From cbfbf42d53d98667dab83ea6b61496b01914d685 Mon Sep 17 00:00:00 2001
From: Ricard Illa <ricard@trkkn.com>
Date: Fri, 23 Jun 2023 15:29:57 +0200
Subject: [PATCH] feat: added gtin13 column

---
 pipeline/beam_etl/helpers/parse_row.py | 104 +++++++++++++++++++++++++
 1 file changed, 104 insertions(+)
 create mode 100644 pipeline/beam_etl/helpers/parse_row.py

diff --git a/pipeline/beam_etl/helpers/parse_row.py b/pipeline/beam_etl/helpers/parse_row.py
new file mode 100644
index 0000000..b597f6b
--- /dev/null
+++ b/pipeline/beam_etl/helpers/parse_row.py
@@ -0,0 +1,104 @@
+"""Helper function to parse rows into cleaner data that can be inserted into
+the destination database"""
+
+import logging
+from typing import TypedDict, Dict, Optional, List
+
+from helpers.parse_xml import parse_raw_specs
+from helpers.materials import parse_materials
+from helpers.origin import clean_origin_name
+from helpers.dimensions import parse_dimensions
+from helpers.weight import parse_weight, dimensional_weight
+
+
+class CleanRow(TypedDict):
+    """Type to represent clean rows to be inserted in the database"""
+
+    gtin13: int
+    tcin: int
+    primary_category: str
+    materials: Optional[List[str]]
+    packaging: int
+    origin: str
+    height: Optional[float]
+    depth: Optional[float]
+    width: Optional[float]
+    weight: Optional[float]
+
+
+def parse_row(element: Dict[str, str]) -> Optional[CleanRow]:
+    """Parse a dictionary representing a row for the CSV input into a cleaner
+    dictionary representing a row to be inserted in the database"""
+
+    # gtin13 should always be there
+    try:
+        gtin13 = element["gtin13"]
+    except KeyError:
+        logging.error("gtin13 missing")
+        return None
+
+    try:
+        gtin13 = int(gtin13.strip())
+    except ValueError:
+        logging.error("malformed GTIN13")
+        return None
+
+    # primary category should always be there
+    try:
+        primary_category = element["primary_category"]
+    except KeyError:
+        logging.error("primary_category missing")
+        return None
+
+    specifications = parse_raw_specs(element["raw_specifications"])
+    if specifications is None:
+        logging.error("could not parse raw_specifications")
+        return None
+
+    # TCIN should be a mandatory field in the from of an int
+    try:
+        tcin_value = specifications["tcin"]
+    except KeyError:
+        logging.error("TCIN missing")
+        return None
+
+    try:
+        tcin = int(tcin_value.strip())
+    except ValueError:
+        logging.error("malformed TCIN")
+        return None
+
+    materials = parse_materials(specifications.get("materials"))
+
+    # if packaging is not specified, assume only one unit is found in the
+    # package
+    packaging = specifications.get("packaging", 1)
+    try:
+        packaging = int(packaging)
+    except ValueError:
+        logging.error("could not cast packaging %s into an integer")
+        packaging = 1
+
+    origin = clean_origin_name(specifications.get("origin"))
+
+    dimensions = parse_dimensions(specifications.get("dimensions"))
+    height = dimensions["height"]
+    width = dimensions["width"]
+    depth = dimensions["depth"]
+
+    weight = parse_weight(specifications.get("weight"))
+    if weight is None:
+        weight = dimensional_weight(height=height, width=weight, depth=depth)
+
+    return {
+        "gtin13": gtin13,
+        "tcin": tcin,
+        "primary_category": primary_category,
+        "materials": materials,
+        "packaging": packaging,
+        "origin": origin,
+        "height": height,
+        "width": width,
+        "depth": depth,
+        "weight": weight,
+    }