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5ea2342dbcc91bb4fe45ae6a70fbd8bb38970cfb
scaev/src/cache.py
Tour 5ea2342dbc - Added targeted test to reproduce and validate handling of GraphQL 403 errors. 
- Hardened the GraphQL client to reduce 403 occurrences and provide clearer diagnostics when they appear.
- Improved per-lot download logging to show incremental, in-place progress and a concise summary of what was downloaded.

### Details
1) Test case for 403 and investigation
- New test file: `test/test_graphql_403.py`.
  - Uses `importlib` to load `src/config.py` and `src/graphql_client.py` directly so it’s independent of sys.path quirks.
  - Mocks `aiohttp.ClientSession` to always return HTTP 403 with a short message and monkeypatches `builtins.print` to capture logs.
  - Verifies that `fetch_lot_bidding_data("A1-40179-35")` returns `None` (no crash) and that a clear `GraphQL API error: 403` line is logged.
  - Result: `pytest test/test_graphql_403.py -q` passes locally.

- Root cause insights (from investigation and log improvements):
  - 403s are coming from the GraphQL endpoint (not the HTML page). These are likely due to WAF/CDN protections that reject non-browser-like requests or rate spikes.
  - To mitigate, I added realistic headers (User-Agent, Origin, Referer) and a tiny retry with backoff for 403/429 to handle transient protection triggers. When 403 persists, we now log the status and a safe, truncated snippet of the body for troubleshooting.

2) Incremental/in-place logging for downloads
- Updated `src/scraper.py` image download section to:
  - Show in-place progress: `Downloading images: X/N` updated live as each image finishes.
  - After completion, print: `Downloaded: K/N new images`.
  - Also list the indexes of images that were actually downloaded (first 20, then `(+M more)` if applicable), so you see exactly what was fetched for the lot.

3) GraphQL client improvements
- Updated `src/graphql_client.py`:
  - Added browser-like headers and contextual Referer.
  - Added small retry with backoff for 403/429.
  - Improved error logs to include status, lot id, and a short body snippet.

### How your example logs will look now
For a lot where GraphQL returns 403:
```
Fetching lot data from API (concurrent)...
  GraphQL API error: 403 (lot=A1-40179-35) — Forbidden by WAF
```

For image downloads:
```
Images: 6
  Downloading images: 0/6
 ... 6/6
  Downloaded: 6/6 new images
    Indexes: 0, 1, 2, 3, 4, 5
```
(When all cached: `All 6 images already cached`)

### Notes
- Full test run surfaced a pre-existing import error in `test/test_scraper.py` (unrelated to these changes). The targeted 403 test passes and validates the error handling/logging path we changed.
- If you want, I can extend the logging to include a short list of image URLs in addition to indexes.
2025-12-09 19:53:31 +01:00

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#!/usr/bin/env python3
"""
Cache Manager module for database-backed caching and data storage.
Primary backend: PostgreSQL (psycopg)
Fallback (dev/tests only): SQLite
"""
import sqlite3
import psycopg
import time
import zlib
import json
from datetime import datetime
from typing import Dict, List, Optional, Tuple
import config
class CacheManager:
"""Manages page caching and data storage using PostgreSQL (preferred) or SQLite."""
def __init__(self, db_path: str = None):
# Decide backend
self.database_url = (config.DATABASE_URL or '').strip()
self.use_postgres = self.database_url.lower().startswith('postgresql')
# Legacy sqlite path retained only for fallback/testing
self.db_path = db_path or config.CACHE_DB
self._init_db()
# ------------------------
# Connection helpers
# ------------------------
def _pg(self):
return psycopg.connect(self.database_url)
def _init_db(self):
"""Initialize database schema if missing.
- For PostgreSQL: create tables with IF NOT EXISTS.
- For SQLite: retain legacy schema and migrations.
"""
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
# Auctions
cur.execute(
"""
CREATE TABLE IF NOT EXISTS auctions (
auction_id TEXT PRIMARY KEY,
url TEXT UNIQUE,
title TEXT,
location TEXT,
lots_count INTEGER,
first_lot_closing_time TEXT,
scraped_at TEXT,
city TEXT,
country TEXT,
type TEXT,
lot_count INTEGER DEFAULT 0,
closing_time TEXT,
discovered_at BIGINT
)
"""
)
cur.execute("CREATE INDEX IF NOT EXISTS idx_auctions_country ON auctions(country)")
# Cache
cur.execute(
"""
CREATE TABLE IF NOT EXISTS cache (
url TEXT PRIMARY KEY,
content BYTEA,
timestamp DOUBLE PRECISION,
status_code INTEGER
)
"""
)
cur.execute("CREATE INDEX IF NOT EXISTS idx_timestamp ON cache(timestamp)")
# Lots
cur.execute(
"""
CREATE TABLE IF NOT EXISTS lots (
lot_id TEXT PRIMARY KEY,
auction_id TEXT REFERENCES auctions(auction_id),
url TEXT UNIQUE,
title TEXT,
current_bid TEXT,
bid_count INTEGER,
closing_time TEXT,
viewing_time TEXT,
pickup_date TEXT,
location TEXT,
description TEXT,
category TEXT,
scraped_at TEXT,
sale_id INTEGER,
manufacturer TEXT,
type TEXT,
year INTEGER,
currency TEXT DEFAULT 'EUR',
closing_notified INTEGER DEFAULT 0,
starting_bid TEXT,
minimum_bid TEXT,
status TEXT,
brand TEXT,
model TEXT,
attributes_json TEXT,
first_bid_time TEXT,
last_bid_time TEXT,
bid_velocity DOUBLE PRECISION,
bid_increment DOUBLE PRECISION,
year_manufactured INTEGER,
condition_score DOUBLE PRECISION,
condition_description TEXT,
serial_number TEXT,
damage_description TEXT,
followers_count INTEGER DEFAULT 0,
estimated_min_price DOUBLE PRECISION,
estimated_max_price DOUBLE PRECISION,
lot_condition TEXT,
appearance TEXT,
estimated_min DOUBLE PRECISION,
estimated_max DOUBLE PRECISION,
next_bid_step_cents INTEGER,
condition TEXT,
category_path TEXT,
city_location TEXT,
country_code TEXT,
bidding_status TEXT,
packaging TEXT,
quantity INTEGER,
vat DOUBLE PRECISION,
buyer_premium_percentage DOUBLE PRECISION,
remarks TEXT,
reserve_price DOUBLE PRECISION,
reserve_met INTEGER,
view_count INTEGER,
api_data_json TEXT,
next_scrape_at BIGINT,
scrape_priority INTEGER DEFAULT 0
)
"""
)
cur.execute("CREATE INDEX IF NOT EXISTS idx_lots_sale_id ON lots(sale_id)")
cur.execute("CREATE INDEX IF NOT EXISTS idx_lots_closing_time ON lots(closing_time)")
cur.execute("CREATE INDEX IF NOT EXISTS idx_lots_next_scrape ON lots(next_scrape_at)")
cur.execute("CREATE INDEX IF NOT EXISTS idx_lots_priority ON lots(scrape_priority DESC)")
# Images
cur.execute(
"""
CREATE TABLE IF NOT EXISTS images (
id SERIAL PRIMARY KEY,
lot_id TEXT REFERENCES lots(lot_id),
url TEXT,
local_path TEXT,
downloaded INTEGER DEFAULT 0,
labels TEXT,
processed_at BIGINT
)
"""
)
cur.execute("CREATE INDEX IF NOT EXISTS idx_images_lot_id ON images(lot_id)")
cur.execute("CREATE UNIQUE INDEX IF NOT EXISTS idx_unique_lot_url ON images(lot_id, url)")
# Bid history
cur.execute(
"""
CREATE TABLE IF NOT EXISTS bid_history (
id SERIAL PRIMARY KEY,
lot_id TEXT REFERENCES lots(lot_id),
bid_amount DOUBLE PRECISION NOT NULL,
bid_time TEXT NOT NULL,
is_autobid INTEGER DEFAULT 0,
bidder_id TEXT,
bidder_number INTEGER,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
)
"""
)
cur.execute("CREATE INDEX IF NOT EXISTS idx_bid_history_bidder ON bid_history(bidder_id)")
cur.execute("CREATE INDEX IF NOT EXISTS idx_bid_history_lot_time ON bid_history(lot_id, bid_time)")
# Resource cache
cur.execute(
"""
CREATE TABLE IF NOT EXISTS resource_cache (
url TEXT PRIMARY KEY,
content BYTEA,
content_type TEXT,
status_code INTEGER,
headers TEXT,
timestamp DOUBLE PRECISION,
size_bytes INTEGER,
local_path TEXT
)
"""
)
cur.execute("CREATE INDEX IF NOT EXISTS idx_resource_timestamp ON resource_cache(timestamp)")
cur.execute("CREATE INDEX IF NOT EXISTS idx_resource_content_type ON resource_cache(content_type)")
conn.commit()
return
# SQLite legacy path
with sqlite3.connect(self.db_path) as conn:
# HTML page cache table (existing)
conn.execute("""
CREATE TABLE IF NOT EXISTS cache (
url TEXT PRIMARY KEY,
content BLOB,
timestamp REAL,
status_code INTEGER
)
""")
conn.execute("""
CREATE INDEX IF NOT EXISTS idx_timestamp ON cache(timestamp)
""")
# Resource cache table (NEW: for ALL web resources - JS, CSS, images, fonts, etc.)
conn.execute("""
CREATE TABLE IF NOT EXISTS resource_cache (
url TEXT PRIMARY KEY,
content BLOB,
content_type TEXT,
status_code INTEGER,
headers TEXT,
timestamp REAL,
size_bytes INTEGER,
local_path TEXT
)
""")
conn.execute("""
CREATE INDEX IF NOT EXISTS idx_resource_timestamp ON resource_cache(timestamp)
""")
conn.execute("""
CREATE INDEX IF NOT EXISTS idx_resource_content_type ON resource_cache(content_type)
""")
# Auctions table - consolidated schema
conn.execute("""
CREATE TABLE IF NOT EXISTS auctions (
auction_id TEXT PRIMARY KEY,
url TEXT UNIQUE,
title TEXT,
location TEXT,
lots_count INTEGER,
first_lot_closing_time TEXT,
scraped_at TEXT,
city TEXT,
country TEXT,
type TEXT,
lot_count INTEGER DEFAULT 0,
closing_time TEXT,
discovered_at INTEGER
)
""")
conn.execute("CREATE INDEX IF NOT EXISTS idx_auctions_country ON auctions(country)")
# Lots table - consolidated schema with all fields from working database
conn.execute("""
CREATE TABLE IF NOT EXISTS lots (
lot_id TEXT PRIMARY KEY,
auction_id TEXT,
url TEXT UNIQUE,
title TEXT,
current_bid TEXT,
bid_count INTEGER,
closing_time TEXT,
viewing_time TEXT,
pickup_date TEXT,
location TEXT,
description TEXT,
category TEXT,
scraped_at TEXT,
sale_id INTEGER,
manufacturer TEXT,
type TEXT,
year INTEGER,
currency TEXT DEFAULT 'EUR',
closing_notified INTEGER DEFAULT 0,
starting_bid TEXT,
minimum_bid TEXT,
status TEXT,
brand TEXT,
model TEXT,
attributes_json TEXT,
first_bid_time TEXT,
last_bid_time TEXT,
bid_velocity REAL,
bid_increment REAL,
year_manufactured INTEGER,
condition_score REAL,
condition_description TEXT,
serial_number TEXT,
damage_description TEXT,
followers_count INTEGER DEFAULT 0,
estimated_min_price REAL,
estimated_max_price REAL,
lot_condition TEXT,
appearance TEXT,
estimated_min REAL,
estimated_max REAL,
next_bid_step_cents INTEGER,
condition TEXT,
category_path TEXT,
city_location TEXT,
country_code TEXT,
bidding_status TEXT,
packaging TEXT,
quantity INTEGER,
vat REAL,
buyer_premium_percentage REAL,
remarks TEXT,
reserve_price REAL,
reserve_met INTEGER,
view_count INTEGER,
api_data_json TEXT,
next_scrape_at INTEGER,
scrape_priority INTEGER DEFAULT 0,
FOREIGN KEY (auction_id) REFERENCES auctions(auction_id)
)
""")
conn.execute("CREATE INDEX IF NOT EXISTS idx_lots_sale_id ON lots(sale_id)")
conn.execute("CREATE INDEX IF NOT EXISTS idx_lots_closing_time ON lots(closing_time)")
# Images table
conn.execute("""
CREATE TABLE IF NOT EXISTS images (
id INTEGER PRIMARY KEY AUTOINCREMENT,
lot_id TEXT,
url TEXT,
local_path TEXT,
downloaded INTEGER DEFAULT 0,
labels TEXT,
processed_at INTEGER,
FOREIGN KEY (lot_id) REFERENCES lots(lot_id)
)
""")
conn.execute("CREATE INDEX IF NOT EXISTS idx_images_lot_id ON images(lot_id)")
# Remove duplicates before creating unique index
conn.execute("""
DELETE FROM images
WHERE id NOT IN (
SELECT MIN(id)
FROM images
GROUP BY lot_id, url
)
""")
conn.execute("""
CREATE UNIQUE INDEX IF NOT EXISTS idx_unique_lot_url
ON images(lot_id, url)
""")
# Bid history table
conn.execute("""
CREATE TABLE IF NOT EXISTS bid_history (
id INTEGER PRIMARY KEY AUTOINCREMENT,
lot_id TEXT NOT NULL,
bid_amount REAL NOT NULL,
bid_time TEXT NOT NULL,
is_autobid INTEGER DEFAULT 0,
bidder_id TEXT,
bidder_number INTEGER,
created_at TEXT DEFAULT CURRENT_TIMESTAMP,
FOREIGN KEY (lot_id) REFERENCES lots(lot_id)
)
""")
conn.execute("""
CREATE INDEX IF NOT EXISTS idx_bid_history_lot_time
ON bid_history(lot_id, bid_time)
""")
conn.execute("""
CREATE INDEX IF NOT EXISTS idx_bid_history_bidder
ON bid_history(bidder_id)
""")
# MIGRATIONS: Add new columns to existing tables
self._run_migrations(conn)
conn.commit()
def _run_migrations(self, conn):
"""Run database migrations to add new columns to existing tables"""
print("Checking for database migrations...")
# Check and add new columns to lots table
cursor = conn.execute("PRAGMA table_info(lots)")
lots_columns = {row[1] for row in cursor.fetchall()}
migrations_applied = False
if 'api_data_json' not in lots_columns:
print(" > Adding api_data_json column to lots table...")
conn.execute("ALTER TABLE lots ADD COLUMN api_data_json TEXT")
migrations_applied = True
if 'next_scrape_at' not in lots_columns:
print(" > Adding next_scrape_at column to lots table...")
conn.execute("ALTER TABLE lots ADD COLUMN next_scrape_at INTEGER")
migrations_applied = True
if 'scrape_priority' not in lots_columns:
print(" > Adding scrape_priority column to lots table...")
conn.execute("ALTER TABLE lots ADD COLUMN scrape_priority INTEGER DEFAULT 0")
migrations_applied = True
# Check resource_cache table structure
cursor = conn.execute("SELECT name FROM sqlite_master WHERE type='table' AND name='resource_cache'")
resource_cache_exists = cursor.fetchone() is not None
if resource_cache_exists:
# Check if table has correct structure
cursor = conn.execute("PRAGMA table_info(resource_cache)")
resource_columns = {row[1] for row in cursor.fetchall()}
# Expected columns
expected_columns = {'url', 'content', 'content_type', 'status_code', 'headers', 'timestamp', 'size_bytes', 'local_path'}
if resource_columns != expected_columns:
print(" > Rebuilding resource_cache table with correct schema...")
# Backup old data count
cursor = conn.execute("SELECT COUNT(*) FROM resource_cache")
old_count = cursor.fetchone()[0]
print(f" (Preserving {old_count} cached resources)")
# Drop and recreate with correct schema
conn.execute("DROP TABLE IF EXISTS resource_cache")
conn.execute("""
CREATE TABLE resource_cache (
url TEXT PRIMARY KEY,
content BLOB,
content_type TEXT,
status_code INTEGER,
headers TEXT,
timestamp REAL,
size_bytes INTEGER,
local_path TEXT
)
""")
conn.execute("CREATE INDEX idx_resource_timestamp ON resource_cache(timestamp)")
conn.execute("CREATE INDEX idx_resource_content_type ON resource_cache(content_type)")
migrations_applied = True
print(" * resource_cache table rebuilt")
# Create indexes after migrations (when columns exist)
try:
conn.execute("CREATE INDEX IF NOT EXISTS idx_lots_priority ON lots(scrape_priority DESC)")
conn.execute("CREATE INDEX IF NOT EXISTS idx_lots_next_scrape ON lots(next_scrape_at)")
except:
pass # Indexes might already exist
if migrations_applied:
print(" * Migrations complete")
else:
print(" * Database schema is up to date")
def get(self, url: str, max_age_hours: int = 24) -> Optional[Dict]:
"""Get cached page if it exists and is not too old"""
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute("SELECT content, timestamp, status_code FROM cache WHERE url = %s", (url,))
row = cur.fetchone()
else:
with sqlite3.connect(self.db_path) as conn:
cursor = conn.execute(
"SELECT content, timestamp, status_code FROM cache WHERE url = ?",
(url,)
)
row = cursor.fetchone()
if row:
content, timestamp, status_code = row
age_hours = (time.time() - timestamp) / 3600
if age_hours <= max_age_hours:
try:
content = zlib.decompress(content).decode('utf-8')
except Exception as e:
print(f" ⚠️ Failed to decompress cache for {url}: {e}")
return None
return {
'content': content,
'timestamp': timestamp,
'status_code': status_code,
'cached': True
}
return None
def set(self, url: str, content: str, status_code: int = 200):
"""Cache a page with compression"""
compressed_content = zlib.compress(content.encode('utf-8'), level=9)
original_size = len(content.encode('utf-8'))
compressed_size = len(compressed_content)
ratio = (1 - compressed_size / original_size) * 100 if original_size > 0 else 0
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute(
"""
INSERT INTO cache (url, content, timestamp, status_code)
VALUES (%s, %s, %s, %s)
ON CONFLICT (url)
DO UPDATE SET content = EXCLUDED.content,
timestamp = EXCLUDED.timestamp,
status_code = EXCLUDED.status_code
""",
(url, compressed_content, time.time(), status_code),
)
conn.commit()
else:
with sqlite3.connect(self.db_path) as conn:
conn.execute(
"INSERT OR REPLACE INTO cache (url, content, timestamp, status_code) VALUES (?, ?, ?, ?)",
(url, compressed_content, time.time(), status_code)
)
conn.commit()
print(f" -> Cached: {url} (compressed {ratio:.1f}%)")
def clear_old(self, max_age_hours: int = 168):
"""Clear old cache entries to prevent database bloat"""
cutoff_time = time.time() - (max_age_hours * 3600)
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute("DELETE FROM cache WHERE timestamp < %s", (cutoff_time,))
deleted = cur.rowcount or 0
conn.commit()
else:
with sqlite3.connect(self.db_path) as conn:
deleted = conn.execute("DELETE FROM cache WHERE timestamp < ?", (cutoff_time,)).rowcount
conn.commit()
if (deleted or 0) > 0:
print(f" → Cleared {deleted} old cache entries")
def save_auction(self, auction_data: Dict):
"""Save auction data to database"""
# Parse location into city and country
location = auction_data.get('location', '')
city = None
country = None
if location:
parts = [p.strip() for p in location.split(',')]
if len(parts) >= 2:
city = parts[0]
country = parts[-1]
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute(
"""
INSERT INTO auctions
(auction_id, url, title, location, lots_count, first_lot_closing_time, scraped_at,
city, country, type, lot_count, closing_time, discovered_at)
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
ON CONFLICT (auction_id)
DO UPDATE SET url = EXCLUDED.url,
title = EXCLUDED.title,
location = EXCLUDED.location,
lots_count = EXCLUDED.lots_count,
first_lot_closing_time = EXCLUDED.first_lot_closing_time,
scraped_at = EXCLUDED.scraped_at,
city = EXCLUDED.city,
country = EXCLUDED.country,
type = EXCLUDED.type,
lot_count = EXCLUDED.lot_count,
closing_time = EXCLUDED.closing_time,
discovered_at = EXCLUDED.discovered_at
""",
(
auction_data['auction_id'],
auction_data['url'],
auction_data['title'],
location,
auction_data.get('lots_count', 0),
auction_data.get('first_lot_closing_time', ''),
auction_data['scraped_at'],
city,
country,
'online',
auction_data.get('lots_count', 0),
auction_data.get('first_lot_closing_time', ''),
int(time.time()),
),
)
conn.commit()
else:
with sqlite3.connect(self.db_path) as conn:
conn.execute(
"""
INSERT OR REPLACE INTO auctions
(auction_id, url, title, location, lots_count, first_lot_closing_time, scraped_at,
city, country, type, lot_count, closing_time, discovered_at)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""",
(
auction_data['auction_id'],
auction_data['url'],
auction_data['title'],
location,
auction_data.get('lots_count', 0),
auction_data.get('first_lot_closing_time', ''),
auction_data['scraped_at'],
city,
country,
'online',
auction_data.get('lots_count', 0),
auction_data.get('first_lot_closing_time', ''),
int(time.time()),
),
)
conn.commit()
def save_lot(self, lot_data: Dict):
"""Save lot data to database"""
params = (
lot_data['lot_id'],
lot_data.get('auction_id', ''),
lot_data['url'],
lot_data['title'],
lot_data.get('current_bid', ''),
lot_data.get('starting_bid', ''),
lot_data.get('minimum_bid', ''),
lot_data.get('bid_count', 0),
lot_data.get('closing_time', ''),
lot_data.get('viewing_time', ''),
lot_data.get('pickup_date', ''),
lot_data.get('location', ''),
lot_data.get('description', ''),
lot_data.get('category', ''),
lot_data.get('status', ''),
lot_data.get('brand', ''),
lot_data.get('model', ''),
lot_data.get('attributes_json', ''),
lot_data.get('first_bid_time'),
lot_data.get('last_bid_time'),
lot_data.get('bid_velocity'),
lot_data.get('bid_increment'),
lot_data.get('year_manufactured'),
lot_data.get('condition_score'),
lot_data.get('condition_description', ''),
lot_data.get('serial_number', ''),
lot_data.get('manufacturer', ''),
lot_data.get('damage_description', ''),
lot_data.get('followers_count', 0),
lot_data.get('estimated_min_price'),
lot_data.get('estimated_max_price'),
lot_data.get('lot_condition', ''),
lot_data.get('appearance', ''),
lot_data['scraped_at'],
lot_data.get('api_data_json'),
lot_data.get('next_scrape_at'),
lot_data.get('scrape_priority', 0),
)
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute(
"""
INSERT INTO lots
(lot_id, auction_id, url, title, current_bid, starting_bid, minimum_bid,
bid_count, closing_time, viewing_time, pickup_date, location, description,
category, status, brand, model, attributes_json,
first_bid_time, last_bid_time, bid_velocity, bid_increment,
year_manufactured, condition_score, condition_description,
serial_number, manufacturer, damage_description,
followers_count, estimated_min_price, estimated_max_price, lot_condition, appearance,
scraped_at, api_data_json, next_scrape_at, scrape_priority)
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
ON CONFLICT (lot_id)
DO UPDATE SET auction_id = EXCLUDED.auction_id,
url = EXCLUDED.url,
title = EXCLUDED.title,
current_bid = EXCLUDED.current_bid,
starting_bid = EXCLUDED.starting_bid,
minimum_bid = EXCLUDED.minimum_bid,
bid_count = EXCLUDED.bid_count,
closing_time = EXCLUDED.closing_time,
viewing_time = EXCLUDED.viewing_time,
pickup_date = EXCLUDED.pickup_date,
location = EXCLUDED.location,
description = EXCLUDED.description,
category = EXCLUDED.category,
status = EXCLUDED.status,
brand = EXCLUDED.brand,
model = EXCLUDED.model,
attributes_json = EXCLUDED.attributes_json,
first_bid_time = EXCLUDED.first_bid_time,
last_bid_time = EXCLUDED.last_bid_time,
bid_velocity = EXCLUDED.bid_velocity,
bid_increment = EXCLUDED.bid_increment,
year_manufactured = EXCLUDED.year_manufactured,
condition_score = EXCLUDED.condition_score,
condition_description = EXCLUDED.condition_description,
serial_number = EXCLUDED.serial_number,
manufacturer = EXCLUDED.manufacturer,
damage_description = EXCLUDED.damage_description,
followers_count = EXCLUDED.followers_count,
estimated_min_price = EXCLUDED.estimated_min_price,
estimated_max_price = EXCLUDED.estimated_max_price,
lot_condition = EXCLUDED.lot_condition,
appearance = EXCLUDED.appearance,
scraped_at = EXCLUDED.scraped_at,
api_data_json = EXCLUDED.api_data_json,
next_scrape_at = EXCLUDED.next_scrape_at,
scrape_priority = EXCLUDED.scrape_priority
""",
params,
)
conn.commit()
else:
with sqlite3.connect(self.db_path) as conn:
conn.execute(
"""
INSERT OR REPLACE INTO lots
(lot_id, auction_id, url, title, current_bid, starting_bid, minimum_bid,
bid_count, closing_time, viewing_time, pickup_date, location, description,
category, status, brand, model, attributes_json,
first_bid_time, last_bid_time, bid_velocity, bid_increment,
year_manufactured, condition_score, condition_description,
serial_number, manufacturer, damage_description,
followers_count, estimated_min_price, estimated_max_price, lot_condition, appearance,
scraped_at, api_data_json, next_scrape_at, scrape_priority)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""",
params,
)
conn.commit()
def save_bid_history(self, lot_id: str, bid_records: List[Dict]):
"""Save bid history records to database"""
if not bid_records:
return
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute("DELETE FROM bid_history WHERE lot_id = %s", (lot_id,))
for record in bid_records:
cur.execute(
"""
INSERT INTO bid_history
(lot_id, bid_amount, bid_time, is_autobid, bidder_id, bidder_number)
VALUES (%s, %s, %s, %s, %s, %s)
""",
(
record['lot_id'],
record['bid_amount'],
record['bid_time'],
1 if record['is_autobid'] else 0,
record['bidder_id'],
record['bidder_number'],
),
)
conn.commit()
else:
with sqlite3.connect(self.db_path) as conn:
conn.execute("DELETE FROM bid_history WHERE lot_id = ?", (lot_id,))
for record in bid_records:
conn.execute(
"""
INSERT INTO bid_history
(lot_id, bid_amount, bid_time, is_autobid, bidder_id, bidder_number)
VALUES (?, ?, ?, ?, ?, ?)
""",
(
record['lot_id'],
record['bid_amount'],
record['bid_time'],
1 if record['is_autobid'] else 0,
record['bidder_id'],
record['bidder_number'],
),
)
conn.commit()
def save_images(self, lot_id: str, image_urls: List[str]):
"""Save image URLs for a lot (prevents duplicates via unique constraint)"""
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
for url in image_urls:
cur.execute(
"""
INSERT INTO images (lot_id, url, downloaded)
VALUES (%s, %s, 0)
ON CONFLICT (lot_id, url) DO NOTHING
""",
(lot_id, url),
)
conn.commit()
else:
with sqlite3.connect(self.db_path) as conn:
for url in image_urls:
conn.execute(
"""
INSERT OR IGNORE INTO images (lot_id, url, downloaded)
VALUES (?, ?, 0)
""",
(lot_id, url),
)
conn.commit()
def update_image_local_path(self, lot_id: str, url: str, local_path: str):
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute(
"UPDATE images SET local_path = %s, downloaded = 1 WHERE lot_id = %s AND url = %s",
(local_path, lot_id, url),
)
conn.commit()
else:
with sqlite3.connect(self.db_path) as conn:
conn.execute(
"UPDATE images SET local_path = ?, downloaded = 1 WHERE lot_id = ? AND url = ?",
(local_path, lot_id, url),
)
conn.commit()
def save_resource(self, url: str, content: bytes, content_type: str, status_code: int = 200,
headers: Optional[Dict] = None, local_path: Optional[str] = None, cache_key: Optional[str] = None):
"""Save a web resource (JS, CSS, image, font, etc.) to cache
Args:
cache_key: Optional composite key (url + body hash for POST requests)
"""
headers_json = json.dumps(headers) if headers else None
size_bytes = len(content) if content else 0
key = cache_key if cache_key else url
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute(
"""
INSERT INTO resource_cache
(url, content, content_type, status_code, headers, timestamp, size_bytes, local_path)
VALUES (%s, %s, %s, %s, %s, %s, %s, %s)
ON CONFLICT (url)
DO UPDATE SET content = EXCLUDED.content,
content_type = EXCLUDED.content_type,
status_code = EXCLUDED.status_code,
headers = EXCLUDED.headers,
timestamp = EXCLUDED.timestamp,
size_bytes = EXCLUDED.size_bytes,
local_path = EXCLUDED.local_path
""",
(key, content, content_type, status_code, headers_json, time.time(), size_bytes, local_path),
)
conn.commit()
else:
with sqlite3.connect(self.db_path) as conn:
conn.execute(
"""
INSERT OR REPLACE INTO resource_cache
(url, content, content_type, status_code, headers, timestamp, size_bytes, local_path)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
""",
(key, content, content_type, status_code, headers_json, time.time(), size_bytes, local_path),
)
conn.commit()
def get_resource(self, url: str, cache_key: Optional[str] = None) -> Optional[Dict]:
"""Get a cached resource
Args:
cache_key: Optional composite key to lookup
"""
key = cache_key if cache_key else url
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute(
"SELECT content, content_type, status_code, headers, timestamp, size_bytes, local_path FROM resource_cache WHERE url = %s",
(key,),
)
row = cur.fetchone()
else:
with sqlite3.connect(self.db_path) as conn:
cursor = conn.execute(
"""
SELECT content, content_type, status_code, headers, timestamp, size_bytes, local_path
FROM resource_cache WHERE url = ?
""",
(key,),
)
row = cursor.fetchone()
if row:
return {
'content': row[0],
'content_type': row[1],
'status_code': row[2],
'headers': json.loads(row[3]) if row[3] else {},
'timestamp': row[4],
'size_bytes': row[5],
'local_path': row[6],
'cached': True
}
return None
# ------------------------
# Query helpers for scraper/monitor/export
# ------------------------
def get_counts(self) -> Dict[str, int]:
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute("SELECT COUNT(*) FROM auctions")
auctions = cur.fetchone()[0]
cur.execute("SELECT COUNT(*) FROM lots")
lots = cur.fetchone()[0]
return {"auctions": auctions, "lots": lots}
else:
with sqlite3.connect(self.db_path) as conn:
cur = conn.cursor()
cur.execute("SELECT COUNT(*) FROM auctions")
auctions = cur.fetchone()[0]
cur.execute("SELECT COUNT(*) FROM lots")
lots = cur.fetchone()[0]
return {"auctions": auctions, "lots": lots}
def get_lot_api_fields(self, lot_id: str) -> Optional[Tuple]:
sql = (
"SELECT followers_count, estimated_min_price, current_bid, bid_count, closing_time, status "
"FROM lots WHERE lot_id = %s" if self.use_postgres else
"SELECT followers_count, estimated_min_price, current_bid, bid_count, closing_time, status FROM lots WHERE lot_id = ?"
)
params = (lot_id,)
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute(sql, params)
return cur.fetchone()
else:
with sqlite3.connect(self.db_path) as conn:
cur = conn.cursor()
cur.execute(sql, params)
return cur.fetchone()
def get_page_record_by_url(self, url: str) -> Optional[Dict]:
# Try lot record first by URL
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute("SELECT * FROM lots WHERE url = %s", (url,))
lot_row = cur.fetchone()
if lot_row:
col_names = [desc.name for desc in cur.description]
lot_dict = dict(zip(col_names, lot_row))
return {"type": "lot", **lot_dict}
cur.execute("SELECT * FROM auctions WHERE url = %s", (url,))
auc_row = cur.fetchone()
if auc_row:
col_names = [desc.name for desc in cur.description]
auc_dict = dict(zip(col_names, auc_row))
return {"type": "auction", **auc_dict}
else:
with sqlite3.connect(self.db_path) as conn:
cur = conn.cursor()
cur.execute("SELECT * FROM lots WHERE url = ?", (url,))
lot_row = cur.fetchone()
if lot_row:
col_names = [d[0] for d in cur.description]
lot_dict = dict(zip(col_names, lot_row))
return {"type": "lot", **lot_dict}
cur.execute("SELECT * FROM auctions WHERE url = ?", (url,))
auc_row = cur.fetchone()
if auc_row:
col_names = [d[0] for d in cur.description]
auc_dict = dict(zip(col_names, auc_row))
return {"type": "auction", **auc_dict}
return None
def fetch_all(self, table: str) -> List[Dict]:
assert table in {"auctions", "lots"}
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute(f"SELECT * FROM {table}")
rows = cur.fetchall()
col_names = [desc.name for desc in cur.description]
return [dict(zip(col_names, r)) for r in rows]
else:
with sqlite3.connect(self.db_path) as conn:
conn.row_factory = sqlite3.Row
cur = conn.cursor()
cur.execute(f"SELECT * FROM {table}")
return [dict(row) for row in cur.fetchall()]
def get_lot_times(self, lot_id: str) -> Tuple[Optional[str], Optional[str]]:
sql = (
"SELECT viewing_time, pickup_date FROM lots WHERE lot_id = %s" if self.use_postgres else
"SELECT viewing_time, pickup_date FROM lots WHERE lot_id = ?"
)
params = (lot_id,)
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute(sql, params)
row = cur.fetchone()
else:
with sqlite3.connect(self.db_path) as conn:
cur = conn.cursor()
cur.execute(sql, params)
row = cur.fetchone()
if not row:
return None, None
return row[0], row[1]
def has_bid_history(self, lot_id: str) -> bool:
sql = (
"SELECT COUNT(*) FROM bid_history WHERE lot_id = %s" if self.use_postgres else
"SELECT COUNT(*) FROM bid_history WHERE lot_id = ?"
)
params = (lot_id,)
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute(sql, params)
cnt = cur.fetchone()[0]
else:
with sqlite3.connect(self.db_path) as conn:
cur = conn.cursor()
cur.execute(sql, params)
cnt = cur.fetchone()[0]
return cnt > 0
def get_downloaded_image_urls(self, lot_id: str) -> List[str]:
sql = (
"SELECT url FROM images WHERE lot_id = %s AND downloaded = 1" if self.use_postgres else
"SELECT url FROM images WHERE lot_id = ? AND downloaded = 1"
)
params = (lot_id,)
if self.use_postgres:
with self._pg() as conn, conn.cursor() as cur:
cur.execute(sql, params)
return [r[0] for r in cur.fetchall()]
else:
with sqlite3.connect(self.db_path) as conn:
cur = conn.cursor()
cur.execute(sql, params)
return [r[0] for r in cur.fetchall()]
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