update

app.py

@@ -9,7 +9,8 @@ from ui import (
     meta,
     twitter,
     price_matching,
-    inventory
+    inventory,
+    listing_checks
 )
 
 from server import (
@@ -18,7 +19,8 @@ from server import (
     meta as meta_srv,
     twitter as twitter_srv,
     price_matching as price_matching_srv,
-    inventory as inventory_srv
+    inventory as inventory_srv,
+    listing_checks as listing_checks_srv
 )
 
 
@@ -30,6 +32,7 @@ ui = ui.page_fluid(
         twitter.ui,
         price_matching.ui,
         inventory.ui,
+        listing_checks.ui,
         title="SEO Blog Writer",
         header=ui.tags.head(
             ui.tags.link(rel='stylesheet', type='text/css', href='style.css')
@@ -44,5 +47,6 @@ def server(input, output, session):
     twitter_srv.server(input, output, session)
     price_matching_srv.server(input, output, session)
     inventory_srv.server(input, output, session)
+    listing_checks_srv.server(input, output, session)
 
 app = App(ui, server)

server/general_blog.py

@@ -28,6 +28,7 @@ async def scrape_section_content_from_url(url: str) -> str:
             await browser.close()
 
             soup = BeautifulSoup(html, "html.parser")
+            print(soup)
 
             # Match all divs and extract text
             content_blocks = soup.find_all("div")

server/inventory.py

@@ -4,10 +4,18 @@ import duckdb
 from shiny import render, reactive, ui
 from google.oauth2 import service_account
 from googleapiclient.discovery import build
+import requests
+import base64
+import xml.etree.ElementTree as ET
 from dotenv import load_dotenv
+import time
+import pandas as pd
 
 load_dotenv()
 
+WALMART_CLIENT_ID = os.getenv('WALMART_CLIENT_ID')
+WALMART_CLIENT_SECRET = os.getenv('WALMART_CLIENT_SECRET')
+
 SERVICE_ACCOUNT_JSON = json.loads(os.getenv("SERVICE_ACCOUNT_JSON"))
 GOOGLE_FOLDER_ID = os.getenv("GOOGLE_DRIVE_FOLDER_ID")
 SCOPES = [
@@ -15,6 +23,7 @@ SCOPES = [
     "https://www.googleapis.com/auth/spreadsheets.readonly"
 ]
 
+
 credentials = service_account.Credentials.from_service_account_info(SERVICE_ACCOUNT_JSON, scopes=SCOPES)
 drive_service = build("drive", "v3", credentials=credentials)
 sheets_service = build("sheets", "v4", credentials=credentials)

server/listing_checks.py

@@ -0,0 +1,251 @@
+import os
+import json
+from shiny import render, reactive, ui
+from google.oauth2 import service_account
+from googleapiclient.discovery import build
+import requests
+import base64
+import xml.etree.ElementTree as ET
+from dotenv import load_dotenv
+import time
+import pandas as pd
+import uuid
+
+load_dotenv()
+
+WALMART_CLIENT_ID = os.getenv('WALMART_CLIENT_ID')
+WALMART_CLIENT_SECRET = os.getenv('WALMART_CLIENT_SECRET')
+
+SERVICE_ACCOUNT_JSON = json.loads(os.getenv("SERVICE_ACCOUNT_JSON"))
+GOOGLE_FOLDER_ID = os.getenv("GOOGLE_DRIVE_FOLDER_ID")
+SCOPES = [
+    "https://www.googleapis.com/auth/drive.readonly",
+    "https://www.googleapis.com/auth/spreadsheets.readonly"
+]
+
+credentials = service_account.Credentials.from_service_account_info(
+    SERVICE_ACCOUNT_JSON, scopes=SCOPES
+)
+drive_service = build("drive", "v3", credentials=credentials)
+sheets_service = build("sheets", "v4", credentials=credentials)
+
+
+def get_walmart_token(client_id: str, client_secret: str) -> str:
+    auth_str = f"{client_id}:{client_secret}"
+    auth_b64 = base64.b64encode(auth_str.encode()).decode()
+
+    headers = {
+        "Authorization": f"Basic {auth_b64}",
+        "Content-Type": "application/x-www-form-urlencoded",
+        "WM_SVC.NAME": "Walmart Marketplace"
+    }
+
+    payload = {"grant_type": "client_credentials"}
+    url = "https://marketplace.walmartapis.com/v3/token"
+
+    response = requests.post(url, headers=headers, data=payload)
+
+    if response.status_code != 200:
+        raise Exception(f"Token request failed: {response.status_code}\n{response.text}")
+
+    # Parse the XML response
+    root = ET.fromstring(response.text)
+    token_elem = root.find("accessToken")
+    
+    if token_elem is None:
+        raise Exception("accessToken not found in response.")
+
+    return token_elem.text
+
+
+def get_inventory_quantity(sku: str, access_token: str) -> int:
+    url = f"https://marketplace.walmartapis.com/v3/inventory?sku={sku}"
+    headers = {
+        "Authorization": f"Bearer {access_token}",
+        "WM_SEC.ACCESS_TOKEN": access_token,
+        "WM_SVC.NAME": "Walmart Marketplace",
+        "WM_QOS.CORRELATION_ID": str(uuid.uuid4()),
+        "Accept": "application/json"
+    }
+
+    response = requests.get(url, headers=headers)
+    if response.status_code == 200:
+        return response.json().get("quantity", {}).get("amount")
+    else:
+        print(f"⚠️ Inventory fetch failed for {sku} ({response.status_code})")
+        return None
+
+
+def get_item_ids_and_quantities(access_token: str) -> pd.DataFrame:
+    url = "https://marketplace.walmartapis.com/v3/items"
+    headers = {
+        "Authorization": f"Bearer {access_token}",
+        "WM_SEC.ACCESS_TOKEN": access_token,
+        "WM_SVC.NAME": "Walmart Marketplace",
+        "WM_QOS.CORRELATION_ID": str(uuid.uuid4()),
+        "Accept": "application/json"
+    }
+
+    records = []
+    offset = 0
+    limit = 365
+    total_items = None
+    item_counter = 0
+
+    while True:
+        full_url = f"{url}?limit={limit}&offset={offset}"
+        response = requests.get(full_url, headers=headers)
+        if response.status_code != 200:
+            print(f"❌ Error {response.status_code}: {response.text}")
+            break
+
+        data = response.json()
+        if total_items is None:
+            total_items = data.get("totalItems", 0)
+            print(f"📦 Total items to process: {total_items}")
+
+        items = data.get("ItemResponse", [])
+        if not items:
+            break
+
+        for item in items:
+            item_counter += 1
+            item_name = item.get('productName')
+            sku = item.get("sku")
+            gtin = item.get("gtin")
+            qty = get_inventory_quantity(sku, access_token)
+            time.sleep(0.1)
+
+            print(f"🔢 [{item_counter}/{total_items}] gtin: {gtin} | Product: {item_name[:20]} | Qty: {qty}")
+
+            records.append({
+                'productName': item_name,
+                "gtin": gtin,
+                "quantity": qty
+            })
+
+        offset += limit
+        if offset >= total_items:
+            break
+
+    return pd.DataFrame(records)
+
+
+def list_sheets_in_folder(folder_id):
+    query = (
+        f"'{folder_id}' in parents and "
+        "mimeType = 'application/vnd.google-apps.spreadsheet' and trashed = false"
+    )
+    results = drive_service.files().list(
+        q=query, fields="files(id, name)"
+    ).execute()
+    return results.get("files", [])
+
+
+def load_sheet_as_dataframe(sheet_id, range_name="Sheet1"):
+    result = sheets_service.spreadsheets().values().get(
+        spreadsheetId=sheet_id,
+        range=range_name
+    ).execute()
+
+    values = result.get("values", [])
+    if not values:
+        return pd.DataFrame()
+
+    # First row = header
+    df = pd.DataFrame(values[1:], columns=values[0])
+    return df
+
+
+sheet_index = {}
+walmart_data = {"df": None}
+
+
+def server(input, output, session):
+    @reactive.Effect
+    def init_dropdown_from_folder():
+        global sheet_index
+        try:
+            sheets = list_sheets_in_folder(GOOGLE_FOLDER_ID)
+            sheet_index = {s['name']: s['id'] for s in sheets}
+            sheet_names = list(sheet_index.keys())
+            print(f"[DEBUG] Found {len(sheet_names)} sheets: {sheet_names}")
+
+            ui.update_select("sheet_dropdown_check", choices=sheet_names)
+
+        except Exception as e:
+            print(f"[ERROR] Failed to list folder contents: {e}")
+
+    @reactive.Effect
+    @reactive.event(input.load_walmart_data)
+    def load_walmart_data():
+        try:
+            print("[DEBUG] Getting Walmart token...")
+            token = get_walmart_token(WALMART_CLIENT_ID, WALMART_CLIENT_SECRET)
+            print("[DEBUG] Fetching Walmart inventory data...")
+            walmart_data["df"] = get_item_ids_and_quantities(token)
+            print(f"[DEBUG] Loaded {len(walmart_data['df'])} Walmart items")
+        except Exception as e:
+            print(f"[ERROR] Failed to load Walmart data: {e}")
+            walmart_data["df"] = pd.DataFrame()  # Set empty DataFrame on error
+
+    @output
+    @render.text
+    def walmart_status():
+        if walmart_data["df"] is None:
+            return "Click 'Load Walmart Data' to fetch inventory data"
+        elif len(walmart_data["df"]) == 0:
+            return "Error loading Walmart data"
+        else:
+            return f"Walmart data loaded: {len(walmart_data['df'])} items"
+
+    @output
+    @render.table
+    def results_check():
+        sheet_name = input.sheet_dropdown()
+        
+        try:
+            if not sheet_name or sheet_name not in sheet_index:
+                return pd.DataFrame({"status": ["Select a sheet to compare"]})
+            
+            if walmart_data["df"] is None:
+                return pd.DataFrame({"status": ["Loading Walmart data..."]})
+
+            print(f"[DEBUG] Loading sheet: {sheet_name}")
+            sheet_id = sheet_index[sheet_name]
+            google_df = load_sheet_as_dataframe(sheet_id)
+            
+            if google_df.empty:
+                return pd.DataFrame({"error": ["Google sheet is empty"]})
+            
+            walmart_df = walmart_data["df"]
+            
+            # Merge the data - adjust column names as needed
+            if 'walmart_gtin' in google_df.columns:
+                merged = google_df.merge(
+                    walmart_df[['gtin', 'productName', 'quantity']],
+                    left_on='walmart_gtin',
+                    right_on='gtin',
+                    how='inner'
+                )
+                
+                # Show discrepancies
+                if 'walmart_quantity' in merged.columns:
+                    discrepancies = merged[
+                        merged['walmart_quantity'].astype(int) !=
+                        merged['quantity'].astype(int)
+                    ][['productName', 'walmart_quantity', 'quantity']]
+                    
+                    if discrepancies.empty:
+                        return pd.DataFrame({
+                            "status": ["No quantity discrepancies found"]
+                        })
+                    return discrepancies
+                else:
+                    return merged[['productName', 'gtin', 'quantity']]
+            else:
+                # If no walmart_gtin column, just show the merged data
+                return walmart_df
+                
+        except Exception as e:
+            return pd.DataFrame({"error": [f"Error: {str(e)}"]})

ui/general_blog.py

@@ -4,7 +4,7 @@ ui = ui.nav_panel(
     "General Blog Writer",
 
     # Scoped URL input
-    ui.input_text("blog_url", "Enter Pokémon.com Article URL", placeholder="https://www.pokemon.com/us/pokemon-news/..."),
+    ui.input_text("blog_url", "Enter Pokémon.com Article URL", placeholder="https://www.pokemon.com/us/..."),
 
     # Scoped buttons
     ui.div(

ui/listing_checks.py

@@ -0,0 +1,22 @@
+from shiny import ui
+
+ui = ui.nav_panel(
+    "Listing Checks",
+
+    ui.input_select(
+        "sheet_dropdown_check",
+        "Select a Sheet from Folder",
+        choices=[],
+        selected=None
+    ),
+
+    ui.input_action_button(
+        "load_walmart_data",
+        "Load Walmart Data",
+        class_="btn btn-primary mb-3"
+    ),
+
+    ui.output_text_verbatim("walmart_status"),
+
+    ui.output_table("results_check", class_="mt-3")
+)