413 lines
15 KiB
Python
413 lines
15 KiB
Python
from decimal import Decimal
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from pathlib import Path
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import click
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import build_canonical_layer
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import build_observed_products
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import validate_cross_retailer_flow
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from enrich_giant import format_decimal, to_decimal
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from layer_helpers import read_csv_rows, stable_id, write_csv_rows
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PURCHASE_FIELDS = [
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"purchase_date",
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"retailer",
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"order_id",
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"line_no",
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"observed_item_key",
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"observed_product_id",
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"canonical_product_id",
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"review_status",
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"resolution_action",
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"raw_item_name",
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"normalized_item_name",
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"retailer_item_id",
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"upc",
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"qty",
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"unit",
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"pack_qty",
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"size_value",
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"size_unit",
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"measure_type",
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"line_total",
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"unit_price",
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"store_name",
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"store_number",
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"store_city",
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"store_state",
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"price_per_each",
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"price_per_each_basis",
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"price_per_count",
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"price_per_count_basis",
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"price_per_lb",
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"price_per_lb_basis",
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"price_per_oz",
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"price_per_oz_basis",
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"is_discount_line",
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"is_coupon_line",
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"is_fee",
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"raw_order_path",
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]
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EXAMPLE_FIELDS = [
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"example_name",
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"canonical_product_id",
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"giant_purchase_date",
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"giant_raw_item_name",
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"giant_price_per_lb",
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"costco_purchase_date",
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"costco_raw_item_name",
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"costco_price_per_lb",
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"notes",
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]
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CATALOG_FIELDS = [
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"canonical_product_id",
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"canonical_name",
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"category",
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"product_type",
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"brand",
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"variant",
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"size_value",
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"size_unit",
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"pack_qty",
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"measure_type",
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"notes",
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"created_at",
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"updated_at",
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]
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RESOLUTION_FIELDS = [
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"observed_product_id",
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"canonical_product_id",
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"resolution_action",
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"status",
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"resolution_notes",
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"reviewed_at",
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]
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def decimal_or_zero(value):
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return to_decimal(value) or Decimal("0")
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def derive_metrics(row):
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line_total = to_decimal(row.get("line_total"))
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qty = to_decimal(row.get("qty"))
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pack_qty = to_decimal(row.get("pack_qty"))
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size_value = to_decimal(row.get("size_value"))
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picked_weight = to_decimal(row.get("picked_weight"))
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size_unit = row.get("size_unit", "")
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price_per_each = row.get("price_per_each", "")
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price_per_lb = row.get("price_per_lb", "")
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price_per_oz = row.get("price_per_oz", "")
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price_per_count = ""
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basis_each = ""
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basis_count = ""
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basis_lb = ""
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basis_oz = ""
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if price_per_each:
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basis_each = "line_total_over_qty"
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elif line_total is not None and qty not in (None, 0):
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price_per_each = format_decimal(line_total / qty)
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basis_each = "line_total_over_qty"
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if line_total is not None and pack_qty not in (None, 0):
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total_count = pack_qty * (qty or Decimal("1"))
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if total_count not in (None, 0):
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price_per_count = format_decimal(line_total / total_count)
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basis_count = "line_total_over_pack_qty"
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if picked_weight not in (None, 0):
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price_per_lb = format_decimal(line_total / picked_weight) if line_total is not None else ""
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price_per_oz = (
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format_decimal((line_total / picked_weight) / Decimal("16"))
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if line_total is not None
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else ""
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)
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basis_lb = "picked_weight_lb"
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basis_oz = "picked_weight_lb_to_oz"
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elif line_total is not None and size_value not in (None, 0):
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total_units = size_value * (pack_qty or Decimal("1")) * (qty or Decimal("1"))
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if size_unit == "lb" and total_units not in (None, 0):
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per_lb = line_total / total_units
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price_per_lb = format_decimal(per_lb)
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price_per_oz = format_decimal(per_lb / Decimal("16"))
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basis_lb = "parsed_size_lb"
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basis_oz = "parsed_size_lb_to_oz"
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elif size_unit == "oz" and total_units not in (None, 0):
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per_oz = line_total / total_units
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price_per_oz = format_decimal(per_oz)
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price_per_lb = format_decimal(per_oz * Decimal("16"))
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basis_lb = "parsed_size_oz_to_lb"
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basis_oz = "parsed_size_oz"
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return {
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"price_per_each": price_per_each,
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"price_per_each_basis": basis_each,
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"price_per_count": price_per_count,
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"price_per_count_basis": basis_count,
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"price_per_lb": price_per_lb,
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"price_per_lb_basis": basis_lb,
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"price_per_oz": price_per_oz,
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"price_per_oz_basis": basis_oz,
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}
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def order_lookup(rows, retailer):
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return {
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(retailer, row["order_id"]): row
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for row in rows
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}
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def read_optional_csv_rows(path):
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path = Path(path)
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if not path.exists():
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return []
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return read_csv_rows(path)
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def load_resolution_lookup(resolution_rows):
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lookup = {}
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for row in resolution_rows:
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if not row.get("observed_product_id"):
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continue
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lookup[row["observed_product_id"]] = row
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return lookup
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def merge_catalog_rows(existing_rows, auto_rows):
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merged = {}
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for row in auto_rows + existing_rows:
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canonical_product_id = row.get("canonical_product_id", "")
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if canonical_product_id:
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merged[canonical_product_id] = row
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return sorted(merged.values(), key=lambda row: row["canonical_product_id"])
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def catalog_row_from_canonical(row):
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return {
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"canonical_product_id": row.get("canonical_product_id", ""),
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"canonical_name": row.get("canonical_name", ""),
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"category": row.get("category", ""),
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"product_type": row.get("product_type", ""),
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"brand": row.get("brand", ""),
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"variant": row.get("variant", ""),
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"size_value": row.get("size_value", ""),
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"size_unit": row.get("size_unit", ""),
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"pack_qty": row.get("pack_qty", ""),
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"measure_type": row.get("measure_type", ""),
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"notes": row.get("notes", ""),
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"created_at": row.get("created_at", ""),
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"updated_at": row.get("updated_at", ""),
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}
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def build_link_state(enriched_rows):
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observed_rows = build_observed_products.build_observed_products(enriched_rows)
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canonical_rows, link_rows = build_canonical_layer.build_canonical_layer(observed_rows)
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giant_row, costco_row = validate_cross_retailer_flow.find_proof_pair(observed_rows)
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canonical_rows, link_rows, _proof_rows = validate_cross_retailer_flow.merge_proof_pair(
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canonical_rows,
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link_rows,
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giant_row,
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costco_row,
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)
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observed_id_by_key = {
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row["observed_key"]: row["observed_product_id"] for row in observed_rows
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}
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canonical_id_by_observed = {
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row["observed_product_id"]: row["canonical_product_id"] for row in link_rows
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}
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return observed_rows, canonical_rows, link_rows, observed_id_by_key, canonical_id_by_observed
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def build_purchase_rows(
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giant_enriched_rows,
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costco_enriched_rows,
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giant_orders,
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costco_orders,
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resolution_rows,
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):
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all_enriched_rows = giant_enriched_rows + costco_enriched_rows
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(
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observed_rows,
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canonical_rows,
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link_rows,
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observed_id_by_key,
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canonical_id_by_observed,
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) = build_link_state(all_enriched_rows)
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resolution_lookup = load_resolution_lookup(resolution_rows)
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for observed_product_id, resolution in resolution_lookup.items():
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action = resolution.get("resolution_action", "")
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status = resolution.get("status", "")
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if status != "approved":
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continue
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if action in {"link", "create"} and resolution.get("canonical_product_id"):
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canonical_id_by_observed[observed_product_id] = resolution["canonical_product_id"]
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elif action == "exclude":
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canonical_id_by_observed[observed_product_id] = ""
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orders_by_id = {}
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orders_by_id.update(order_lookup(giant_orders, "giant"))
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orders_by_id.update(order_lookup(costco_orders, "costco"))
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purchase_rows = []
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for row in sorted(
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all_enriched_rows,
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key=lambda item: (item["order_date"], item["retailer"], item["order_id"], int(item["line_no"])),
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):
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observed_key = build_observed_products.build_observed_key(row)
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observed_product_id = observed_id_by_key.get(observed_key, "")
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order_row = orders_by_id.get((row["retailer"], row["order_id"]), {})
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metrics = derive_metrics(row)
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resolution = resolution_lookup.get(observed_product_id, {})
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purchase_rows.append(
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{
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"purchase_date": row["order_date"],
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"retailer": row["retailer"],
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"order_id": row["order_id"],
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"line_no": row["line_no"],
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"observed_item_key": row["observed_item_key"],
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"observed_product_id": observed_product_id,
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"canonical_product_id": canonical_id_by_observed.get(observed_product_id, ""),
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"review_status": resolution.get("status", ""),
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"resolution_action": resolution.get("resolution_action", ""),
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"raw_item_name": row["item_name"],
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"normalized_item_name": row["item_name_norm"],
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"retailer_item_id": row["retailer_item_id"],
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"upc": row["upc"],
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"qty": row["qty"],
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"unit": row["unit"],
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"pack_qty": row["pack_qty"],
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"size_value": row["size_value"],
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"size_unit": row["size_unit"],
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"measure_type": row["measure_type"],
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"line_total": row["line_total"],
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"unit_price": row["unit_price"],
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"store_name": order_row.get("store_name", ""),
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"store_number": order_row.get("store_number", ""),
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"store_city": order_row.get("store_city", ""),
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"store_state": order_row.get("store_state", ""),
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"is_discount_line": row["is_discount_line"],
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"is_coupon_line": row["is_coupon_line"],
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"is_fee": row["is_fee"],
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"raw_order_path": row["raw_order_path"],
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**metrics,
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}
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)
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return purchase_rows, observed_rows, canonical_rows, link_rows
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def apply_manual_resolutions_to_links(link_rows, resolution_rows):
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link_by_observed = {row["observed_product_id"]: dict(row) for row in link_rows}
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for resolution in resolution_rows:
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if resolution.get("status") != "approved":
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continue
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observed_product_id = resolution.get("observed_product_id", "")
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action = resolution.get("resolution_action", "")
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if not observed_product_id:
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continue
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if action == "exclude":
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link_by_observed.pop(observed_product_id, None)
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continue
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if action in {"link", "create"} and resolution.get("canonical_product_id"):
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link_by_observed[observed_product_id] = {
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"observed_product_id": observed_product_id,
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"canonical_product_id": resolution["canonical_product_id"],
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"link_method": f"manual_{action}",
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"link_confidence": "high",
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"review_status": resolution.get("status", ""),
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"reviewed_by": "",
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"reviewed_at": resolution.get("reviewed_at", ""),
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"link_notes": resolution.get("resolution_notes", ""),
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}
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return sorted(link_by_observed.values(), key=lambda row: row["observed_product_id"])
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def build_comparison_examples(purchase_rows):
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giant_banana = None
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costco_banana = None
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for row in purchase_rows:
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if row.get("normalized_item_name") != "BANANA":
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continue
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if not row.get("canonical_product_id"):
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continue
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if row["retailer"] == "giant" and row.get("price_per_lb"):
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giant_banana = row
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if row["retailer"] == "costco" and row.get("price_per_lb"):
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costco_banana = row
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if not giant_banana or not costco_banana:
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return []
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return [
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{
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"example_name": "banana_price_per_lb",
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"canonical_product_id": giant_banana["canonical_product_id"],
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"giant_purchase_date": giant_banana["purchase_date"],
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"giant_raw_item_name": giant_banana["raw_item_name"],
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"giant_price_per_lb": giant_banana["price_per_lb"],
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"costco_purchase_date": costco_banana["purchase_date"],
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"costco_raw_item_name": costco_banana["raw_item_name"],
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"costco_price_per_lb": costco_banana["price_per_lb"],
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"notes": "Example comparison using normalized price_per_lb across Giant and Costco",
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}
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]
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@click.command()
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@click.option("--giant-items-enriched-csv", default="giant_output/items_enriched.csv", show_default=True)
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@click.option("--costco-items-enriched-csv", default="costco_output/items_enriched.csv", show_default=True)
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@click.option("--giant-orders-csv", default="giant_output/orders.csv", show_default=True)
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@click.option("--costco-orders-csv", default="costco_output/orders.csv", show_default=True)
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@click.option("--resolutions-csv", default="combined_output/review_resolutions.csv", show_default=True)
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@click.option("--catalog-csv", default="combined_output/canonical_catalog.csv", show_default=True)
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@click.option("--links-csv", default="combined_output/product_links.csv", show_default=True)
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@click.option("--output-csv", default="combined_output/purchases.csv", show_default=True)
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@click.option("--examples-csv", default="combined_output/comparison_examples.csv", show_default=True)
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def main(
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giant_items_enriched_csv,
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costco_items_enriched_csv,
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giant_orders_csv,
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costco_orders_csv,
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resolutions_csv,
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catalog_csv,
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links_csv,
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output_csv,
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examples_csv,
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):
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resolution_rows = read_optional_csv_rows(resolutions_csv)
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purchase_rows, _observed_rows, canonical_rows, link_rows = build_purchase_rows(
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read_csv_rows(giant_items_enriched_csv),
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read_csv_rows(costco_items_enriched_csv),
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read_csv_rows(giant_orders_csv),
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read_csv_rows(costco_orders_csv),
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resolution_rows,
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)
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existing_catalog_rows = read_optional_csv_rows(catalog_csv)
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merged_catalog_rows = merge_catalog_rows(
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existing_catalog_rows,
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[catalog_row_from_canonical(row) for row in canonical_rows],
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)
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link_rows = apply_manual_resolutions_to_links(link_rows, resolution_rows)
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example_rows = build_comparison_examples(purchase_rows)
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write_csv_rows(catalog_csv, merged_catalog_rows, CATALOG_FIELDS)
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write_csv_rows(links_csv, link_rows, build_canonical_layer.LINK_FIELDS)
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write_csv_rows(output_csv, purchase_rows, PURCHASE_FIELDS)
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write_csv_rows(examples_csv, example_rows, EXAMPLE_FIELDS)
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click.echo(
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f"wrote {len(purchase_rows)} purchase rows to {output_csv}, "
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f"{len(merged_catalog_rows)} catalog rows to {catalog_csv}, "
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f"and {len(example_rows)} comparison examples to {examples_csv}"
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)
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if __name__ == "__main__":
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main()
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