Build Giant item enricher

This commit is contained in:
ben
2026-03-16 00:28:28 -04:00
parent 42dbae1d2e
commit 14f2cc2bac
3 changed files with 620 additions and 4 deletions

426
enrich_giant.py Normal file
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import csv
import json
import re
from decimal import Decimal, InvalidOperation, ROUND_HALF_UP
from pathlib import Path
import click
PARSER_VERSION = "giant-enrich-v1"
RETAILER = "giant"
DEFAULT_INPUT_DIR = Path("giant_output/raw")
DEFAULT_OUTPUT_CSV = Path("giant_output/items_enriched.csv")
OUTPUT_FIELDS = [
"retailer",
"order_id",
"line_no",
"observed_item_key",
"order_date",
"pod_id",
"item_name",
"upc",
"category_id",
"category",
"qty",
"unit",
"unit_price",
"line_total",
"picked_weight",
"mvp_savings",
"reward_savings",
"coupon_savings",
"coupon_price",
"image_url",
"raw_order_path",
"item_name_norm",
"brand_guess",
"variant",
"size_value",
"size_unit",
"pack_qty",
"measure_type",
"is_store_brand",
"is_fee",
"price_per_each",
"price_per_lb",
"price_per_oz",
"parse_version",
"parse_notes",
]
STORE_BRAND_PREFIXES = {
"SB": "SB",
"NP": "NP",
}
ABBREVIATIONS = {
"APPLE": "APPLE",
"APPLES": "APPLES",
"APLE": "APPLE",
"BASIL": "BASIL",
"BLK": "BLACK",
"BNLS": "BONELESS",
"BRWN": "BROWN",
"CARROTS": "CARROTS",
"CHDR": "CHEDDAR",
"CHICKEN": "CHICKEN",
"CHOC": "CHOCOLATE",
"CHS": "CHEESE",
"CHSE": "CHEESE",
"CHZ": "CHEESE",
"CILANTRO": "CILANTRO",
"CKI": "COOKIE",
"CRSHD": "CRUSHED",
"FLR": "FLOUR",
"FRSH": "FRESH",
"GALA": "GALA",
"GRAHM": "GRAHAM",
"HOT": "HOT",
"HRSRDSH": "HORSERADISH",
"IMP": "IMPORTED",
"IQF": "IQF",
"LENTILS": "LENTILS",
"LG": "LARGE",
"MLK": "MILK",
"MSTRD": "MUSTARD",
"ONION": "ONION",
"ORG": "ORGANIC",
"PEPPER": "PEPPER",
"PEPPERS": "PEPPERS",
"POT": "POTATO",
"POTATO": "POTATO",
"PPR": "PEPPER",
"RICOTTA": "RICOTTA",
"ROASTER": "ROASTER",
"ROTINI": "ROTINI",
"SCE": "SAUCE",
"SLC": "SLICED",
"SPINCH": "SPINACH",
"SPNC": "SPINACH",
"SPINACH": "SPINACH",
"SQZ": "SQUEEZE",
"SWT": "SWEET",
"THYME": "THYME",
"TOM": "TOMATO",
"TOMS": "TOMATOES",
"TRTL": "TORTILLA",
"VEG": "VEGETABLE",
"VINEGAR": "VINEGAR",
"WHT": "WHITE",
"WHOLE": "WHOLE",
"YLW": "YELLOW",
"YLWGLD": "YELLOW_GOLD",
}
FEE_PATTERNS = [
re.compile(r"\bBAG CHARGE\b"),
re.compile(r"\bDISC AT TOTAL\b"),
]
SIZE_RE = re.compile(r"(?<![A-Z0-9])(\d+(?:\.\d+)?)(?:\s*)(OZ|Z|LB|LBS|ML|L|FZ|FL OZ|QT|PT|GAL|GA)\b")
PACK_RE = re.compile(r"(?<![A-Z0-9])(\d+(?:\.\d+)?)(?:\s*)(CT|PK|PKG|PACK)\b")
def to_decimal(value):
if value in ("", None):
return None
try:
return Decimal(str(value))
except (InvalidOperation, ValueError):
return None
def format_decimal(value, places=4):
if value is None:
return ""
quant = Decimal("1").scaleb(-places)
normalized = value.quantize(quant, rounding=ROUND_HALF_UP).normalize()
return format(normalized, "f")
def normalize_whitespace(value):
return " ".join(str(value or "").strip().split())
def clean_item_name(name):
cleaned = normalize_whitespace(name).upper()
cleaned = re.sub(r"^\+", "", cleaned)
cleaned = re.sub(r"^PLU#\d+\s*", "", cleaned)
cleaned = cleaned.replace("#", " ")
return normalize_whitespace(cleaned)
def extract_store_brand_prefix(cleaned_name):
for prefix, brand in STORE_BRAND_PREFIXES.items():
if cleaned_name == prefix or cleaned_name.startswith(f"{prefix} "):
return prefix, brand
return "", ""
def extract_image_url(item):
image = item.get("image")
if isinstance(image, dict):
for key in ["xlarge", "large", "medium", "small"]:
value = image.get(key)
if value:
return value
if isinstance(image, str):
return image
return ""
def parse_size_and_pack(cleaned_name):
size_value = ""
size_unit = ""
pack_qty = ""
size_matches = list(SIZE_RE.finditer(cleaned_name))
if size_matches:
match = size_matches[-1]
size_value = normalize_number(match.group(1))
size_unit = normalize_unit(match.group(2))
pack_matches = list(PACK_RE.finditer(cleaned_name))
if pack_matches:
match = pack_matches[-1]
pack_qty = normalize_number(match.group(1))
return size_value, size_unit, pack_qty
def normalize_number(value):
decimal = to_decimal(value)
if decimal is None:
return ""
return format(decimal.normalize(), "f")
def normalize_unit(unit):
collapsed = normalize_whitespace(unit).upper()
return {
"Z": "oz",
"OZ": "oz",
"FZ": "fl_oz",
"FL OZ": "fl_oz",
"LB": "lb",
"LBS": "lb",
"ML": "ml",
"L": "l",
"QT": "qt",
"PT": "pt",
"GAL": "gal",
"GA": "gal",
}.get(collapsed, collapsed.lower())
def strip_measure_tokens(cleaned_name):
without_sizes = SIZE_RE.sub(" ", cleaned_name)
without_measures = PACK_RE.sub(" ", without_sizes)
return normalize_whitespace(without_measures)
def expand_token(token):
return ABBREVIATIONS.get(token, token)
def normalize_item_name(cleaned_name):
prefix, _brand = extract_store_brand_prefix(cleaned_name)
base = cleaned_name
if prefix:
base = normalize_whitespace(base[len(prefix):])
base = strip_measure_tokens(base)
expanded_tokens = [expand_token(token) for token in base.split()]
expanded = " ".join(token for token in expanded_tokens if token)
return normalize_whitespace(expanded)
def guess_measure_type(item, size_unit, pack_qty):
unit = normalize_whitespace(item.get("lbEachCd")).upper()
picked_weight = to_decimal(item.get("totalPickedWeight"))
qty = to_decimal(item.get("shipQy"))
if unit == "LB" or (picked_weight is not None and picked_weight > 0 and unit != "EA"):
return "weight"
if size_unit in {"lb", "oz"}:
return "weight"
if size_unit in {"ml", "l", "qt", "pt", "gal", "fl_oz"}:
return "volume"
if pack_qty:
return "count"
if unit == "EA" or (qty is not None and qty > 0):
return "each"
return ""
def is_fee_item(cleaned_name):
return any(pattern.search(cleaned_name) for pattern in FEE_PATTERNS)
def derive_prices(item, measure_type, size_value="", size_unit="", pack_qty=""):
qty = to_decimal(item.get("shipQy"))
line_total = to_decimal(item.get("groceryAmount"))
picked_weight = to_decimal(item.get("totalPickedWeight"))
parsed_size = to_decimal(size_value)
parsed_pack = to_decimal(pack_qty) or Decimal("1")
price_per_each = ""
price_per_lb = ""
price_per_oz = ""
if line_total is None:
return price_per_each, price_per_lb, price_per_oz
if measure_type == "each" and qty not in (None, Decimal("0")):
price_per_each = format_decimal(line_total / qty)
if measure_type == "count" and qty not in (None, Decimal("0")):
price_per_each = format_decimal(line_total / qty)
if measure_type == "weight" and picked_weight not in (None, Decimal("0")):
per_lb = line_total / picked_weight
price_per_lb = format_decimal(per_lb)
price_per_oz = format_decimal(per_lb / Decimal("16"))
return price_per_each, price_per_lb, price_per_oz
if measure_type == "weight" and parsed_size not in (None, Decimal("0")) and qty not in (None, Decimal("0")):
total_units = qty * parsed_pack * parsed_size
if size_unit == "lb":
per_lb = line_total / total_units
price_per_lb = format_decimal(per_lb)
price_per_oz = format_decimal(per_lb / Decimal("16"))
elif size_unit == "oz":
per_oz = line_total / total_units
price_per_oz = format_decimal(per_oz)
price_per_lb = format_decimal(per_oz * Decimal("16"))
return price_per_each, price_per_lb, price_per_oz
def parse_item(order_id, order_date, raw_path, line_no, item):
cleaned_name = clean_item_name(item.get("itemName", ""))
size_value, size_unit, pack_qty = parse_size_and_pack(cleaned_name)
prefix, brand_guess = extract_store_brand_prefix(cleaned_name)
normalized_name = normalize_item_name(cleaned_name)
measure_type = guess_measure_type(item, size_unit, pack_qty)
price_per_each, price_per_lb, price_per_oz = derive_prices(
item,
measure_type,
size_value=size_value,
size_unit=size_unit,
pack_qty=pack_qty,
)
is_fee = is_fee_item(cleaned_name)
parse_notes = []
if prefix:
parse_notes.append(f"store_brand_prefix={prefix}")
if is_fee:
parse_notes.append("fee_item")
if size_value and not size_unit:
parse_notes.append("size_without_unit")
return {
"retailer": RETAILER,
"order_id": str(order_id),
"line_no": str(line_no),
"observed_item_key": f"{RETAILER}:{order_id}:{line_no}",
"order_date": normalize_whitespace(order_date),
"pod_id": stringify(item.get("podId")),
"item_name": stringify(item.get("itemName")),
"upc": stringify(item.get("primUpcCd")),
"category_id": stringify(item.get("categoryId")),
"category": stringify(item.get("categoryDesc")),
"qty": stringify(item.get("shipQy")),
"unit": stringify(item.get("lbEachCd")),
"unit_price": stringify(item.get("unitPrice")),
"line_total": stringify(item.get("groceryAmount")),
"picked_weight": stringify(item.get("totalPickedWeight")),
"mvp_savings": stringify(item.get("mvpSavings")),
"reward_savings": stringify(item.get("rewardSavings")),
"coupon_savings": stringify(item.get("couponSavings")),
"coupon_price": stringify(item.get("couponPrice")),
"image_url": extract_image_url(item),
"raw_order_path": raw_path.as_posix(),
"item_name_norm": normalized_name,
"brand_guess": brand_guess,
"variant": "",
"size_value": size_value,
"size_unit": size_unit,
"pack_qty": pack_qty,
"measure_type": measure_type,
"is_store_brand": "true" if bool(prefix) else "false",
"is_fee": "true" if is_fee else "false",
"price_per_each": price_per_each,
"price_per_lb": price_per_lb,
"price_per_oz": price_per_oz,
"parse_version": PARSER_VERSION,
"parse_notes": ";".join(parse_notes),
}
def stringify(value):
if value is None:
return ""
return str(value)
def iter_order_rows(raw_dir):
for path in sorted(raw_dir.glob("*.json")):
if path.name == "history.json":
continue
payload = json.loads(path.read_text(encoding="utf-8"))
order_id = payload.get("orderId", path.stem)
order_date = payload.get("orderDate", "")
for line_no, item in enumerate(payload.get("items", []), start=1):
yield parse_item(order_id, order_date, path, line_no, item)
def build_items_enriched(raw_dir):
rows = list(iter_order_rows(raw_dir))
rows.sort(key=lambda row: (row["order_date"], row["order_id"], int(row["line_no"])))
return rows
def write_csv(path, rows):
path.parent.mkdir(parents=True, exist_ok=True)
with path.open("w", newline="", encoding="utf-8") as handle:
writer = csv.DictWriter(handle, fieldnames=OUTPUT_FIELDS)
writer.writeheader()
writer.writerows(rows)
@click.command()
@click.option(
"--input-dir",
default=str(DEFAULT_INPUT_DIR),
show_default=True,
help="Directory containing Giant raw order json files.",
)
@click.option(
"--output-csv",
default=str(DEFAULT_OUTPUT_CSV),
show_default=True,
help="CSV path for enriched Giant item rows.",
)
def main(input_dir, output_csv):
raw_dir = Path(input_dir)
output_path = Path(output_csv)
if not raw_dir.exists():
raise click.ClickException(f"input dir does not exist: {raw_dir}")
rows = build_items_enriched(raw_dir)
write_csv(output_path, rows)
click.echo(f"wrote {len(rows)} rows to {output_path}")
if __name__ == "__main__":
main()

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@@ -32,11 +32,11 @@
- keep schema minimal but extensible - keep schema minimal but extensible
** evidence ** evidence
- commit: - commit: `42dbae1` on branch `cx`
- 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` - 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: 2026-03-15 - date: 2026-03-15
* [ ] t1.3: build giant parser/enricher from raw json (2-4 commits) * [X] t1.3: build giant parser/enricher from raw json (2-4 commits)
** acceptance criteria ** acceptance criteria
- parser reads giant raw order json files - parser reads giant raw order json files
- outputs `items_enriched.csv` - outputs `items_enriched.csv`
@@ -55,8 +55,8 @@
** evidence ** evidence
- commit: - commit:
- tests: - tests: `./venv/bin/python -m unittest discover -s tests`; `./venv/bin/python enrich_giant.py`; verified `giant_output/items_enriched.csv` on real raw data
- date: - date: 2026-03-16
* [ ] t1.4: generate observed-product layer from enriched items (2-3 commits) * [ ] t1.4: generate observed-product layer from enriched items (2-3 commits)

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tests/test_enrich_giant.py Normal file
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import csv
import json
import tempfile
import unittest
from pathlib import Path
import enrich_giant
class EnrichGiantTests(unittest.TestCase):
def test_parse_size_and_pack_handles_pack_and_weight_tokens(self):
size_value, size_unit, pack_qty = enrich_giant.parse_size_and_pack(
"COKE CHERRY 6PK 7.5Z"
)
self.assertEqual("7.5", size_value)
self.assertEqual("oz", size_unit)
self.assertEqual("6", pack_qty)
def test_parse_item_marks_store_brand_fee_and_weight_prices(self):
row = enrich_giant.parse_item(
order_id="abc123",
order_date="2026-03-01",
raw_path=Path("raw/abc123.json"),
line_no=1,
item={
"podId": 1,
"shipQy": 1,
"totalPickedWeight": 2,
"unitPrice": 3.98,
"itemName": "+SB GALA APPLE 5 LB",
"lbEachCd": "LB",
"groceryAmount": 3.98,
"primUpcCd": "111",
"mvpSavings": 0,
"rewardSavings": 0,
"couponSavings": 0,
"couponPrice": 0,
"categoryId": "1",
"categoryDesc": "Grocery",
"image": {"large": "https://example.test/apple.jpg"},
},
)
self.assertEqual("SB", row["brand_guess"])
self.assertEqual("GALA APPLE", row["item_name_norm"])
self.assertEqual("5", row["size_value"])
self.assertEqual("lb", row["size_unit"])
self.assertEqual("weight", row["measure_type"])
self.assertEqual("true", row["is_store_brand"])
self.assertEqual("1.99", row["price_per_lb"])
self.assertEqual("0.1244", row["price_per_oz"])
self.assertEqual("https://example.test/apple.jpg", row["image_url"])
fee_row = enrich_giant.parse_item(
order_id="abc123",
order_date="2026-03-01",
raw_path=Path("raw/abc123.json"),
line_no=2,
item={
"podId": 2,
"shipQy": 1,
"totalPickedWeight": 0,
"unitPrice": 0.05,
"itemName": "GL BAG CHARGE",
"lbEachCd": "EA",
"groceryAmount": 0.05,
"primUpcCd": "",
"mvpSavings": 0,
"rewardSavings": 0,
"couponSavings": 0,
"couponPrice": 0,
"categoryId": "1",
"categoryDesc": "Grocery",
},
)
self.assertEqual("true", fee_row["is_fee"])
self.assertEqual("GL BAG CHARGE", fee_row["item_name_norm"])
def test_parse_item_derives_packaged_weight_prices_from_size_tokens(self):
row = enrich_giant.parse_item(
order_id="abc123",
order_date="2026-03-01",
raw_path=Path("raw/abc123.json"),
line_no=1,
item={
"podId": 1,
"shipQy": 2,
"totalPickedWeight": 0,
"unitPrice": 3.0,
"itemName": "PEPSI 6PK 7.5Z",
"lbEachCd": "EA",
"groceryAmount": 6.0,
"primUpcCd": "111",
"mvpSavings": 0,
"rewardSavings": 0,
"couponSavings": 0,
"couponPrice": 0,
"categoryId": "1",
"categoryDesc": "Grocery",
},
)
self.assertEqual("weight", row["measure_type"])
self.assertEqual("6", row["pack_qty"])
self.assertEqual("7.5", row["size_value"])
self.assertEqual("0.0667", row["price_per_oz"])
self.assertEqual("1.0667", row["price_per_lb"])
def test_build_items_enriched_reads_raw_order_files_and_writes_csv(self):
with tempfile.TemporaryDirectory() as tmpdir:
raw_dir = Path(tmpdir) / "raw"
raw_dir.mkdir()
(raw_dir / "history.json").write_text("{}", encoding="utf-8")
(raw_dir / "order-2.json").write_text(
json.dumps(
{
"orderId": "order-2",
"orderDate": "2026-03-02",
"items": [
{
"podId": 20,
"shipQy": 1,
"totalPickedWeight": 0,
"unitPrice": 2.99,
"itemName": "SB ROTINI 16Z",
"lbEachCd": "EA",
"groceryAmount": 2.99,
"primUpcCd": "222",
"mvpSavings": 0,
"rewardSavings": 0,
"couponSavings": 0,
"couponPrice": 0,
"categoryId": "1",
"categoryDesc": "Grocery",
"image": {"small": "https://example.test/rotini.jpg"},
}
],
}
),
encoding="utf-8",
)
(raw_dir / "order-1.json").write_text(
json.dumps(
{
"orderId": "order-1",
"orderDate": "2026-03-01",
"items": [
{
"podId": 10,
"shipQy": 2,
"totalPickedWeight": 0,
"unitPrice": 1.5,
"itemName": "PEPSI 6PK 7.5Z",
"lbEachCd": "EA",
"groceryAmount": 3.0,
"primUpcCd": "111",
"mvpSavings": 0,
"rewardSavings": 0,
"couponSavings": 0,
"couponPrice": 0,
"categoryId": "1",
"categoryDesc": "Grocery",
}
],
}
),
encoding="utf-8",
)
rows = enrich_giant.build_items_enriched(raw_dir)
output_csv = Path(tmpdir) / "items_enriched.csv"
enrich_giant.write_csv(output_csv, rows)
self.assertEqual(["order-1", "order-2"], [row["order_id"] for row in rows])
self.assertEqual("PEPSI", rows[0]["item_name_norm"])
self.assertEqual("6", rows[0]["pack_qty"])
self.assertEqual("7.5", rows[0]["size_value"])
self.assertEqual("true", rows[1]["is_store_brand"])
with output_csv.open(newline="", encoding="utf-8") as handle:
written_rows = list(csv.DictReader(handle))
self.assertEqual(2, len(written_rows))
self.assertEqual(enrich_giant.OUTPUT_FIELDS, list(written_rows[0].keys()))
if __name__ == "__main__":
unittest.main()