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"""Business schema, migrations and deterministic seed for the llbean clone.
The catalog rows come from source-observed evidence captured with Playwright in
the Mac Chrome session (see ``materials/llbean/scope/notes/``). Review bodies,
store rows, accounts, addresses and orders are synthetic fixtures: the source
never exposed them in a form this clone may persist.
"""
from __future__ import annotations
import hashlib
import json
import sqlite3
from pathlib import Path
from typing import Any
SEED_DIR = Path(__file__).resolve().parents[1] / "data" / "seed"
# Colour buckets are the 13 facet values observed on the source category page.
COLOR_BUCKETS: dict[str, tuple[str, ...]] = {
"Black": ("black", "carbon", "onyx", "jet"),
"Blue": ("blue", "navy", "teal", "indigo", "denim", "nautical", "mallard"),
"Brown": ("brown", "bark", "chocolate", "coffee", "walnut", "espresso"),
"Gray": ("gray", "grey", "graphite", "granite", "slate", "mineral", "charcoal"),
"Green": ("green", "olive", "sage", "moss", "spruce", "forest", "fatigue"),
"Orange": ("orange", "rust", "blaze", "burnt", "apricot"),
"Pink": ("pink", "rose", "blush", "coral"),
"Purple": ("purple", "plum", "violet", "lilac"),
"Red": ("red", "crimson", "cardinal", "scarlet", "burgundy", "wine"),
"Tan": ("tan", "khaki", "sand", "camel", "oatmeal", "wheat", "putty", "stone"),
"White": ("white", "cream", "ivory", "natural", "bone"),
"Yellow": ("yellow", "gold", "mustard", "honey", "citron"),
"Multicolor": ("plaid", "print", "multi", "stripe", "camo", "tartan", "buffalo"),
}
# Brand names observed in the source Brand facet.
KNOWN_BRANDS = (
"L.L.Bean",
"Anglers Image",
"Anglers Sport Group",
"Boyt",
"Buck",
"Buff",
"Byer of Maine",
"Camelbak",
"Clic",
"Darn Tough",
"ENO",
"ExOfficio",
"Fishpond",
"Flip Focal",
"Garmin",
"Gear Keeper",
"Hydro Flask",
"Leatherman",
"Nalgene",
"Osprey",
"Smartwool",
"Thule",
"Yeti",
)
# Price bands are the nine bands observed in the source Price facet.
PRICE_BANDS: tuple[tuple[str, float, float], ...] = (
("$0 to $30", 0.0, 30.0),
("$30 to $50", 30.0, 50.0),
("$50 to $75", 50.0, 75.0),
("$75 to $100", 75.0, 100.0),
("$100 to $150", 100.0, 150.0),
("$150 to $250", 150.0, 250.0),
("$250 to $500", 250.0, 500.0),
("$500 to $1000", 500.0, 1000.0),
("$1000 to $5000", 1000.0, 5000.0),
)
# The Sale collection filters by discount depth, as the source's "% Off" facet does.
PERCENT_OFF_BANDS: tuple[tuple[str, int, int], ...] = (
("20% Off & More", 20, 1000),
("30% Off & More", 30, 1000),
("40% Off & More", 40, 1000),
("50% Off & More", 50, 1000),
)
SORT_FIELDS: dict[str, str] = {
"relevance": "Recommended",
"price_low_high": "Price: Low to High",
"price_high_low": "Price: High to Low",
"bestselling": "Bestselling",
"newest": "Newest",
"rating": "Customer Rating",
}
VIEW_COUNT = 48
SCHEMA = """
CREATE TABLE IF NOT EXISTS categories (
cat_id INTEGER PRIMARY KEY,
name TEXT NOT NULL,
slug TEXT,
parent_id INTEGER,
depth INTEGER NOT NULL DEFAULT 0,
nav_order INTEGER NOT NULL DEFAULT 0,
kind TEXT NOT NULL DEFAULT 'category',
tile_image TEXT,
tile_alt TEXT
);
CREATE TABLE IF NOT EXISTS products (
product_id TEXT PRIMARY KEY,
slug TEXT,
name TEXT NOT NULL,
item_number TEXT,
brand TEXT NOT NULL DEFAULT 'L.L.Bean',
description TEXT,
material TEXT,
price_low REAL NOT NULL,
price_high REAL NOT NULL,
list_price REAL NOT NULL,
sale_price REAL,
on_sale INTEGER NOT NULL DEFAULT 0,
is_new INTEGER NOT NULL DEFAULT 0,
rating REAL,
review_count INTEGER NOT NULL DEFAULT 0,
availability TEXT NOT NULL DEFAULT 'InStock',
low_inventory INTEGER NOT NULL DEFAULT 0,
color_count INTEGER NOT NULL DEFAULT 0,
gender TEXT,
percent_off INTEGER NOT NULL DEFAULT 0,
grid_image TEXT,
grid_image_alt TEXT,
position INTEGER NOT NULL DEFAULT 0,
breadcrumb TEXT NOT NULL DEFAULT '[]'
);
CREATE TABLE IF NOT EXISTS product_categories (
product_id TEXT NOT NULL,
cat_id INTEGER NOT NULL,
PRIMARY KEY (product_id, cat_id)
);
CREATE TABLE IF NOT EXISTS product_images (
product_id TEXT NOT NULL,
idx INTEGER NOT NULL,
asset TEXT NOT NULL,
caption TEXT,
PRIMARY KEY (product_id, idx)
);
CREATE TABLE IF NOT EXISTS product_colors (
product_id TEXT NOT NULL,
idx INTEGER NOT NULL,
name TEXT NOT NULL,
bucket TEXT,
swatch TEXT,
price REAL,
PRIMARY KEY (product_id, idx)
);
CREATE TABLE IF NOT EXISTS product_sizes (
product_id TEXT NOT NULL,
idx INTEGER NOT NULL,
name TEXT NOT NULL,
in_stock INTEGER NOT NULL DEFAULT 1,
PRIMARY KEY (product_id, idx)
);
CREATE TABLE IF NOT EXISTS reviews (
review_id INTEGER PRIMARY KEY AUTOINCREMENT,
product_id TEXT NOT NULL,
rating INTEGER NOT NULL,
title TEXT NOT NULL,
body TEXT NOT NULL,
author TEXT NOT NULL,
location TEXT,
created_at TEXT NOT NULL,
helpful INTEGER NOT NULL DEFAULT 0,
not_helpful INTEGER NOT NULL DEFAULT 0,
synthetic INTEGER NOT NULL DEFAULT 1
);
CREATE TABLE IF NOT EXISTS carts (
cart_id TEXT PRIMARY KEY,
owner_key TEXT NOT NULL UNIQUE,
created_at TEXT NOT NULL
);
CREATE TABLE IF NOT EXISTS cart_items (
item_id INTEGER PRIMARY KEY AUTOINCREMENT,
cart_id TEXT NOT NULL,
product_id TEXT NOT NULL,
color TEXT,
size TEXT,
qty INTEGER NOT NULL DEFAULT 1,
unit_price REAL NOT NULL,
saved INTEGER NOT NULL DEFAULT 0,
added_at TEXT NOT NULL
);
CREATE TABLE IF NOT EXISTS addresses (
address_id INTEGER PRIMARY KEY AUTOINCREMENT,
owner TEXT NOT NULL,
label TEXT,
first_name TEXT NOT NULL,
last_name TEXT NOT NULL,
street1 TEXT NOT NULL,
street2 TEXT,
city TEXT NOT NULL,
state TEXT NOT NULL,
postal TEXT NOT NULL,
country TEXT NOT NULL DEFAULT 'United States',
phone TEXT,
is_default INTEGER NOT NULL DEFAULT 0
);
CREATE TABLE IF NOT EXISTS orders (
order_id TEXT PRIMARY KEY,
owner TEXT NOT NULL,
order_number TEXT NOT NULL UNIQUE,
last_name TEXT NOT NULL,
postal TEXT NOT NULL,
placed_at TEXT NOT NULL,
status TEXT NOT NULL,
subtotal REAL NOT NULL,
shipping REAL NOT NULL DEFAULT 0,
tax REAL NOT NULL DEFAULT 0,
total REAL NOT NULL,
payment_ref TEXT
);
CREATE TABLE IF NOT EXISTS order_items (
order_item_id INTEGER PRIMARY KEY AUTOINCREMENT,
order_id TEXT NOT NULL,
product_id TEXT NOT NULL,
name TEXT NOT NULL,
color TEXT,
size TEXT,
qty INTEGER NOT NULL,
unit_price REAL NOT NULL
);
CREATE TABLE IF NOT EXISTS stores (
store_id INTEGER PRIMARY KEY,
name TEXT NOT NULL,
street TEXT NOT NULL,
city TEXT NOT NULL,
state TEXT NOT NULL,
postal TEXT NOT NULL,
phone TEXT NOT NULL,
hours TEXT NOT NULL
);
CREATE TABLE IF NOT EXISTS wishlist_items (
wish_id INTEGER PRIMARY KEY AUTOINCREMENT,
owner TEXT NOT NULL,
product_id TEXT NOT NULL,
added_at TEXT NOT NULL,
UNIQUE (owner, product_id)
);
CREATE TABLE IF NOT EXISTS gift_cards (
code TEXT PRIMARY KEY,
pin TEXT NOT NULL,
balance REAL NOT NULL
);
CREATE TABLE IF NOT EXISTS promotions (
code TEXT PRIMARY KEY,
kind TEXT NOT NULL,
amount REAL NOT NULL,
label TEXT NOT NULL
);
CREATE TABLE IF NOT EXISTS cart_promotions (
cart_id TEXT NOT NULL,
code TEXT NOT NULL,
PRIMARY KEY (cart_id, code)
);
CREATE TABLE IF NOT EXISTS catalog_requests (
request_id INTEGER PRIMARY KEY AUTOINCREMENT,
first_name TEXT NOT NULL,
last_name TEXT NOT NULL,
email TEXT NOT NULL,
street1 TEXT NOT NULL,
city TEXT NOT NULL,
state TEXT NOT NULL,
postal TEXT NOT NULL,
created_at TEXT NOT NULL
);
CREATE TABLE IF NOT EXISTS email_prefs (
owner TEXT PRIMARY KEY,
subscribed INTEGER NOT NULL DEFAULT 1,
frequency TEXT NOT NULL DEFAULT 'weekly',
catalog_opt INTEGER NOT NULL DEFAULT 1
);
CREATE TABLE IF NOT EXISTS nav_menu (
row_id INTEGER PRIMARY KEY AUTOINCREMENT,
top_label TEXT NOT NULL,
kind TEXT NOT NULL,
position INTEGER NOT NULL,
depth INTEGER NOT NULL,
label TEXT NOT NULL,
cat_id INTEGER,
slug TEXT,
is_group INTEGER NOT NULL DEFAULT 0,
group_label TEXT
);
CREATE TABLE IF NOT EXISTS category_facets (
cat_id INTEGER NOT NULL,
position INTEGER NOT NULL,
facet TEXT NOT NULL,
PRIMARY KEY (cat_id, facet)
);
CREATE TABLE IF NOT EXISTS lander_sections (
section_id INTEGER PRIMARY KEY AUTOINCREMENT,
cat_id INTEGER NOT NULL,
position INTEGER NOT NULL,
heading TEXT,
prose TEXT,
view_all_cat_id INTEGER,
view_all_slug TEXT
);
CREATE TABLE IF NOT EXISTS lander_items (
item_id INTEGER PRIMARY KEY AUTOINCREMENT,
section_id INTEGER NOT NULL,
position INTEGER NOT NULL,
label TEXT NOT NULL,
cat_id INTEGER,
slug TEXT,
blurb TEXT,
asset TEXT,
alt TEXT,
external INTEGER NOT NULL DEFAULT 0
);
CREATE TABLE IF NOT EXISTS home_sections (
section_id INTEGER PRIMARY KEY AUTOINCREMENT,
key TEXT NOT NULL UNIQUE,
kind TEXT NOT NULL,
position INTEGER NOT NULL,
heading TEXT,
sub TEXT,
cta_label TEXT,
cta_cat_id INTEGER,
cta_slug TEXT
);
CREATE TABLE IF NOT EXISTS home_items (
item_id INTEGER PRIMARY KEY AUTOINCREMENT,
section_id INTEGER NOT NULL,
position INTEGER NOT NULL,
label TEXT NOT NULL,
cat_id INTEGER,
slug TEXT,
blurb TEXT,
asset TEXT,
alt TEXT
);
CREATE TABLE IF NOT EXISTS recently_viewed (
owner TEXT NOT NULL,
product_id TEXT NOT NULL,
viewed_at TEXT NOT NULL,
PRIMARY KEY (owner, product_id)
);
CREATE TABLE IF NOT EXISTS content_pages (
cat_id INTEGER PRIMARY KEY,
name TEXT NOT NULL,
blurb TEXT NOT NULL
);
CREATE INDEX IF NOT EXISTS idx_pc_cat ON product_categories(cat_id);
CREATE INDEX IF NOT EXISTS idx_ci_cart ON cart_items(cart_id);
CREATE INDEX IF NOT EXISTS idx_rev_product ON reviews(product_id);
CREATE INDEX IF NOT EXISTS idx_oi_order ON order_items(order_id);
"""
def migrate(connection: sqlite3.Connection) -> None:
"""Create the business schema. Safe to run repeatedly.
Statements run one at a time on purpose: ``executescript`` commits the
caller's open transaction, which breaks the backend lifecycle contract.
"""
for statement in SCHEMA.split(";"):
if statement.strip():
connection.execute(statement)
def _load(name: str) -> Any:
return json.loads((SEED_DIR / name).read_text(encoding="utf-8"))
def _color_bucket(name: str) -> str | None:
lowered = name.lower()
for bucket, needles in COLOR_BUCKETS.items():
if any(needle in lowered for needle in needles):
return bucket
return None
GENDER_CRUMBS = {
"Women's": "Women's",
"Men's": "Men's",
"Kids'": "Kids'",
"Baby": "Kids'",
"Toddler": "Kids'",
"Girls'": "Kids'",
"Boys'": "Kids'",
}
def _gender_for(breadcrumb: list[str], name: str) -> str | None:
"""Gender comes from the breadcrumb the source renders on the product page."""
for crumb in breadcrumb:
for needle, label in GENDER_CRUMBS.items():
if needle.lower() in crumb.lower():
return label
for needle, label in GENDER_CRUMBS.items():
if name.lower().startswith(needle.lower()):
return label
return None
def _brand_for(name: str) -> str:
for brand in KNOWN_BRANDS:
if brand == "L.L.Bean":
continue
if brand.lower() in name.lower():
return brand
return "L.L.Bean"
def _stable_int(*parts: str) -> int:
digest = hashlib.sha256("|".join(parts).encode("utf-8")).hexdigest()
return int(digest[:8], 16)
REVIEW_TEMPLATES = (
(5, "Exactly what I wanted", "Held up through a full season of use and still looks new. Sizing was true to the chart."),
(5, "Buy it once", "Well made and thoughtfully designed. The details are where this one earns its price."),
(4, "Very good, one small note", "Quality is excellent. I would prefer one more pocket, but that is a minor thing."),
(4, "Solid everyday pick", "Comfortable and durable. Colour matches the product photos closely."),
(3, "Good but runs large", "The material is nice. I sized down and it fit much better."),
(2, "Not for me", "The fit was not right for my build and the fabric was heavier than I expected."),
(1, "Disappointed", "Arrived with a loose seam. Returns were straightforward but I expected better."),
)
AUTHORS = (
("Casco Bay Hiker", "Portland, ME"),
("Trailhead Sam", "Burlington, VT"),
("Northwoods Reader", "Duluth, MN"),
("Coastal Walker", "Camden, ME"),
("Weekend Paddler", "Ithaca, NY"),
("Frost Hollow", "Berlin, NH"),
("Granite Stater", "Concord, NH"),
)
SEED_STORES = (
(1, "Freeport Flagship Store", "95 Main Street", "Freeport", "ME", "04033", "(877) 755-2326", "Open 24 hours"),
(2, "Portland Store", "375 Riverside Street", "Portland", "ME", "04103", "(207) 470-1200", "9:00 AM - 8:00 PM"),
(3, "South Portland Store", "200 Running Hill Road", "South Portland", "ME", "04106", "(207) 253-9500", "9:00 AM - 9:00 PM"),
(4, "Burlington Store", "49 Church Street", "Burlington", "VT", "05401", "(802) 448-3800", "10:00 AM - 7:00 PM"),
(5, "Nashua Store", "310 Daniel Webster Highway", "Nashua", "NH", "03060", "(603) 546-5100", "10:00 AM - 8:00 PM"),
(6, "Marlborough Store", "601 Donald Lynch Boulevard", "Marlborough", "MA", "01752", "(508) 251-3000", "10:00 AM - 8:00 PM"),
(7, "Yonkers Store", "2500 Central Park Avenue", "Yonkers", "NY", "10710", "(914) 573-2000", "10:00 AM - 8:00 PM"),
(8, "King of Prussia Store", "160 North Gulph Road", "King of Prussia", "PA", "19406", "(610) 337-4400", "10:00 AM - 8:00 PM"),
(9, "Columbia Store", "6151 Little River Turnpike", "Alexandria", "VA", "22312", "(703) 941-3400", "10:00 AM - 8:00 PM"),
(10, "Glenview Store", "1931 Tower Drive", "Glenview", "IL", "60026", "(847) 400-2100", "10:00 AM - 8:00 PM"),
)
SEED_PROMOTIONS = (
("BEAN20", "percent", 20.0, "20% off your order"),
("SHIPFREE", "shipping", 0.0, "Free standard shipping"),
("TRAIL10", "amount", 10.0, "$10 off your order"),
)
SEED_GIFT_CARDS = (
("6006000000000001", "1234", 75.00),
("6006000000000002", "5678", 0.00),
)
def seed(connection: sqlite3.Connection) -> None:
"""Seed deterministic catalog data. Idempotent."""
migrate(connection)
if connection.execute("SELECT COUNT(*) FROM products").fetchone()[0]:
return
categories = _load("categories.json")
tiles = _load("category_tiles.json")
connection.executemany(
"INSERT OR REPLACE INTO categories"
" (cat_id, name, slug, parent_id, depth, nav_order, kind, tile_image, tile_alt)"
" VALUES (?,?,?,?,?,?,?,?,?)",
[
(
c["cat_id"],
c["name"],
c.get("slug"),
c.get("parent_id"),
c.get("depth", 0),
c.get("nav_order", 0),
"category",
(
f"/static/img/category/{c['cat_id']}.jpg"
if str(c["cat_id"]) in tiles
else None
),
(tiles.get(str(c["cat_id"]), {}) or {}).get("alt"),
)
for c in categories
],
)
products = _load("products.json")
known_categories = {c["cat_id"] for c in categories}
outdoor_equipment = 29
for product in products:
pid = str(product["product_id"])
name = product["name"]
low = float(product["price_low"])
high = float(product["price_high"])
on_sale = 1 if product.get("on_sale") else 0
seed_int = _stable_int(pid, name)
low_inventory = 1 if seed_int % 7 == 0 else 0
is_new = 1 if seed_int % 5 == 0 else 0
connection.execute(
"INSERT OR REPLACE INTO products (product_id, slug, name, item_number, brand,"
" description, material, price_low, price_high, list_price, sale_price, on_sale,"
" is_new, rating, review_count, availability, low_inventory, color_count,"
" gender, percent_off, grid_image, grid_image_alt, position, breadcrumb)"
" VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)",
(
pid,
product.get("slug"),
name,
product.get("item_number"),
_brand_for(name),
product.get("description"),
product.get("material"),
low,
high,
float(product.get("list_price") or high),
product.get("sale_price"),
on_sale,
is_new,
product.get("rating"),
int(product.get("review_count") or 0),
product.get("availability") or "InStock",
low_inventory,
int(product.get("color_count") or 0),
_gender_for(product.get("breadcrumb") or [], name),
(
round((1 - low / high) * 100)
if on_sale and high
else 0
),
f"/static/img/product/{pid}_grid.webp",
product.get("grid_image_alt") or name,
int(product.get("position") or 0),
json.dumps(product.get("breadcrumb") or []),
),
)
# Category membership comes from the crawl: every category page whose grid
# listed this product. Falls back to the deepest known breadcrumb name.
assigned = [c for c in (product.get("categories") or []) if c in known_categories]
if not assigned:
for crumb in reversed(product.get("breadcrumb") or []):
match = connection.execute(
"SELECT cat_id FROM categories WHERE name = ? ORDER BY depth DESC LIMIT 1",
(crumb,),
).fetchone()
if match and match[0] in known_categories:
assigned = [match[0]]
break
for cat_id in assigned or [outdoor_equipment]:
connection.execute(
"INSERT OR IGNORE INTO product_categories (product_id, cat_id) VALUES (?,?)",
(pid, cat_id),
)
detail_limit = 5 if product.get("observed_in_grid") else 2
for idx, image in enumerate(product.get("images") or []):
if idx >= detail_limit:
break
connection.execute(
"INSERT OR REPLACE INTO product_images (product_id, idx, asset, caption)"
" VALUES (?,?,?,?)",
(pid, idx, f"/static/img/product/{pid}_d{idx}.webp", image.get("caption")),
)
swatches = product.get("swatches") or []
colors = product.get("colors") or []
for idx, color in enumerate(colors):
swatch_asset = None
if idx < len(swatches):
swatch_asset = f"/static/img/swatch/{pid}_s{idx}.webp"
connection.execute(
"INSERT OR REPLACE INTO product_colors (product_id, idx, name, bucket, swatch, price)"
" VALUES (?,?,?,?,?,?)",
(
pid,
idx,
color,
_color_bucket(color),
swatch_asset,
low if (on_sale and idx == 0) else high,
),
)
for idx, size in enumerate(product.get("sizes") or []):
connection.execute(
"INSERT OR REPLACE INTO product_sizes (product_id, idx, name, in_stock)"
" VALUES (?,?,?,?)",
(pid, idx, size, 0 if (seed_int + idx) % 11 == 0 else 1),
)
# Synthetic review bodies distributed to match the observed rating.
target = float(product.get("rating") or 4.5)
count = min(int(product.get("review_count") or 0), 12)
for n in range(count):
template = REVIEW_TEMPLATES[(seed_int + n) % len(REVIEW_TEMPLATES)]
if n < max(1, int(count * 0.7)):
template = REVIEW_TEMPLATES[(seed_int + n) % 2]
author, location = AUTHORS[(seed_int + n) % len(AUTHORS)]
day = 1 + ((seed_int + n * 7) % 28)
month = 1 + ((seed_int + n * 3) % 12)
connection.execute(
"INSERT INTO reviews (product_id, rating, title, body, author, location,"
" created_at, helpful, not_helpful, synthetic) VALUES (?,?,?,?,?,?,?,?,?,1)",
(
pid,
template[0],
template[1],
template[2],
author,
location,
f"2026-{month:02d}-{day:02d}",
(seed_int + n) % 40,
(seed_int + n) % 5,
),
)
del target
connection.executemany(
"INSERT INTO nav_menu (top_label, kind, position, depth, label, cat_id, slug,"
" is_group, group_label) VALUES (?,?,?,?,?,?,?,?,?)",
[
(
m["top"], m["kind"], m["position"], m["depth"], m["label"],
m.get("cat_id"), m.get("slug"), m.get("is_group", 0), m.get("group"),
)
for m in _load("nav_menu.json")
],
)
facet_cfg = _load("category_facets.json")
connection.executemany(
"INSERT OR REPLACE INTO category_facets (cat_id, position, facet) VALUES (?,?,?)",
[
(int(cat_id), position, facet)
for cat_id, entry in facet_cfg.items()
for position, facet in enumerate(entry["facets"])
],
)
home = _load("home.json")
for position, section in enumerate(home["sections"]):
cursor = connection.execute(
"INSERT OR REPLACE INTO home_sections (key, kind, position, heading, sub,"
" cta_label, cta_cat_id, cta_slug) VALUES (?,?,?,?,?,?,?,?)",
(
section["key"], section["kind"], section.get("position", position),
section.get("heading"), section.get("sub"),
section.get("cta_label"), section.get("cta_cat_id"), section.get("cta_slug"),
),
)
connection.executemany(
"INSERT INTO home_items (section_id, position, label, cat_id, slug, blurb,"
" asset, alt) VALUES (?,?,?,?,?,?,?,?)",
[
(
cursor.lastrowid, i, it["label"], it.get("cat_id"), it.get("slug"),
it.get("blurb"), it.get("asset"), it.get("alt"),
)
for i, it in enumerate(section["items"])
],
)
for cat_id, lander in _load("landers.json").items():
for position, section in enumerate(lander["sections"]):
view_all = section.get("view_all") or {}
cursor = connection.execute(
"INSERT INTO lander_sections (cat_id, position, heading, prose,"
" view_all_cat_id, view_all_slug) VALUES (?,?,?,?,?,?)",
(
int(cat_id), position, section.get("heading"), section.get("prose"),
view_all.get("cat_id"), view_all.get("slug"),
),
)
section_id = cursor.lastrowid
connection.executemany(
"INSERT INTO lander_items (section_id, position, label, cat_id, slug,"
" blurb, asset, alt, external) VALUES (?,?,?,?,?,?,?,?,?)",
[
(
section_id, i, it["label"], it.get("cat_id"), it.get("slug"),
it.get("blurb"), it.get("asset"), it.get("alt"),
1 if it.get("external") else 0,
)
for i, it in enumerate(section["items"])
],
)
connection.executemany(
"INSERT OR REPLACE INTO content_pages (cat_id, name, blurb) VALUES (?,?,?)",
[(c["cat_id"], c["name"], c["blurb"]) for c in _load("content_pages.json")],
)
connection.executemany(
"INSERT OR REPLACE INTO stores (store_id, name, street, city, state, postal, phone, hours)"
" VALUES (?,?,?,?,?,?,?,?)",
SEED_STORES,
)
connection.executemany(
"INSERT OR REPLACE INTO promotions (code, kind, amount, label) VALUES (?,?,?,?)",
SEED_PROMOTIONS,
)
connection.executemany(
"INSERT OR REPLACE INTO gift_cards (code, pin, balance) VALUES (?,?,?)",
SEED_GIFT_CARDS,
)