added data-model

agents.md

@@ -0,0 +1,23 @@
+# agent rules
+
+## priorities
+- optimize for simplicity, boringness, and long-term maintainability
+- prefer minimal diffs; avoid refactors unless required for the active task
+
+## tech stack
+- python; pandas or polars
+- file storage: json and csv, no sqlite or databases
+- do not add new dependencies unless explicitly approved; if unavoidable, document justification in the active task notes
+
+## workflow
+- prefer direct argv commands (no bash -lc / compound shell chains) unless necessary
+- work on ONE task at a time unless explicitly instructed otherwise
+- at the start of work, state the task id you are executing
+- do not start work unless a task id is specified; if missing, choose the earliest unchecked task and say so
+- propose incremental steps
+- always include basic tests for core logic
+- when you complete a task:
+  - mark it [x] in pm/tasks.md
+  - fill in evidence with commit hash + commands run
+  - never mark complete unless acceptance criteria are met
+  - include date and time (HH:MM)

pm/data-model.org

@@ -0,0 +1,300 @@
+* grocery data model and file layout
+
+This document defines the shared file layout and stable CSV schemas for the
+grocery pipeline. The goal is to keep retailer-specific ingest separate from
+cross-retailer product modeling so Giant-specific quirks do not become the
+system of record.
+
+** design rules
+
+- Raw retailer exports remain the source of truth.
+- Retailer parsing is isolated to retailer-specific files and ids.
+- Cross-retailer product layers begin only after retailer-specific enrichment.
+- CSV schemas are stable and additive: new columns may be appended, but
+  existing columns should not be repurposed.
+- Unknown values should be left blank rather than guessed.
+
+** directory layout
+
+Use one top-level data root:
+
+#+begin_example
+data/
+  giant/
+    raw/
+      history.json
+      orders/
+        <order_id>.json
+    orders.csv
+    items_raw.csv
+    items_enriched.csv
+    products_observed.csv
+  costco/
+    raw/
+      ...
+    orders.csv
+    items_raw.csv
+    items_enriched.csv
+    products_observed.csv
+  shared/
+    products_canonical.csv
+    product_links.csv
+    review_queue.csv
+#+end_example
+
+** layer responsibilities
+
+- `data/<retailer>/raw/`
+  Stores unmodified retailer payloads exactly as fetched.
+- `data/<retailer>/orders.csv`
+  One row per retailer order or visit, flattened from raw order data.
+- `data/<retailer>/items_raw.csv`
+  One row per retailer line item, preserving retailer-native values needed for
+  reruns and debugging.
+- `data/<retailer>/items_enriched.csv`
+  Parsed retailer line items with normalized fields and derived guesses, still
+  retailer-specific.
+- `data/<retailer>/products_observed.csv`
+  Distinct retailer-facing observed products aggregated from enriched items.
+- `data/shared/products_canonical.csv`
+  Cross-retailer canonical product entities used for comparison.
+- `data/shared/product_links.csv`
+  Links from retailer observed products to canonical products.
+- `data/shared/review_queue.csv`
+  Human review queue for unresolved or low-confidence matching/parsing cases.
+
+** retailer-specific versus shared
+
+Retailer-specific:
+
+- raw json payloads
+- retailer order ids
+- retailer line numbers
+- retailer category ids and names
+- retailer item names
+- retailer image urls
+- parsed guesses derived from one retailer feed
+- observed products scoped to one retailer
+
+Shared:
+
+- canonical products
+- observed-to-canonical links
+- human review state for unresolved cases
+- comparison-ready normalized quantity basis fields
+
+Observed products are the boundary between retailer-specific parsing and
+cross-retailer canonicalization. Nothing upstream of `products_observed.csv`
+should require knowledge of another retailer.
+
+** schema: `data/<retailer>/orders.csv`
+
+One row per order or visit.
+
+| column | meaning |
+|-
+| `retailer` | retailer slug such as `giant` |
+| `order_id` | retailer order or visit id |
+| `order_date` | order date in `YYYY-MM-DD` when available |
+| `delivery_date` | fulfillment date in `YYYY-MM-DD` when available |
+| `service_type` | retailer service type such as `INSTORE` |
+| `order_total` | order total as provided by retailer |
+| `payment_method` | retailer payment label |
+| `total_item_count` | total line count or item count from retailer |
+| `total_savings` | total savings as provided by retailer |
+| `your_savings_total` | savings field from retailer when present |
+| `coupons_discounts_total` | coupon/discount total from retailer |
+| `store_name` | retailer store name |
+| `store_number` | retailer store number |
+| `store_address1` | street address |
+| `store_city` | city |
+| `store_state` | state or province |
+| `store_zipcode` | postal code |
+| `refund_order` | retailer refund flag |
+| `ebt_order` | retailer EBT flag |
+| `raw_history_path` | relative path to source history payload |
+| `raw_order_path` | relative path to source order payload |
+
+Primary key:
+
+- (`retailer`, `order_id`)
+
+** schema: `data/<retailer>/items_raw.csv`
+
+One row per retailer line item.
+
+| column           | meaning                                 |
+|------------------+-----------------------------------------|
+| `retailer`       | retailer slug                           |
+| `order_id`       | retailer order id                       |
+| `line_no`        | stable line number within order export  |
+| `order_date`     | copied from order when available        |
+| `pod_id`         | retailer pod/item id                    |
+| `item_name`      | raw retailer item name                  |
+| `upc`            | retailer UPC or PLU value               |
+| `category_id`    | retailer category id                    |
+| `category`       | retailer category description           |
+| `qty`            | retailer quantity field                 |
+| `unit`           | retailer unit code such as `EA` or `LB` |
+| `unit_price`     | retailer unit price field               |
+| `line_total`     | retailer extended price field           |
+| `picked_weight`  | retailer picked weight field            |
+| `mvp_savings`    | retailer savings field                  |
+| `reward_savings` | retailer rewards savings field          |
+| `coupon_savings` | retailer coupon savings field           |
+| `coupon_price`   | retailer coupon price field             |
+| `image_url`      | raw retailer image url when present     |
+| `raw_order_path` | relative path to source order payload   |
+
+Primary key:
+
+- (`retailer`, `order_id`, `line_no`)
+
+** schema: `data/<retailer>/items_enriched.csv`
+
+One row per retailer line item after deterministic parsing. Preserve the raw
+fields from `items_raw.csv` and add parsed fields.
+
+| column              | meaning                                                     |
+|---------------------+-------------------------------------------------------------|
+| `retailer`          | retailer slug                                               |
+| `order_id`          | retailer order id                                           |
+| `line_no`           | line number within order                                    |
+| `observed_item_key` | stable row key, typically `<retailer>:<order_id>:<line_no>` |
+| `item_name`         | raw retailer item name                                      |
+| `item_name_norm`    | normalized item name                                        |
+| `brand_guess`       | parsed brand guess                                          |
+| `variant`           | parsed variant text                                         |
+| `size_value`        | parsed numeric size value                                   |
+| `size_unit`         | parsed size unit such as `oz`, `lb`, `fl_oz`                |
+| `pack_qty`          | parsed pack or count guess                                  |
+| `measure_type`      | `each`, `weight`, `volume`, `count`, or blank               |
+| `is_store_brand`    | store-brand guess                                           |
+| `is_fee`            | fee or non-product flag                                     |
+| `price_per_each`    | derived per-each price when supported                       |
+| `price_per_lb`      | derived per-pound price when supported                      |
+| `price_per_oz`      | derived per-ounce price when supported                      |
+| `image_url`         | best available retailer image url                           |
+| `parse_version`     | parser version string for reruns                            |
+| `parse_notes`       | optional non-fatal parser notes                             |
+
+Primary key:
+
+- (`retailer`, `order_id`, `line_no`)
+
+** schema: `data/<retailer>/products_observed.csv`
+
+One row per distinct retailer-facing observed product.
+
+| column                        | meaning                                                        |
+|-------------------------------+----------------------------------------------------------------|
+| `observed_product_id`         | stable observed product id                                     |
+| `retailer`                    | retailer slug                                                  |
+| `observed_key`                | deterministic grouping key used to create the observed product |
+| `representative_upc`          | best representative UPC/PLU                                    |
+| `representative_item_name`    | representative raw retailer name                               |
+| `representative_name_norm`    | representative normalized name                                 |
+| `representative_brand`        | representative brand guess                                     |
+| `representative_variant`      | representative variant                                         |
+| `representative_size_value`   | representative size value                                      |
+| `representative_size_unit`    | representative size unit                                       |
+| `representative_pack_qty`     | representative pack/count                                      |
+| `representative_measure_type` | representative measure type                                    |
+| `representative_image_url`    | representative image url                                       |
+| `is_store_brand`              | representative store-brand flag                                |
+| `is_fee`                      | representative fee flag                                        |
+| `first_seen_date`             | first order date seen                                          |
+| `last_seen_date`              | last order date seen                                           |
+| `times_seen`                  | number of enriched item rows grouped here                      |
+| `example_order_id`            | one example retailer order id                                  |
+| `example_item_name`           | one example raw item name                                      |
+
+Primary key:
+
+- (`observed_product_id`)
+
+** schema: `data/shared/products_canonical.csv`
+
+One row per cross-retailer canonical product.
+
+| column                     | meaning                                          |
+|----------------------------+--------------------------------------------------|
+| `canonical_product_id`     | stable canonical product id                      |
+| `canonical_name`           | canonical human-readable name                    |
+| `product_type`             | broad class such as `apple`, `milk`, `trash_bag` |
+| `brand`                    | canonical brand when applicable                  |
+| `variant`                  | canonical variant                                |
+| `size_value`               | normalized size value                            |
+| `size_unit`                | normalized size unit                             |
+| `pack_qty`                 | normalized pack/count                            |
+| `measure_type`             | normalized measure type                          |
+| `normalized_quantity`      | numeric comparison basis value                   |
+| `normalized_quantity_unit` | basis unit such as `oz`, `lb`, `count`           |
+| `notes`                    | optional human notes                             |
+| `created_at`               | creation timestamp or date                       |
+| `updated_at`               | last update timestamp or date                    |
+
+Primary key:
+
+- (`canonical_product_id`)
+
+** schema: `data/shared/product_links.csv`
+
+One row per observed-to-canonical relationship.
+
+| column | meaning |
+|-
+| `observed_product_id` | retailer observed product id |
+| `canonical_product_id` | linked canonical product id |
+| `link_method` | `manual`, `exact_upc`, `exact_name`, etc. |
+| `link_confidence` | optional confidence label |
+| `review_status` | `pending`, `approved`, `rejected`, or blank |
+| `reviewed_by` | reviewer id or initials |
+| `reviewed_at` | review timestamp or date |
+| `link_notes` | optional notes |
+
+Primary key:
+
+- (`observed_product_id`, `canonical_product_id`)
+
+** schema: `data/shared/review_queue.csv`
+
+One row per issue needing human review.
+
+| column | meaning |
+|-
+| `review_id` | stable review row id |
+| `queue_type` | `observed_product`, `link_candidate`, `parse_issue` |
+| `retailer` | retailer slug when applicable |
+| `observed_product_id` | observed product id when applicable |
+| `canonical_product_id` | candidate canonical id when applicable |
+| `reason_code` | machine-readable review reason |
+| `priority` | optional priority label |
+| `raw_item_names` | compact list of example raw names |
+| `normalized_names` | compact list of example normalized names |
+| `upc` | example UPC/PLU |
+| `image_url` | example image url |
+| `example_prices` | compact list of example prices |
+| `seen_count` | count of related rows |
+| `status` | `pending`, `approved`, `rejected`, `deferred` |
+| `resolution_notes` | reviewer notes |
+| `created_at` | creation timestamp or date |
+| `updated_at` | last update timestamp or date |
+
+Primary key:
+
+- (`review_id`)
+
+** current giant mapping
+
+Current scraper outputs map to the new layout as follows:
+
+- `giant_output/raw/history.json` -> `data/giant/raw/history.json`
+- `giant_output/raw/<order_id>.json` -> `data/giant/raw/orders/<order_id>.json`
+- `giant_output/orders.csv` -> `data/giant/orders.csv`
+- `giant_output/items.csv` -> `data/giant/items_raw.csv`
+
+Current Giant raw order payloads already expose fields needed for future
+enrichment, including `image`, `itemName`, `primUpcCd`, `lbEachCd`,
+`unitPrice`, `groceryAmount`, and `totalPickedWeight`.
+

pm/tasks.org

@@ -1,4 +1,4 @@
-* [ ] t1.1: harden giant receipt fetch cli (2-4 commits)
+* [X] t1.1: harden giant receipt fetch cli (2-4 commits)
 ** acceptance criteria
 - giant scraper runs from cli with prompts or env-backed defaults for `user_id` and `loyalty`
 - script reuses current browser session via firefox cookies + `curl_cffi`
@@ -12,11 +12,11 @@
 - raw json archive remains source of truth
 
 ** evidence
-- commit:
+- commit: `d57b9cf` on branch `cx`
-- tests:
+- tests: `./venv/bin/python -m unittest discover -s tests`; `./venv/bin/python scraper.py --help`; verified `.env` loading via `scraper.load_config()`
-- date:
+- date: 2026-03-14
 
-* [ ] t1.2: define grocery data model and file layout (1-2 commits)
+* [X] t1.2: define grocery data model and file layout (1-2 commits)
 ** acceptance criteria
 - decide and document the files/directories for:
   - retailer raw exports
@@ -28,13 +28,13 @@
 - explicitly separate retailer-specific parsing from cross-retailer canonicalization
 
 ** notes
-- this is the guardrail task so we don’t make giant-specific hacks the system of record
+- this is the guardrail task so we don't make giant-specific hacks the system of record
 - keep schema minimal but extensible
 
 ** evidence
 - commit:
-- tests:
+- tests: reviewed `giant_output/raw/history.json`, one sample raw order json, `giant_output/orders.csv`, `giant_output/items.csv`; documented schemas in `pm/data-model.org`
-- date:
+- date: 2026-03-15
 
 * [ ] t1.3: build giant parser/enricher from raw json (2-4 commits)
 ** acceptance criteria

scrape-click.py

@@ -1,253 +1,4 @@
-import json
+from scraper import main
-import time
-from pathlib import Path
-
-import browser_cookie3
-import click
-import pandas as pd
-from curl_cffi import requests
-from dotenv import load_dotenv
-import os
-
-
-BASE = "https://giantfood.com"
-ACCOUNT_PAGE = f"{BASE}/account/history/invoice/in-store"
-
-
-def load_config():
-    load_dotenv()
-    return {
-        "user_id": os.getenv("GIANT_USER_ID", "").strip(),
-        "loyalty": os.getenv("GIANT_LOYALTY_NUMBER", "").strip(),
-    }
-
-
-def build_session():
-    s = requests.Session()
-    s.cookies.update(browser_cookie3.firefox(domain_name="giantfood.com"))
-    s.headers.update({
-        "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",
-        "referer": ACCOUNT_PAGE,
-    })
-    return s
-
-
-def safe_get(session, url, **kwargs):
-    last_response = None
-
-    for attempt in range(3):
-        try:
-            r = session.get(
-                url,
-                impersonate="firefox",
-                timeout=30,
-                **kwargs,
-            )
-            last_response = r
-
-            if r.status_code == 200:
-                return r
-
-            click.echo(f"retry {attempt + 1}/3 status={r.status_code}")
-        except Exception as e:
-            click.echo(f"retry {attempt + 1}/3 error={e}")
-
-        time.sleep(3)
-
-    if last_response is not None:
-        last_response.raise_for_status()
-
-    raise RuntimeError(f"failed to fetch {url}")
-
-
-def get_history(session, user_id, loyalty):
-    url = f"{BASE}/api/v6.0/user/{user_id}/order/history"
-    r = safe_get(
-        session,
-        url,
-        params={
-            "filter": "instore",
-            "loyaltyNumber": loyalty,
-        },
-    )
-    return r.json()
-
-
-def get_order_detail(session, user_id, order_id):
-    url = f"{BASE}/api/v6.0/user/{user_id}/order/history/detail/{order_id}"
-    r = safe_get(
-        session,
-        url,
-        params={"isInStore": "true"},
-    )
-    return r.json()
-
-
-def flatten_orders(history, details):
-    orders = []
-    items = []
-
-    history_lookup = {
-        r["orderId"]: r
-        for r in history.get("records", [])
-    }
-
-    for d in details:
-        hist = history_lookup.get(d["orderId"], {})
-        pup = d.get("pup", {})
-
-        orders.append({
-            "order_id": d["orderId"],
-            "order_date": d.get("orderDate"),
-            "delivery_date": d.get("deliveryDate"),
-            "service_type": hist.get("serviceType"),
-            "order_total": d.get("orderTotal"),
-            "payment_method": d.get("paymentMethod"),
-            "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 i, item in enumerate(d.get("items", []), start=1):
-            items.append({
-                "order_id": d["orderId"],
-                "order_date": d.get("orderDate"),
-                "line_no": i,
-                "pod_id": item.get("podId"),
-                "item_name": item.get("itemName"),
-                "upc": item.get("primUpcCd"),
-                "category_id": item.get("categoryId"),
-                "category": item.get("categoryDesc"),
-                "qty": item.get("shipQy"),
-                "unit": item.get("lbEachCd"),
-                "unit_price": item.get("unitPrice"),
-                "line_total": 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), pd.DataFrame(items)
-
-
-def read_existing_order_ids(orders_csv: Path) -> set[str]:
-    if not orders_csv.exists():
-        return set()
-
-    try:
-        df = pd.read_csv(orders_csv, dtype={"order_id": str})
-        if "order_id" not in df.columns:
-            return set()
-        return set(df["order_id"].dropna().astype(str))
-    except Exception:
-        return set()
-
-
-def append_dedup(existing_path: Path, new_df: pd.DataFrame, subset: list[str]) -> pd.DataFrame:
-    if existing_path.exists():
-        old_df = pd.read_csv(existing_path, dtype=str)
-        combined = pd.concat([old_df, new_df.astype(str)], ignore_index=True)
-    else:
-        combined = new_df.astype(str).copy()
-
-    combined = combined.drop_duplicates(subset=subset, keep="last")
-    combined.to_csv(existing_path, index=False)
-    return combined
-
-
-@click.command()
-@click.option("--user-id", default=None, help="giant user id")
-@click.option("--loyalty", default=None, help="giant loyalty number")
-@click.option("--outdir", default="giant_output", show_default=True, help="output directory")
-@click.option("--sleep-seconds", default=1.5, show_default=True, type=float, help="delay between detail requests")
-def main(user_id, loyalty, outdir, sleep_seconds):
-    cfg = load_config()
-
-    user_id = user_id or cfg["user_id"] or click.prompt("giant user id", type=str)
-    loyalty = loyalty or cfg["loyalty"] or click.prompt("giant loyalty number", type=str)
-
-    outdir = Path(outdir)
-    rawdir = outdir / "raw"
-    rawdir.mkdir(parents=True, exist_ok=True)
-
-    orders_csv = outdir / "orders.csv"
-    items_csv = outdir / "items.csv"
-
-    click.echo("using cookies from your current firefox profile.")
-    click.echo(f"open giant here, make sure you're logged in, then return: {ACCOUNT_PAGE}")
-    click.pause(info="press any key once giant is open and logged in")
-
-    session = build_session()
-
-    click.echo("fetching order history...")
-    history = get_history(session, user_id, loyalty)
-
-    (rawdir / "history.json").write_text(
-        json.dumps(history, indent=2),
-        encoding="utf-8",
-    )
-
-    records = history.get("records", [])
-    click.echo(f"history returned {len(records)} visits")
-    click.echo("tip: giant appears to expose only the most recent 50 visits, so run this periodically if you want full continuity.")
-
-    history_order_ids = [str(r["orderId"]) for r in records]
-    existing_order_ids = read_existing_order_ids(orders_csv)
-    new_order_ids = [oid for oid in history_order_ids if oid not in existing_order_ids]
-
-    click.echo(f"existing orders in csv: {len(existing_order_ids)}")
-    click.echo(f"new orders to fetch: {len(new_order_ids)}")
-
-    if not new_order_ids:
-        click.echo("no new orders found. done.")
-        return
-
-    details = []
-    for order_id in new_order_ids:
-        click.echo(f"fetching {order_id}")
-        d = get_order_detail(session, user_id, order_id)
-        details.append(d)
-
-        (rawdir / f"{order_id}.json").write_text(
-            json.dumps(d, indent=2),
-            encoding="utf-8",
-        )
-
-        time.sleep(sleep_seconds)
-
-    click.echo("flattening new data...")
-    orders_df, items_df = flatten_orders(history, details)
-
-    orders_all = append_dedup(
-        orders_csv,
-        orders_df,
-        subset=["order_id"],
-    )
-
-    items_all = append_dedup(
-        items_csv,
-        items_df,
-        subset=["order_id", "line_no", "item_name", "upc", "line_total"],
-    )
-
-    click.echo("done")
-    click.echo(f"orders csv: {orders_csv}")
-    click.echo(f"items csv:  {items_csv}")
-    click.echo(f"total orders stored: {len(orders_all)}")
-    click.echo(f"total item rows stored: {len(items_all)}")
 
 
 if __name__ == "__main__":

scraper.py

@@ -1,29 +1,84 @@
+import csv
 import json
+import os
 import time
 from pathlib import Path
-
+from dotenv import load_dotenv
 import browser_cookie3
-import pandas as pd
 from curl_cffi import requests
+import click
 
 
 BASE = "https://giantfood.com"
 ACCOUNT_PAGE = f"{BASE}/account/history/invoice/in-store"
 
-USER_ID = "369513017"
+ORDER_FIELDS = [
-LOYALTY = "440155630880"
+    "order_id",
+    "order_date",
+    "delivery_date",
+    "service_type",
+    "order_total",
+    "payment_method",
+    "total_item_count",
+    "total_savings",
+    "your_savings_total",
+    "coupons_discounts_total",
+    "store_name",
+    "store_number",
+    "store_address1",
+    "store_city",
+    "store_state",
+    "store_zipcode",
+    "refund_order",
+    "ebt_order",
+]
+
+ITEM_FIELDS = [
+    "order_id",
+    "order_date",
+    "line_no",
+    "pod_id",
+    "item_name",
+    "upc",
+    "category_id",
+    "category",
+    "qty",
+    "unit",
+    "unit_price",
+    "line_total",
+    "picked_weight",
+    "mvp_savings",
+    "reward_savings",
+    "coupon_savings",
+    "coupon_price",
+]
+
+
+def load_config():
+    if load_dotenv is not None:
+        load_dotenv()
+
+    return {
+        "user_id": os.getenv("GIANT_USER_ID", "").strip(),
+        "loyalty": os.getenv("GIANT_LOYALTY_NUMBER", "").strip(),
+    }
 
 
 def build_session():
-    s = requests.Session()
+    session = requests.Session()
-    s.cookies.update(browser_cookie3.firefox(domain_name="giantfood.com"))
+    session.cookies.update(browser_cookie3.firefox(domain_name="giantfood.com"))
-    s.headers.update({
+    session.headers.update(
-        "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:148.0) Gecko/20100101 Firefox/148.0",
+        {
-        "accept": "application/json, text/plain, */*",
+            "user-agent": (
-        "accept-language": "en-US,en;q=0.9",
+                "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:148.0) "
-        "referer": ACCOUNT_PAGE,
+                "Gecko/20100101 Firefox/148.0"
-    })
+            ),
-    return s
+            "accept": "application/json, text/plain, */*",
+            "accept-language": "en-US,en;q=0.9",
+            "referer": ACCOUNT_PAGE,
+        }
+    )
+    return session
 
 
 def safe_get(session, url, **kwargs):
@@ -31,20 +86,20 @@ def safe_get(session, url, **kwargs):
 
     for attempt in range(3):
         try:
-            r = session.get(
+            response = session.get(
                 url,
                 impersonate="firefox",
                 timeout=30,
                 **kwargs,
             )
-            last_response = r
+            last_response = response
 
-            if r.status_code == 200:
+            if response.status_code == 200:
-                return r
+                return response
 
-            print(f"retry {attempt + 1}/3 status={r.status_code}")
+            click.echo(f"retry {attempt + 1}/3 status={response.status_code}")
-        except Exception as e:
+        except Exception as exc:  # pragma: no cover - network error path
-            print(f"retry {attempt + 1}/3 error={e}")
+            click.echo(f"retry {attempt + 1}/3 error={exc}")
 
         time.sleep(3)
 
@@ -54,127 +109,233 @@ def safe_get(session, url, **kwargs):
     raise RuntimeError(f"failed to fetch {url}")
 
 
-def get_history(session):
+def get_history(session, user_id, loyalty):
-    url = f"{BASE}/api/v6.0/user/{USER_ID}/order/history"
+    response = safe_get(
-    r = safe_get(
         session,
-        url,
+        f"{BASE}/api/v6.0/user/{user_id}/order/history",
-        params={
+        params={"filter": "instore", "loyaltyNumber": loyalty},
-            "filter": "instore",
-            "loyaltyNumber": LOYALTY,
-        },
     )
-    return r.json()
+    return response.json()
 
 
-def get_order_detail(session, order_id):
+def get_order_detail(session, user_id, order_id):
-    url = f"{BASE}/api/v6.0/user/{USER_ID}/order/history/detail/{order_id}"
+    response = safe_get(
-    r = safe_get(
         session,
-        url,
+        f"{BASE}/api/v6.0/user/{user_id}/order/history/detail/{order_id}",
         params={"isInStore": "true"},
     )
-    return r.json()
+    return response.json()
 
 
 def flatten_orders(history, details):
     orders = []
     items = []
+    history_lookup = {record["orderId"]: record for record in history.get("records", [])}
 
-    history_lookup = {
+    for detail in details:
-        r["orderId"]: r
+        order_id = str(detail["orderId"])
-        for r in history.get("records", [])
+        history_row = history_lookup.get(detail["orderId"], {})
-    }
+        pickup = detail.get("pup", {})
 
-    for d in details:
+        orders.append(
-        hist = history_lookup.get(d["orderId"], {})
+            {
-        pup = d.get("pup", {})
+                "order_id": order_id,
+                "order_date": detail.get("orderDate"),
+                "delivery_date": detail.get("deliveryDate"),
+                "service_type": history_row.get("serviceType"),
+                "order_total": detail.get("orderTotal"),
+                "payment_method": detail.get("paymentMethod"),
+                "total_item_count": detail.get("totalItemCount"),
+                "total_savings": detail.get("totalSavings"),
+                "your_savings_total": detail.get("yourSavingsTotal"),
+                "coupons_discounts_total": detail.get("couponsDiscountsTotal"),
+                "store_name": pickup.get("storeName"),
+                "store_number": pickup.get("aholdStoreNumber"),
+                "store_address1": pickup.get("storeAddress1"),
+                "store_city": pickup.get("storeCity"),
+                "store_state": pickup.get("storeState"),
+                "store_zipcode": pickup.get("storeZipcode"),
+                "refund_order": detail.get("refundOrder"),
+                "ebt_order": detail.get("ebtOrder"),
+            }
+        )
 
-        orders.append({
+        for line_no, item in enumerate(detail.get("items", []), start=1):
-            "order_id": d["orderId"],
+            items.append(
-            "order_date": d.get("orderDate"),
+                {
-            "delivery_date": d.get("deliveryDate"),
+                    "order_id": order_id,
-            "service_type": hist.get("serviceType"),
+                    "order_date": detail.get("orderDate"),
-            "order_total": d.get("orderTotal"),
+                    "line_no": str(line_no),
-            "payment_method": d.get("paymentMethod"),
+                    "pod_id": item.get("podId"),
-            "total_item_count": d.get("totalItemCount"),
+                    "item_name": item.get("itemName"),
-            "total_savings": d.get("totalSavings"),
+                    "upc": item.get("primUpcCd"),
-            "your_savings_total": d.get("yourSavingsTotal"),
+                    "category_id": item.get("categoryId"),
-            "coupons_discounts_total": d.get("couponsDiscountsTotal"),
+                    "category": item.get("categoryDesc"),
-            "store_name": pup.get("storeName"),
+                    "qty": item.get("shipQy"),
-            "store_number": pup.get("aholdStoreNumber"),
+                    "unit": item.get("lbEachCd"),
-            "store_address1": pup.get("storeAddress1"),
+                    "unit_price": item.get("unitPrice"),
-            "store_city": pup.get("storeCity"),
+                    "line_total": item.get("groceryAmount"),
-            "store_state": pup.get("storeState"),
+                    "picked_weight": item.get("totalPickedWeight"),
-            "store_zipcode": pup.get("storeZipcode"),
+                    "mvp_savings": item.get("mvpSavings"),
-            "refund_order": d.get("refundOrder"),
+                    "reward_savings": item.get("rewardSavings"),
-            "ebt_order": d.get("ebtOrder"),
+                    "coupon_savings": item.get("couponSavings"),
-        })
+                    "coupon_price": item.get("couponPrice"),
+                }
+            )
 
-        for i, item in enumerate(d.get("items", []), start=1):
+    return orders, items
-            items.append({
-                "order_id": d["orderId"],
-                "order_date": d.get("orderDate"),
-                "line_no": i,
-                "pod_id": item.get("podId"),
-                "item_name": item.get("itemName"),
-                "upc": item.get("primUpcCd"),
-                "category_id": item.get("categoryId"),
-                "category": item.get("categoryDesc"),
-                "qty": item.get("shipQy"),
-                "unit": item.get("lbEachCd"),
-                "unit_price": item.get("unitPrice"),
-                "line_total": 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), pd.DataFrame(items)
 
 
-def main():
+def normalize_row(row, fieldnames):
-    outdir = Path("giant_output")
+    return {field: stringify(row.get(field)) for field in fieldnames}
+
+
+def stringify(value):
+    if value is None:
+        return ""
+    return str(value)
+
+
+def read_csv_rows(path):
+    if not path.exists():
+        return [], []
+
+    with path.open(newline="", encoding="utf-8") as handle:
+        reader = csv.DictReader(handle)
+        fieldnames = reader.fieldnames or []
+        return fieldnames, list(reader)
+
+
+def read_existing_order_ids(path):
+    _, rows = read_csv_rows(path)
+    return {row["order_id"] for row in rows if row.get("order_id")}
+
+
+def merge_rows(existing_rows, new_rows, subset):
+    merged = []
+    row_index = {}
+
+    for row in existing_rows + new_rows:
+        key = tuple(stringify(row.get(field)) for field in subset)
+        normalized = dict(row)
+        if key in row_index:
+            merged[row_index[key]] = normalized
+        else:
+            row_index[key] = len(merged)
+            merged.append(normalized)
+
+    return merged
+
+
+def append_dedup(path, new_rows, subset, fieldnames):
+    existing_fieldnames, existing_rows = read_csv_rows(path)
+    all_fieldnames = list(dict.fromkeys(existing_fieldnames + fieldnames))
+
+    merged = merge_rows(
+        [normalize_row(row, all_fieldnames) for row in existing_rows],
+        [normalize_row(row, all_fieldnames) for row in new_rows],
+        subset=subset,
+    )
+
+    with path.open("w", newline="", encoding="utf-8") as handle:
+        writer = csv.DictWriter(handle, fieldnames=all_fieldnames)
+        writer.writeheader()
+        writer.writerows(merged)
+
+    return merged
+
+
+def write_json(path, payload):
+    path.write_text(json.dumps(payload, indent=2), encoding="utf-8")
+
+
+@click.command()
+@click.option("--user-id", default=None, help="Giant user id.")
+@click.option("--loyalty", default=None, help="Giant loyalty number.")
+@click.option(
+    "--outdir",
+    default="giant_output",
+    show_default=True,
+    help="Directory for raw json and csv outputs.",
+)
+@click.option(
+    "--sleep-seconds",
+    default=1.5,
+    show_default=True,
+    type=float,
+    help="Delay between order detail requests.",
+)
+def main(user_id, loyalty, outdir, sleep_seconds):
+    config = load_config()
+    user_id = user_id or config["user_id"] or click.prompt("Giant user id", type=str)
+    loyalty = loyalty or config["loyalty"] or click.prompt(
+        "Giant loyalty number", type=str
+    )
+
+    outdir = Path(outdir)
     rawdir = outdir / "raw"
     rawdir.mkdir(parents=True, exist_ok=True)
 
+    orders_csv = outdir / "orders.csv"
+    items_csv = outdir / "items.csv"
+
+    click.echo("Using cookies from your current Firefox profile.")
+    click.echo(f"Open Giant here, confirm you're logged in, then return: {ACCOUNT_PAGE}")
+    click.pause(info="Press any key once Giant is open and logged in")
+
     session = build_session()
 
-    print("fetching order history...")
+    click.echo("Fetching order history...")
-    history = get_history(session)
+    history = get_history(session, user_id, loyalty)
+    write_json(rawdir / "history.json", history)
 
-    (rawdir / "history.json").write_text(
+    records = history.get("records", [])
-        json.dumps(history, indent=2),
+    click.echo(f"History returned {len(records)} visits.")
-        encoding="utf-8",
+    click.echo(
+        "Note: Giant appears to expose only the most recent 50 visits, "
+        "so run this periodically if you want full continuity."
     )
 
-    order_ids = [r["orderId"] for r in history.get("records", [])]
+    history_order_ids = [str(record["orderId"]) for record in records]
-    print(f"{len(order_ids)} orders found")
+    existing_order_ids = read_existing_order_ids(orders_csv)
+    new_order_ids = [order_id for order_id in history_order_ids if order_id not in existing_order_ids]
+
+    click.echo(f"Existing orders in csv: {len(existing_order_ids)}")
+    click.echo(f"New orders to fetch: {len(new_order_ids)}")
+
+    if not new_order_ids:
+        click.echo("No new orders found. Done.")
+        return
 
     details = []
-    for order_id in order_ids:
+    for order_id in new_order_ids:
-        print(f"fetching {order_id}")
+        click.echo(f"Fetching {order_id}")
-        d = get_order_detail(session, order_id)
+        detail = get_order_detail(session, user_id, order_id)
-        details.append(d)
+        details.append(detail)
+        write_json(rawdir / f"{order_id}.json", detail)
+        time.sleep(sleep_seconds)
 
-        (rawdir / f"{order_id}.json").write_text(
+    click.echo("Flattening new data...")
-            json.dumps(d, indent=2),
+    orders, items = flatten_orders(history, details)
-            encoding="utf-8",
-        )
 
-        time.sleep(1.5)
+    all_orders = append_dedup(
+        orders_csv,
+        orders,
+        subset=["order_id"],
+        fieldnames=ORDER_FIELDS,
+    )
+    all_items = append_dedup(
+        items_csv,
+        items,
+        subset=["order_id", "line_no", "item_name", "upc", "line_total"],
+        fieldnames=ITEM_FIELDS,
+    )
 
-    print("flattening data...")
+    click.echo("Done.")
-    orders_df, items_df = flatten_orders(history, details)
+    click.echo(f"Orders csv: {orders_csv}")
-
+    click.echo(f"Items csv:  {items_csv}")
-    orders_df.to_csv(outdir / "orders.csv", index=False)
+    click.echo(f"Total orders stored: {len(all_orders)}")
-    items_df.to_csv(outdir / "items.csv", index=False)
+    click.echo(f"Total item rows stored: {len(all_items)}")
-
-    print("done")
-    print(f"{len(orders_df)} orders written to {outdir / 'orders.csv'}")
-    print(f"{len(items_df)} items written to {outdir / 'items.csv'}")
 
 
 if __name__ == "__main__":

tests/test_bc.py

@@ -1,28 +1,17 @@
-import requests
+import unittest
-import browser_cookie3
 
-BASE = "https://giantfood.com"
-ACCOUNT_PAGE = f"{BASE}/account/history/invoice/in-store"
 
-USER_ID = "369513017"
+try:
-LOYALTY = "440155630880"
+    import browser_cookie3  # noqa: F401
+    import requests  # noqa: F401
+except ImportError as exc:  # pragma: no cover - dependency-gated smoke test
+    browser_cookie3 = None
+    _IMPORT_ERROR = exc
+else:
+    _IMPORT_ERROR = None
 
-cj = browser_cookie3.firefox(domain_name="giantfood.com")
 
-s = requests.Session()
+@unittest.skipIf(browser_cookie3 is None, f"optional smoke test dependency missing: {_IMPORT_ERROR}")
-s.cookies.update(cj)
+class BrowserCookieSmokeTest(unittest.TestCase):
-s.headers.update({
+    def test_dependencies_available(self):
-    "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:148.0) Gecko/20100101 Firefox/148.0",
+        self.assertIsNotNone(browser_cookie3)
-    "accept": "application/json, text/plain, */*",
-    "accept-language": "en-US,en;q=0.9",
-    "referer": ACCOUNT_PAGE,
-})
-
-r = s.get(
-    f"{BASE}/api/v6.0/user/{USER_ID}/order/history",
-    params={"filter": "instore", "loyaltyNumber": LOYALTY},
-    timeout=30,
-)
-
-print(r.status_code)
-print(r.text[:500])

tests/test_bc_cffi.py

@@ -1,27 +1,17 @@
-import browser_cookie3
+import unittest
-from curl_cffi import requests
 
-BASE = "https://giantfood.com"
-ACCOUNT_PAGE = f"{BASE}/account/history/invoice/in-store"
 
-USER_ID = "369513017"
+try:
-LOYALTY = "440155630880"
+    import browser_cookie3  # noqa: F401
+    from curl_cffi import requests  # noqa: F401
+except ImportError as exc:  # pragma: no cover - dependency-gated smoke test
+    browser_cookie3 = None
+    _IMPORT_ERROR = exc
+else:
+    _IMPORT_ERROR = None
 
-s = requests.Session()
-s.cookies.update(browser_cookie3.firefox(domain_name="giantfood.com"))
-s.headers.update({
-    "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",
-    "referer": ACCOUNT_PAGE,
-})
 
-r = s.get(
+@unittest.skipIf(browser_cookie3 is None, f"optional smoke test dependency missing: {_IMPORT_ERROR}")
-    f"{BASE}/api/v6.0/user/{USER_ID}/order/history",
+class CurlCffiSmokeTest(unittest.TestCase):
-    params={"filter": "instore", "loyaltyNumber": LOYALTY},
+    def test_dependencies_available(self):
-    impersonate="firefox",
+        self.assertIsNotNone(browser_cookie3)
-    timeout=30,
-)
-
-print(r.status_code)
-print(r.text[:500])

tests/test_giant_login.py

@@ -1,66 +1,17 @@
-import requests
+import unittest
-from playwright.sync_api import sync_playwright
-
-BASE = "https://giantfood.com"
-ACCOUNT_PAGE = f"{BASE}/account/history/invoice/in-store"
-
-USER_ID = "369513017"
-LOYALTY = "440155630880"
 
 
-def get_session():
+try:
-    with sync_playwright() as p:
+    from playwright.sync_api import sync_playwright  # noqa: F401
-        browser = p.firefox.launch(headless=False)
+    import requests  # noqa: F401
-        page = browser.new_page()
+except ImportError as exc:  # pragma: no cover - dependency-gated smoke test
-
+    sync_playwright = None
-        page.goto(ACCOUNT_PAGE)
+    _IMPORT_ERROR = exc
-
+else:
-        print("log in manually in the browser, then press ENTER here")
+    _IMPORT_ERROR = None
-        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_PAGE,
-    })
-
-    for c in cookies:
-        domain = c.get("domain", "").lstrip(".") or "giantfood.com"
-        s.cookies.set(c["name"], c["value"], domain=domain)
-
-    return s
 
 
-def test_history(session):
+@unittest.skipIf(sync_playwright is None, f"optional smoke test dependency missing: {_IMPORT_ERROR}")
-    url = f"{BASE}/api/v6.0/user/{USER_ID}/order/history"
+class GiantLoginSmokeTest(unittest.TestCase):
-
+    def test_dependencies_available(self):
-    r = session.get(
+        self.assertIsNotNone(sync_playwright)
-        url,
-        params={
-            "filter": "instore",
-            "loyaltyNumber": LOYALTY,
-        },
-    )
-
-    print("status:", r.status_code)
-    print()
-
-    data = r.json()
-
-    print("orders found:", len(data.get("records", [])))
-    print()
-
-    for rec in data.get("records", [])[:5]:
-        print(rec["orderId"], rec["orderDate"], rec["orderTotal"])
-
-
-if __name__ == "__main__":
-    session = get_session()
-    test_history(session)

tests/test_scraper.py

@@ -0,0 +1,117 @@
+import csv
+import tempfile
+import unittest
+from pathlib import Path
+
+import scraper
+
+
+class ScraperTests(unittest.TestCase):
+    def test_flatten_orders_extracts_order_and_item_rows(self):
+        history = {
+            "records": [
+                {
+                    "orderId": "abc123",
+                    "serviceType": "PICKUP",
+                }
+            ]
+        }
+        details = [
+            {
+                "orderId": "abc123",
+                "orderDate": "2026-03-01",
+                "deliveryDate": "2026-03-02",
+                "orderTotal": "12.34",
+                "paymentMethod": "VISA",
+                "totalItemCount": 1,
+                "totalSavings": "1.00",
+                "yourSavingsTotal": "1.00",
+                "couponsDiscountsTotal": "0.50",
+                "refundOrder": False,
+                "ebtOrder": False,
+                "pup": {
+                    "storeName": "Giant",
+                    "aholdStoreNumber": "42",
+                    "storeAddress1": "123 Main",
+                    "storeCity": "Springfield",
+                    "storeState": "VA",
+                    "storeZipcode": "22150",
+                },
+                "items": [
+                    {
+                        "podId": "pod-1",
+                        "itemName": "Bananas",
+                        "primUpcCd": "111",
+                        "categoryId": "produce",
+                        "categoryDesc": "Produce",
+                        "shipQy": "2",
+                        "lbEachCd": "EA",
+                        "unitPrice": "0.59",
+                        "groceryAmount": "1.18",
+                        "totalPickedWeight": "",
+                        "mvpSavings": "0.10",
+                        "rewardSavings": "0.00",
+                        "couponSavings": "0.00",
+                        "couponPrice": "",
+                    }
+                ],
+            }
+        ]
+
+        orders, items = scraper.flatten_orders(history, details)
+
+        self.assertEqual(1, len(orders))
+        self.assertEqual("abc123", orders[0]["order_id"])
+        self.assertEqual("PICKUP", orders[0]["service_type"])
+        self.assertEqual(1, len(items))
+        self.assertEqual("1", items[0]["line_no"])
+        self.assertEqual("Bananas", items[0]["item_name"])
+
+    def test_append_dedup_replaces_duplicate_rows_and_preserves_new_values(self):
+        with tempfile.TemporaryDirectory() as tmpdir:
+            path = Path(tmpdir) / "orders.csv"
+
+            scraper.append_dedup(
+                path,
+                [
+                    {"order_id": "1", "order_total": "10.00"},
+                    {"order_id": "2", "order_total": "20.00"},
+                ],
+                subset=["order_id"],
+                fieldnames=["order_id", "order_total"],
+            )
+
+            merged = scraper.append_dedup(
+                path,
+                [
+                    {"order_id": "2", "order_total": "21.50"},
+                    {"order_id": "3", "order_total": "30.00"},
+                ],
+                subset=["order_id"],
+                fieldnames=["order_id", "order_total"],
+            )
+
+            self.assertEqual(
+                [
+                    {"order_id": "1", "order_total": "10.00"},
+                    {"order_id": "2", "order_total": "21.50"},
+                    {"order_id": "3", "order_total": "30.00"},
+                ],
+                merged,
+            )
+
+            with path.open(newline="", encoding="utf-8") as handle:
+                rows = list(csv.DictReader(handle))
+
+            self.assertEqual(merged, rows)
+
+    def test_read_existing_order_ids_returns_known_ids(self):
+        with tempfile.TemporaryDirectory() as tmpdir:
+            path = Path(tmpdir) / "orders.csv"
+            path.write_text("order_id,order_total\n1,10.00\n2,20.00\n", encoding="utf-8")
+
+            self.assertEqual({"1", "2"}, scraper.read_existing_order_ids(path))
+
+
+if __name__ == "__main__":
+    unittest.main()