initial commit

.gitignore

@@ -0,0 +1,32 @@
+# --- python bytecode ---
+__pycache__/
+*.py[cod]
+*$py.class
+
+# --- virtual environments ---
+.venv/
+venv/
+env/
+
+# --- environment files ---
+.env
+.env.*
+*.local
+
+# --- emacs ---
+*~
+\#*\#
+.\#*
+*.elc
+
+# --- project private data ---
+/private/
+/pm/
+
+# --- django ---
+db.sqlite3
+staticfiles/
+media/
+
+# --- misc ---
+.DS_Store

scrape-giant.org

@@ -0,0 +1,83 @@
+
+
+* python setuyp
+venv install playwright, pandas
+playwright install
+* item:
+get:
+  /api/v6.0/user/369513017/order/history/detail/69a2e44a16be1142e74ad3cc
+
+headers:
+  request:
+GET /api/v6.0/user/369513017/order/history/detail/69a2e44a16be1142e74ad3cc?isInStore=true HTTP/2
+Host: giantfood.com
+User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:148.0) Gecko/20100101 Firefox/148.0
+Accept: application/json, text/plain, */*
+Accept-Language: en-US,en;q=0.9
+Accept-Encoding: gzip, deflate, br, zstd
+DNT: 1
+Sec-GPC: 1
+Connection: keep-alive
+Referer: https://giantfood.com/account/history/invoice/in-store
+Cookie: datadome=rDtvd3J2hO5AeghJMSFRRxGc6ifKCQYgMLcqPNr9rWiz2rdcXb032AY6GIZn8tUmYB96BKKbzh3_jSjEzYWLj8hDjl3oGYYAiu4jwdaxpf3vh2v4f7KH7kbqgsMWpkjt; cf_clearance=WEPyQokx9f0qoyS4Svsw4EkZ1TYOxjOwcUHspT3.rXw-1773348940-1.2.1.1-fPvERGxBlFUaBW83sUppbUWpwvFG7mZivag5vBvZb3kxUQv2WSVIV1tON0HV2n8bkVY0U8_BBl62a00Np.oJylYQcGME540gZlYEoL.gMs4WynLqApFe5BOXAEwOm01_6h6b62H90bl4ypRehVb_TXEi4qHaPLVSZhjZK_h.fv6RBqjgYch2j_8XnHe5HXvLziVjl1k2aJskozqy04KOyeHyc3OyIPTZd5On_KAzFIM; dvrctk=MnjKJVShVraEtbrBkkxWxLaZrXnIGNQlwB7QtZVPFeA=; __cflb=0H28vXMLFyydRmDMNgcPHijM6auXkCspCkuh58tVuJ3; __cf_bm=C6QbqiEvbbwdrYBpoJOkcWcedf60vcOfPfTPPbZzKbM-1773348202-1.0.1.1-cSHoYwi8ZjIHTdBItXQP_iXJdRJS6FYjFsGdl1eGHvS5pgfbcT4Lg19P6UStX.bZz1u0OXiS5ykdipPBtwP6OvZr68k4XSmjYpir05jNLhw; _dd_s=rum=0&expire=1773349846445; ppdtk=Uog72CR22mD85C7U4iZHlgOQeRmvHEYp0OdQc+0lEes1c5/LeqGT+ZUlXpSC6FpW; cartId=3820547
+Sec-Fetch-Dest: empty
+Sec-Fetch-Mode: cors
+Sec-Fetch-Site: same-origin
+Priority: u=0
+TE: trailers
+
+  response:
+HTTP/2 200 
+date: Thu, 12 Mar 2026 20:55:47 GMT
+content-type: application/json
+server: cloudflare
+cf-ray: 9db5b3a5d84aff28-IAD
+cf-cache-status: DYNAMIC
+content-encoding: gzip
+set-cookie: datadome=MXMri0hss6PlQ0_oS7gG2iMdOKnNkbDmGvOxelgN~nCcupgkJQOqjcjcgdprIaI7hSlt_w8E9Ri_RAzPFrGqtUfqAJ_szB_aNZ2FdC26qmI3870Nn4~T0vtx8Gj3dEZR; Max-Age=31536000; Domain=.giantfood.com; Path=/; Secure; SameSite=Lax
+strict-transport-security: max-age=31536000; includeSubDomains
+vary: Origin, Access-Control-Request-Method, Access-Control-Request-Headers, accept-encoding
+accept-ch: Sec-CH-UA,Sec-CH-UA-Mobile,Sec-CH-UA-Platform,Sec-CH-UA-Arch,Sec-CH-UA-Full-Version-List,Sec-CH-UA-Model,Sec-CH-Device-Memory
+x-datadome: protected
+request-context: appId=cid-v1:75750625-0c81-4f08-9f5d-ce4f73198e54
+X-Firefox-Spdy: h2
+
+* history:
+GET
+  https://giantfood.com/api/v6.0/user/369513017/order/history?filter=instore&loyaltyNumber=440155630880
+
+headers:
+  request:
+GET /api/v6.0/user/369513017/order/history?filter=instore&loyaltyNumber=440155630880 HTTP/2
+Host: giantfood.com
+User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:148.0) Gecko/20100101 Firefox/148.0
+Accept: application/json, text/plain, */*
+Accept-Language: en-US,en;q=0.9
+Accept-Encoding: gzip, deflate, br, zstd
+DNT: 1
+Sec-GPC: 1
+Connection: keep-alive
+Referer: https://giantfood.com/account/history/invoice/in-store
+Cookie: datadome=OH2XjtCoI6XjE3Qsz_b0F1YULKLatAC0Ea~VMeDGBP0N9Z~CeI3RqEbvkGmNW_VCOU~vRb6p0kqibvF2tLbWnzyAGIdO7jsC41KiYbp7USpJDnefZhIg0e1ypAugvDSw; cf_clearance=WEPyQokx9f0qoyS4Svsw4EkZ1TYOxjOwcUHspT3.rXw-1773348940-1.2.1.1-fPvERGxBlFUaBW83sUppbUWpwvFG7mZivag5vBvZb3kxUQv2WSVIV1tON0HV2n8bkVY0U8_BBl62a00Np.oJylYQcGME540gZlYEoL.gMs4WynLqApFe5BOXAEwOm01_6h6b62H90bl4ypRehVb_TXEi4qHaPLVSZhjZK_h.fv6RBqjgYch2j_8XnHe5HXvLziVjl1k2aJskozqy04KOyeHyc3OyIPTZd5On_KAzFIM; dvrctk=MnjKJVShVraEtbrBkkxWxLaZrXnIGNQlwB7QtZVPFeA=; __cflb=0H28vXMLFyydRmDMNgcPHijM6auXkCspCkuh58tVuJ3; __cf_bm=C6QbqiEvbbwdrYBpoJOkcWcedf60vcOfPfTPPbZzKbM-1773348202-1.0.1.1-cSHoYwi8ZjIHTdBItXQP_iXJdRJS6FYjFsGdl1eGHvS5pgfbcT4Lg19P6UStX.bZz1u0OXiS5ykdipPBtwP6OvZr68k4XSmjYpir05jNLhw; _dd_s=rum=0&expire=1773349842848; ppdtk=Uog72CR22mD85C7U4iZHlgOQeRmvHEYp0OdQc+0lEes1c5/LeqGT+ZUlXpSC6FpW; cartId=3820547
+Sec-Fetch-Dest: empty
+Sec-Fetch-Mode: cors
+Sec-Fetch-Site: same-origin
+Priority: u=0
+TE: trailers
+  
+
+  response:
+  HTTP/2 200 
+date: Thu, 12 Mar 2026 20:55:43 GMT
+content-type: application/json
+server: cloudflare
+cf-ray: 9db5b38f7eebff28-IAD
+cf-cache-status: DYNAMIC
+content-encoding: gzip
+set-cookie: datadome=rDtvd3J2hO5AeghJMSFRRxGc6ifKCQYgMLcqPNr9rWiz2rdcXb032AY6GIZn8tUmYB96BKKbzh3_jSjEzYWLj8hDjl3oGYYAiu4jwdaxpf3vh2v4f7KH7kbqgsMWpkjt; Max-Age=31536000; Domain=.giantfood.com; Path=/; Secure; SameSite=Lax
+strict-transport-security: max-age=31536000; includeSubDomains
+vary: Origin, Access-Control-Request-Method, Access-Control-Request-Headers, accept-encoding
+accept-ch: Sec-CH-UA,Sec-CH-UA-Mobile,Sec-CH-UA-Platform,Sec-CH-UA-Arch,Sec-CH-UA-Full-Version-List,Sec-CH-UA-Model,Sec-CH-Device-Memory
+x-datadome: protected
+request-context: appId=cid-v1:75750625-0c81-4f08-9f5d-ce4f73198e54
+X-Firefox-Spdy: h2

site/order1.json

@@ -0,0 +1 @@
+{"orderId":"69a2e44a16be1142e74ad3cc","orderDate":"2026-02-27","deliveryDate":"2026-02-27","orderTotal":27.31,"totalItemCount":20,"totalSavings":5.02,"yourSavingsTotal":5.02,"couponsDiscountsTotal":0.00,"deliveryMethod":"INSTORE","loyaltyNumber":44015563088,"paymentMethod":"CASH","items":[{"podId":0,"shipQy":3,"totalPickedWeight":0.0000,"unitPrice":0.67,"itemName":"+LEMONS","lbEachCd":"EA","groceryAmount":2.01,"primUpcCd":"4053","mvpSavings":0.00,"rewardSavings":0.00,"couponSavings":0.00,"couponPrice":0.00,"categoryId":"1","categoryDesc":"Grocery","image":{}},{"podId":0,"shipQy":2,"totalPickedWeight":0.0000,"unitPrice":2.19,"itemName":"SB SPCY BRWN MUSTARD12Z","lbEachCd":"EA","groceryAmount":4.38,"primUpcCd":"68826707533","mvpSavings":0.40,"rewardSavings":0.00,"couponSavings":0.00,"couponPrice":0.00,"categoryId":"1","categoryDesc":"Grocery","image":{}},{"podId":310343,"shipQy":2,"totalPickedWeight":0.0000,"unitPrice":0.05,"itemName":"GL BAG CHARGE","lbEachCd":"EA","groceryAmount":0.10,"primUpcCd":"81244","mvpSavings":0.00,"rewardSavings":0.00,"couponSavings":0.00,"couponPrice":0.00,"categoryId":"1","categoryDesc":"Grocery","image":{}},{"podId":793,"shipQy":1,"totalPickedWeight":0.0000,"unitPrice":3.49,"itemName":"PF CHEDDAR GLD FISH 6.6","lbEachCd":"EA","groceryAmount":3.49,"primUpcCd":"1410008547","mvpSavings":0.50,"rewardSavings":0.00,"couponSavings":0.00,"couponPrice":0.00,"categoryId":"1","categoryDesc":"Grocery","image":{"small":"https://i5.peapod.com/c/GD/GD6CA.png","medium":"https://i5.peapod.com/c/VH/VH5NX.png","large":"https://i5.peapod.com/c/K4/K4CCI.png","xlarge":"https://i5.peapod.com/c/UX/UXQM7.png"}},{"podId":396304,"shipQy":6,"totalPickedWeight":0.0000,"unitPrice":1.89,"itemName":"SB CHPD SPINACH 12Z","lbEachCd":"EA","groceryAmount":11.34,"primUpcCd":"68826759629","mvpSavings":2.34,"rewardSavings":0.00,"couponSavings":0.00,"couponPrice":0.00,"categoryId":"1","categoryDesc":"Grocery","image":{"small":"https://i5.peapod.com/c/43/43N4N.png","medium":"https://i5.peapod.com/c/GU/GUJ3V.png","large":"https://i5.peapod.com/c/GD/GDWLE.png","xlarge":"https://i5.peapod.com/c/9O/9OOJY.png"}},{"podId":187420,"shipQy":4,"totalPickedWeight":0.0000,"unitPrice":0.99,"itemName":"SB PINTO BEANS 15.5Z","lbEachCd":"EA","groceryAmount":3.96,"primUpcCd":"68826702790","mvpSavings":0.00,"rewardSavings":0.00,"couponSavings":0.00,"couponPrice":0.00,"categoryId":"1","categoryDesc":"Grocery","image":{"small":"https://i5.peapod.com/c/X9/X9AQ8.png","medium":"https://i5.peapod.com/c/KM/KMSFG.png","large":"https://i5.peapod.com/c/0R/0RM8A.png","xlarge":"https://i5.peapod.com/c/JI/JI0DP.png"}},{"podId":153510,"shipQy":2,"totalPickedWeight":0.0000,"unitPrice":3.39,"itemName":"LA BND FJT TRT 10CT11.3","lbEachCd":"EA","groceryAmount":6.78,"primUpcCd":"2733100035","mvpSavings":1.78,"rewardSavings":0.00,"couponSavings":0.00,"couponPrice":0.00,"categoryId":"1","categoryDesc":"Grocery","image":{"small":"https://i5.peapod.com/c/SO/SO2X8.png","medium":"https://i5.peapod.com/c/QI/QITJ2.png","large":"https://i5.peapod.com/c/J7/J7KRF.png","xlarge":"https://i5.peapod.com/c/MF/MFSYF.png"}}],"pup":{"storeName":"Giant Food","aholdStoreNumber":760,"storeAddress1":"6800 RICHMOND HIGHWAY","storeCity":"ALEXANDRIA","storeState":"VA","storeZipcode":"22306"},"couponsAndDiscounts":[],"orderDetails":[{"itemCd":null,"itemCdDesc":"Subtotal","priceQy":27.04},{"itemCd":null,"itemCdDesc":"Tax","priceQy":0.27}],"weeklySpecials":[{"podId":0,"itemDesc":"SB SPCY BRWN MUSTARD12Z","itemSavings":0.40},{"podId":793,"itemDesc":"PF CHEDDAR GLD FISH 6.6","itemSavings":0.50},{"podId":396304,"itemDesc":"SB CHPD SPINACH 12Z","itemSavings":2.34},{"podId":153510,"itemDesc":"LA BND FJT TRT 10CT11.3","itemSavings":1.78}],"refundOrder":false,"ebtOrder":false}

site/scrape-giant.py

@@ -0,0 +1,162 @@
+import json
+import time
+from pathlib import Path
+
+import pandas as pd
+import requests
+from playwright.sync_api import sync_playwright
+
+
+BASE = "https://giantfood.com"
+ACCOUNT_HISTORY_URL = f"{BASE}/account/history/invoice/in-store"
+
+
+def build_session_via_playwright(headless=False):
+    with sync_playwright() as p:
+        browser = p.firefox.launch(headless=headless)
+        page = browser.new_page()
+        page.goto(ACCOUNT_HISTORY_URL, wait_until="networkidle")
+
+        print("log in in the browser window, then press enter here...")
+        input()
+
+        cookies = page.context.cookies()
+        ua = page.evaluate("() => navigator.userAgent")
+        browser.close()
+
+    s = requests.Session()
+    s.headers.update({
+        "user-agent": ua,
+        "accept": "application/json, text/plain, */*",
+        "referer": ACCOUNT_HISTORY_URL,
+    })
+
+    for c in cookies:
+        # requests wants host-only-ish handling; stripping leading dot is usually fine
+        domain = c.get("domain", "").lstrip(".") or "giantfood.com"
+        s.cookies.set(
+            c["name"],
+            c["value"],
+            domain=domain,
+            path=c.get("path", "/"),
+        )
+
+    return s
+
+
+def get_history(session, user_id, loyalty_number, filter_="instore"):
+    url = f"{BASE}/api/v6.0/user/{user_id}/order/history"
+    params = {
+        "filter": filter_,
+        "loyaltyNumber": loyalty_number,
+    }
+    r = session.get(url, params=params, timeout=30)
+    r.raise_for_status()
+    return r.json()
+
+
+def get_order_detail(session, user_id, order_id, is_instore=True):
+    url = f"{BASE}/api/v6.0/user/{user_id}/order/history/detail/{order_id}"
+    params = {"isInStore": str(is_instore).lower()}
+    r = session.get(url, params=params, timeout=30)
+    r.raise_for_status()
+    return r.json()
+
+
+def flatten_orders(history_json, details_jsons):
+    orders_rows = []
+    items_rows = []
+
+    history_records = {
+        rec["orderId"]: rec
+        for rec in history_json.get("records", [])
+    }
+
+    for d in details_jsons:
+        order_id = d["orderId"]
+        hist = history_records.get(order_id, {})
+        pup = d.get("pup", {})
+
+        orders_rows.append({
+            "order_id": order_id,
+            "order_date": d.get("orderDate"),
+            "delivery_date": d.get("deliveryDate"),
+            "service_type": hist.get("serviceType"),
+            "payment_method": d.get("paymentMethod"),
+            "order_total": d.get("orderTotal"),
+            "total_item_count": d.get("totalItemCount"),
+            "total_savings": d.get("totalSavings"),
+            "your_savings_total": d.get("yourSavingsTotal"),
+            "coupons_discounts_total": d.get("couponsDiscountsTotal"),
+            "store_name": pup.get("storeName"),
+            "store_number": pup.get("aholdStoreNumber"),
+            "store_address1": pup.get("storeAddress1"),
+            "store_city": pup.get("storeCity"),
+            "store_state": pup.get("storeState"),
+            "store_zipcode": pup.get("storeZipcode"),
+            "refund_order": d.get("refundOrder"),
+            "ebt_order": d.get("ebtOrder"),
+        })
+
+        for idx, item in enumerate(d.get("items", []), start=1):
+            items_rows.append({
+                "order_id": order_id,
+                "order_date": d.get("orderDate"),
+                "line_no": idx,
+                "pod_id": item.get("podId"),
+                "upc": item.get("primUpcCd"),
+                "item_name": item.get("itemName"),
+                "category_id": item.get("categoryId"),
+                "category_desc": item.get("categoryDesc"),
+                "qty": item.get("shipQy"),
+                "unit": item.get("lbEachCd"),
+                "unit_price": item.get("unitPrice"),
+                "grocery_amount": item.get("groceryAmount"),
+                "picked_weight": item.get("totalPickedWeight"),
+                "mvp_savings": item.get("mvpSavings"),
+                "reward_savings": item.get("rewardSavings"),
+                "coupon_savings": item.get("couponSavings"),
+                "coupon_price": item.get("couponPrice"),
+            })
+
+    return pd.DataFrame(orders_rows), pd.DataFrame(items_rows)
+
+
+def main():
+    user_id = "369513017"          # move to config/env later
+    loyalty_number = "440155630880"  # move to config/env later
+
+    outdir = Path("giant_output")
+    rawdir = outdir / "raw"
+    rawdir.mkdir(parents=True, exist_ok=True)
+
+    session = build_session_via_playwright(headless=False)
+
+    history = get_history(session, user_id, loyalty_number)
+    (rawdir / "history.json").write_text(json.dumps(history, indent=2), encoding="utf-8")
+
+    details = []
+    for rec in history.get("records", []):
+        order_id = rec["orderId"]
+        print("fetching", order_id)
+        detail = get_order_detail(session, user_id, order_id, is_instore=True)
+        details.append(detail)
+        (rawdir / f"{order_id}.json").write_text(json.dumps(detail, indent=2), encoding="utf-8")
+        time.sleep(1.5)  # dont be a goblin
+
+    orders_df, items_df = flatten_orders(history, details)
+    orders_df.to_csv(outdir / "orders.csv", index=False)
+    items_df.to_csv(outdir / "items.csv", index=False)
+
+    # nice optional local db
+    import sqlite3
+    conn = sqlite3.connect(outdir / "giant.sqlite")
+    orders_df.to_sql("orders", conn, if_exists="replace", index=False)
+    items_df.to_sql("items", conn, if_exists="replace", index=False)
+    conn.close()
+
+    print(f"wrote {len(orders_df)} orders and {len(items_df)} items to {outdir}")
+
+
+if __name__ == "__main__":
+    main()