SLICE-8: Shopify dialect — detect/map Shopify export at the codec boundary + DOC-2/3 (SD-0002 §7.2) #32
@@ -6,6 +6,7 @@ from __future__ import annotations
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import csv
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import io
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from .dialect_shopify import is_shopify_header, map_shopify_header
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from .errors import FileRejected
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from .models import KNOWN_COLUMNS, MAX_DATA_ROWS, MAX_FILE_BYTES, ParsedFile, Row
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@@ -13,8 +14,8 @@ _REQUIRED_HEADER_COLUMNS = ("Handle", "Title")
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def detect_dialect(header: list[str]) -> str:
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"""The INV-17 seam: SLICE-8 recognizes Shopify's exact header set here."""
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return "canonical"
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"""The INV-17 seam: recognize Shopify's header set, else canonical (§6.5.1)."""
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return "shopify" if is_shopify_header(header) else "canonical"
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def parse_csv(data: bytes) -> ParsedFile:
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@@ -31,19 +32,34 @@ def parse_csv(data: bytes) -> ParsedFile:
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except StopIteration:
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raise FileRejected("not_csv", "This file isn't readable as CSV.") from None
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header = [h.strip() for h in raw_header]
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dialect = detect_dialect(header)
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# INV-17: normalize the header to canonical names at the boundary. mapped[i]
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# is the canonical name for header[i] (or None when that column has no
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# canonical home); unknown is the not-imported warning list. Canonical files
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# map to themselves; unknown columns are warned exactly as before.
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if dialect == "shopify":
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mapped, unknown = map_shopify_header(header)
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else:
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mapped = [c if c in KNOWN_COLUMNS else None for c in header]
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unknown = [c for c in header if c and c not in KNOWN_COLUMNS]
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for col in _REQUIRED_HEADER_COLUMNS:
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if col not in header:
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if col not in mapped:
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raise FileRejected(
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"missing_required_column",
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f"This file is missing the required column '{col}'.",
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)
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# First occurrence of a duplicated column wins.
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# First occurrence of a duplicated canonical column wins.
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col_index: dict[str, int] = {}
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for i, name in enumerate(header):
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for i, name in enumerate(mapped):
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if name and name not in col_index:
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col_index[name] = i
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known_present = [c for c in col_index if c in KNOWN_COLUMNS]
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unknown = [c for c in col_index if c not in KNOWN_COLUMNS]
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# De-dup the warning list, order-preserving.
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seen: set[str] = set()
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unknown = [c for c in unknown if not (c in seen or seen.add(c))]
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rows: list[Row] = []
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for raw in reader:
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if not any(cell.strip() for cell in raw):
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@@ -55,11 +71,12 @@ def parse_csv(data: bytes) -> ParsedFile:
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)
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cells = {
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c: (raw[col_index[c]].strip() if col_index[c] < len(raw) else "")
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for c in known_present
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for c in col_index
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}
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# Shopify grams carry an implicit unit; canonical needs it explicit (§6.5.1).
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if dialect == "shopify" and cells.get("Variant Weight"):
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cells["Variant Weight Unit"] = "g"
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rows.append(Row(line_number=reader.line_num, cells=cells))
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except csv.Error:
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raise FileRejected("not_csv", "This file isn't readable as CSV.") from None
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return ParsedFile(
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dialect=detect_dialect(header), header=header, unknown_columns=unknown, rows=rows
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)
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return ParsedFile(dialect=dialect, header=header, unknown_columns=unknown, rows=rows)
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@@ -67,3 +67,29 @@ def test_missing_column_message_names_the_column():
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with pytest.raises(FileRejected) as exc:
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parse_csv(_csv("Handle,Vendor", "mug,Acme"))
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assert "'Title'" in exc.value.message
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def test_parse_detects_and_maps_shopify():
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data = (
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"Handle,Title,Body (HTML),Cost per item,Variant Price,Variant Grams,Type,Gift Card\n"
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"mug,Moon Mug,<p>Grey</p>,9.50,18.00,300,Drinkware,false\n"
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).encode("utf-8")
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parsed = parse_csv(data)
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assert parsed.dialect == "shopify"
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cells = parsed.rows[0].cells
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assert cells["Description"] == "<p>Grey</p>"
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assert cells["Variant Cost"] == "9.50"
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assert cells["Variant Weight"] == "300"
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assert cells["Variant Weight Unit"] == "g" # synthesized
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# Type (free-text) and Gift Card warned, never mapped:
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assert "Type" in parsed.unknown_columns
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assert "Gift Card" in parsed.unknown_columns
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assert "product_type" not in str(cells) # Type never reached canonical
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def test_parse_canonical_unchanged():
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data = b"Handle,Title,Description,Variant Price\nmug,Moon Mug,Grey,18.00\n"
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parsed = parse_csv(data)
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assert parsed.dialect == "canonical"
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assert parsed.rows[0].cells["Description"] == "Grey"
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assert parsed.unknown_columns == []
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