), max_len=20) + barcode = clean_part_number(row.get("Código de barras")) + price = normalize_price(row.get("Precio lista")) + + # Concatenate category info into description if present + extra_info = " | ".join(filter(None, [category, subcategory, unit])) + if extra_info: + description = f"{description or ''} [{extra_info}]".strip() if description else f"[{extra_info}]" + + cur.execute( + """ + INSERT INTO inventory + (part_number, name, description, cost, price_1, tax_rate, + unit, barcode, brand, is_active) + VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s) + ON CONFLICT (part_number) DO NOTHING + RETURNING id + """, + ( + part_number, + name, + description, + Decimal("0"), + price, + Decimal("0.16"), + unit, + barcode, + category, + True, + ), + ) + if cur.fetchone(): + inserted += 1 + + conn.commit() + cur.close() + print(f"[inventory] Inserted: {inserted}, Duplicates skipped: {skipped_dup}") + + +def import_customers(conn): + path = os.path.join(BASE_DIR, "Clientes.xlsx") + df = pd.read_excel(path) + print(f"[customers] Read {len(df)} rows from {path}") + + cur = conn.cursor() + inserted = 0 + skipped = 0 + + for _, row in df.iterrows(): + name = normalize_text(row.get("Empresa"), max_len=200) + if not name: + skipped += 1 + continue + + # Skip generic "Publico" row if it has no real name + if name.lower() in ("publico", "publico en general", "público", "público en general"): + skipped += 1 + continue + + credit_limit = normalize_price(row.get("Límite de crédito")) + customer_type = normalize_text(row.get("Tipo de cliente"), max_len=50) + segment = normalize_text(row.get("Segmento"), max_len=50) + payment_terms = normalize_text(row.get("Condiciones de Pago"), max_len=100) + notes = " | ".join(filter(None, [customer_type, segment, payment_terms])) + + # Avoid duplicates by name + cur.execute("SELECT 1 FROM customers WHERE name = %s LIMIT 1", (name,)) + if cur.fetchone(): + skipped += 1 + continue + + cur.execute( + """ + INSERT INTO customers + (name, razon_social, credit_limit, price_tier, is_active) + VALUES (%s, %s, %s, %s, %s) + RETURNING id + """, + ( + name, + name, + credit_limit, + 1, + True, + ), + ) + if cur.fetchone(): + inserted += 1 + + conn.commit() + cur.close() + print(f"[customers] Inserted: {inserted}, Skipped: {skipped}") + + +def create_historical_sales_table(conn): + cur = conn.cursor() + cur.execute( + """ + CREATE TABLE IF NOT EXISTS historical_sales ( + id SERIAL PRIMARY KEY, + external_document_id VARCHAR(50), + document_no VARCHAR(50), + sale_date DATE, + customer_name VARCHAR(200), + total NUMERIC(12,2), + subtotal NUMERIC(12,2), + amount_paid NUMERIC(12,2), + payment_method VARCHAR(50), + discount NUMERIC(12,2) DEFAULT 0, + balance NUMERIC(12,2) DEFAULT 0, + raw_payment_code VARCHAR(20), + created_at TIMESTAMPTZ DEFAULT NOW() + ); + + CREATE INDEX IF NOT EXISTS idx_historical_sales_date + ON historical_sales(sale_date); + CREATE INDEX IF NOT EXISTS idx_historical_sales_customer + ON historical_sales(customer_name); + CREATE INDEX IF NOT EXISTS idx_historical_sales_document + ON historical_sales(document_no); + """ + ) + conn.commit() + cur.close() + + +def payment_label(code): + mapping = { + "1": "Efectivo", + "3": "Tarjeta", + "4": "Transferencia", + "6": "Cheque", + "28": "Crédito", + "99": "Por definir", + } + return mapping.get(str(code).strip(), f"Código {code}") + + +def import_historical_sales(conn): + path = os.path.join(BASE_DIR, "Historico V.xlsx") + df = pd.read_excel(path) + print(f"[historical_sales] Read {len(df)} rows from {path}") + + create_historical_sales_table(conn) + + cur = conn.cursor() + inserted = 0 + + for _, row in df.iterrows(): + doc_id = normalize_text(row.get("ID Documento"), max_len=50) + doc_no = normalize_text(row.get("Documento No."), max_len=50) + + fecha = row.get("Fecha") + if pd.isna(fecha): + sale_date = None + else: + try: + sale_date = pd.to_datetime(fecha).date() + except Exception: + sale_date = None + + customer = normalize_text(row.get("Cliente"), max_len=200) + total = normalize_price(row.get("Total")) + subtotal = normalize_price(row.get("SubTotal")) + paid = normalize_price(row.get("Total Pagado")) + discount = normalize_price(row.get("Descuento")) + balance = normalize_price(row.get("Saldo")) + raw_payment = normalize_text(row.get("Forma de Pago"), max_len=20) + payment_label_str = payment_label(raw_payment) if raw_payment else None + + cur.execute( + """ + INSERT INTO historical_sales + (external_document_id, document_no, sale_date, customer_name, + total, subtotal, amount_paid, payment_method, discount, balance, + raw_payment_code) + VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s) + ON CONFLICT DO NOTHING + """, + ( + doc_id, + doc_no, + sale_date, + customer, + total, + subtotal, + paid, + payment_label_str, + discount, + balance, + raw_payment, + ), + ) + inserted += cur.rowcount + + conn.commit() + cur.close() + print(f"[historical_sales] Inserted: {inserted}") + + +def main(): + print(f"Connecting to tenant {TENANT_DB}...") + conn = get_tenant_conn() + + try: + import_inventory(conn) + import_customers(conn) + import_historical_sales(conn) + print("\nImport completed successfully.") + except Exception as e: + print(f"ERROR: {e}") + conn.rollback() + raise + finally: + conn.close() + + +if __name__ == "__main__": + main()