fix car mapping

This commit is contained in:
qananasikq
2026-07-01 13:49:30 +03:00
commit 3cd7e785da
68 changed files with 14973 additions and 0 deletions

View File

@@ -0,0 +1 @@
__all__: list[str] = []

View File

@@ -0,0 +1,315 @@
import json
import os
from dataclasses import dataclass, field
from pathlib import Path
from dotenv import load_dotenv
load_dotenv()
TRUE_VALUES = {"1", "true", "yes", "on"}
def _resolve_env_value(name: str) -> str | None:
"""Возвращает значение env с поддержкой legacy-префиксов DUBIZZLE_/IAAI_."""
value = os.getenv(name)
if value is not None:
return value
if name.startswith("DUBIZZLE_"):
return os.getenv("IAAI_" + name[len("DUBIZZLE_"):])
return None
# Хелперы для чтения env-переменных с приведением типов
def _env_str(name: str, default: str) -> str:
value = _resolve_env_value(name)
return value if value is not None else default
def _env_optional_str(name: str) -> str | None:
value = _resolve_env_value(name)
if value is None:
return None
value = value.strip()
return value or None
def _env_path_str(name: str) -> str | None:
value = _env_optional_str(name)
if value is None:
return None
return str(Path(value).expanduser())
def _env_bool(name: str, default: bool) -> bool:
fallback = "true" if default else "false"
return _env_str(name, fallback).strip().lower() in TRUE_VALUES
def _env_int(name: str, default: int) -> int:
return int(_env_str(name, str(default)).strip())
def _env_float(name: str, default: float) -> float:
return float(_env_str(name, str(default)).strip())
# Конфиг браузерного отпечатка (User-Agent, viewport, timezone)
@dataclass(slots=True)
class FingerprintConfig:
user_agent: str = (
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
"AppleWebKit/537.36 (KHTML, like Gecko) "
"Chrome/135.0.0.0 Safari/537.36"
)
viewport_presets: tuple[dict[str, int], ...] = (
{"width": 1920, "height": 1080},
{"width": 1600, "height": 900},
{"width": 1536, "height": 864},
{"width": 1440, "height": 900},
{"width": 1366, "height": 768},
)
timezone_candidates: tuple[str, ...] = (
"America/New_York",
"America/Chicago",
"America/Los_Angeles",
)
locale: str = "en-US"
sec_ch_ua: str = '"Google Chrome";v="135", "Chromium";v="135", "Not.A/Brand";v="24"'
# Конфиг перехвата сетевых запросов (лимиты на кол-во)
@dataclass(slots=True)
class CaptureConfig:
capture_same_origin_only: bool = _env_bool("DUBIZZLE_CAPTURE_SAME_ORIGIN_ONLY", True)
max_requests: int = _env_int("DUBIZZLE_MAX_CAPTURED_REQUESTS", 40)
max_json_responses: int = _env_int("DUBIZZLE_MAX_CAPTURED_JSON_RESPONSES", 30)
# Конфиг пауз между действиями (имитация человека)
@dataclass(slots=True)
class HumanPaceConfig:
enabled: bool = _env_bool("DUBIZZLE_HUMAN_PACE_ENABLED", True)
after_listing_open_min_s: float = _env_float("DUBIZZLE_AFTER_LISTING_OPEN_MIN_S", 0.5)
after_listing_open_max_s: float = _env_float("DUBIZZLE_AFTER_LISTING_OPEN_MAX_S", 1.2)
after_filter_action_min_s: float = _env_float("DUBIZZLE_AFTER_FILTER_ACTION_MIN_S", 0.5)
after_filter_action_max_s: float = _env_float("DUBIZZLE_AFTER_FILTER_ACTION_MAX_S", 1.2)
before_vehicle_open_min_s: float = _env_float("DUBIZZLE_BEFORE_VEHICLE_OPEN_MIN_S", 0.1)
before_vehicle_open_max_s: float = _env_float("DUBIZZLE_BEFORE_VEHICLE_OPEN_MAX_S", 0.3)
after_vehicle_open_min_s: float = _env_float("DUBIZZLE_AFTER_VEHICLE_OPEN_MIN_S", 0.05)
after_vehicle_open_max_s: float = _env_float("DUBIZZLE_AFTER_VEHICLE_OPEN_MAX_S", 0.15)
between_vehicles_min_s: float = _env_float("DUBIZZLE_BETWEEN_VEHICLES_MIN_S", 0.05)
between_vehicles_max_s: float = _env_float("DUBIZZLE_BETWEEN_VEHICLES_MAX_S", 0.15)
after_page_change_min_s: float = _env_float("DUBIZZLE_AFTER_PAGE_CHANGE_MIN_S", 0.8)
after_page_change_max_s: float = _env_float("DUBIZZLE_AFTER_PAGE_CHANGE_MAX_S", 1.8)
# Конфиг сбора листинга (URL, лимиты страниц и машин)
@dataclass(slots=True)
class ListingConfig:
cars_url: str = _env_str("DUBIZZLE_CARS_LISTING_URL", "https://dubai.dubizzle.com/motors/used-cars/")
max_pages_per_run: int = _env_int("DUBIZZLE_MAX_PAGES_PER_RUN", 9999)
max_vehicles_per_run: int = _env_int("DUBIZZLE_MAX_VEHICLES_PER_RUN", 50000)
page_link_limit: int = _env_int("DUBIZZLE_PAGE_LINK_LIMIT", 500)
include_pagination: bool = _env_bool("DUBIZZLE_INCLUDE_PAGINATION", True)
collect_current_page_only: bool = _env_bool("DUBIZZLE_COLLECT_CURRENT_PAGE_ONLY", False)
# Порог раннего останова: если доля уже известных машин на странице >= этого значения,
# прекращаем листать — все новые машины уже найдены. 0 = отключено.
early_stop_threshold: float = _env_float("DUBIZZLE_EARLY_STOP_THRESHOLD", 0.8)
# Сегментация листинга по брендам для обхода лимита пагинации DUBIZZLE (~22 600 машин).
# JSON-массив объектов: [{"make":"TOYOTA"},{"make":"FORD"},...] или "auto" для авто-списка.
# Пустая строка = без сегментации (backward compatible).
listing_segments_json: str = _env_str("DUBIZZLE_LISTING_SEGMENTS", "")
# Пагинационный потолок одного Algolia-запроса: ~100 страниц × 100 = 10 000 результатов.
DUBIZZLE_PAGINATION_CEILING = 10_000
# Авто-сегментация по году. Эти диапазоны подобраны так, чтобы каждый сегмент
# оставался ниже лимита Algolia и собирался быстрее, чем старая make/year схема.
_AUTO_YEAR_SPLITS: tuple[tuple[int, int], ...] = (
(1900, 2012),
(2013, 2015),
(2016, 2017),
(2018, 2019),
(2020, 2021),
(2022, 2023),
(2024, 2025),
(2026, 2027),
)
def parse_listing_segments(raw: str) -> list[dict[str, str | int | None]]:
"""Парсит DUBIZZLE_LISTING_SEGMENTS в список сегментов.
Каждый сегмент — dict с ключами: make (str), year_min/year_max (int|None).
Специальное значение ``"auto"`` генерирует быстрые year-only сегменты,
которые гарантированно проходят через Algolia без упора в лимит ~10k.
"""
raw = raw.strip()
if not raw:
return []
if raw.lower() == "auto":
return [
{"make": None, "year_min": yr_min, "year_max": yr_max}
for yr_min, yr_max in _AUTO_YEAR_SPLITS
]
try:
data = json.loads(raw)
except (json.JSONDecodeError, ValueError):
return []
if not isinstance(data, list):
return []
segments = []
for item in data:
if isinstance(item, str):
segments.append({"make": item.upper(), "year_min": None, "year_max": None})
elif isinstance(item, dict):
segments.append({
"make": str(item.get("make") or "").upper() or None,
"year_min": int(item["year_min"]) if item.get("year_min") is not None else None,
"year_max": int(item["year_max"]) if item.get("year_max") is not None else None,
})
return segments
# - Конфиг PostgreSQL (URL, пул соединений, pool_recycle)
@dataclass(slots=True)
class DatabaseConfig:
url: str = _env_str("DUBIZZLE_DATABASE_URL", "postgresql+psycopg2://dubizzle:dubizzle@localhost:5432/dubizzle_scraper")
echo: bool = _env_bool("DUBIZZLE_DATABASE_ECHO", False)
pool_size: int = _env_int("DUBIZZLE_DATABASE_POOL_SIZE", 5)
max_overflow: int = _env_int("DUBIZZLE_DATABASE_MAX_OVERFLOW", 10)
pool_recycle_seconds: int = _env_int("DUBIZZLE_DATABASE_POOL_RECYCLE_SECONDS", 1800)
auto_create_tables: bool = _env_bool("DUBIZZLE_DATABASE_AUTO_CREATE_TABLES", False)
# --- Конфиг Redis (URL для Celery broker) ---
@dataclass(slots=True)
class RedisConfig:
url: str = _env_str("DUBIZZLE_REDIS_URL", "redis://localhost:6379/0")
socket_timeout_seconds: float = _env_float("DUBIZZLE_REDIS_SOCKET_TIMEOUT_SECONDS", 10.0)
socket_connect_timeout_seconds: float = _env_float("DUBIZZLE_REDIS_SOCKET_CONNECT_TIMEOUT_SECONDS", 5.0)
health_check_interval_seconds: int = _env_int("DUBIZZLE_REDIS_HEALTH_CHECK_INTERVAL_SECONDS", 30)
# --- Конфиг Discovery (режим обнаружения, hourly batch) ---
@dataclass(slots=True)
class DiscoveryConfig:
mode: str = _env_str("DUBIZZLE_DISCOVERY_MODE", "algolia")
hourly_mode: str = _env_str("DUBIZZLE_HOURLY_MODE", "rolling_refresh")
hourly_refresh_batch_size: int = _env_int("DUBIZZLE_HOURLY_REFRESH_BATCH_SIZE", 500)
always_full_scan: bool = _env_bool("DUBIZZLE_ALWAYS_FULL_SCAN", False)
sitemap_fallback_on_empty: bool = _env_bool("DUBIZZLE_SITEMAP_FALLBACK_ON_EMPTY", False)
@dataclass(slots=True)
class AlgoliaConfig:
application_id: str = _env_str("DUBIZZLE_ALGOLIA_APPLICATION_ID", "WD0PTZ13ZS")
api_key: str = _env_str(
"DUBIZZLE_ALGOLIA_API_KEY",
"cef139620248f1bc328a00fddc7107a6",
)
index_name: str = _env_str("DUBIZZLE_ALGOLIA_INDEX_NAME", "motors.com")
category_slug: str = _env_str("DUBIZZLE_ALGOLIA_CATEGORY_SLUG", "motors/used-cars")
base_url: str = _env_str("DUBIZZLE_ALGOLIA_BASE_URL", "https://WD0PTZ13ZS-dsn.algolia.net")
hits_per_page: int = _env_int("DUBIZZLE_ALGOLIA_HITS_PER_PAGE", 20)
# --- Конфиг Celery (лимиты задач, concurrency, beat-расписание) ---
@dataclass(slots=True)
class CeleryConfig:
broker_url: str = _env_str("CELERY_BROKER_URL", "")
result_backend: str = _env_str("CELERY_RESULT_BACKEND", "")
task_soft_time_limit: int = _env_int("CELERY_TASK_SOFT_TIME_LIMIT", 3300)
task_time_limit: int = _env_int("CELERY_TASK_TIME_LIMIT", 3600)
task_stall_timeout_seconds: int = _env_int("CELERY_TASK_STALL_TIMEOUT_SECONDS", 600)
worker_concurrency: int = _env_int("CELERY_WORKER_CONCURRENCY", 4)
worker_max_tasks_per_child: int = _env_int("CELERY_WORKER_MAX_TASKS_PER_CHILD", 5)
broker_visibility_timeout: int = _env_int("CELERY_BROKER_VISIBILITY_TIMEOUT", 7200)
beat_sync_interval_minutes: int = _env_int("CELERY_BEAT_SYNC_INTERVAL_MINUTES", 60)
beat_sync_limit: int | None = _env_int("CELERY_BEAT_SYNC_LIMIT", 0) or None
batch_size: int = _env_int("CELERY_BATCH_SIZE", 50)
parallel_tabs: int = _env_int("DUBIZZLE_PARALLEL_TABS", 8)
parallel_segments: bool = _env_bool("CELERY_PARALLEL_SEGMENTS", False)
block_resources: bool = _env_bool("DUBIZZLE_BLOCK_RESOURCES", True)
# --- Конфиг прокси (server, username, password) ---
@dataclass(slots=True)
class ProxyConfig:
server: str | None = _env_optional_str("DUBIZZLE_PROXY_SERVER")
username: str | None = _env_optional_str("DUBIZZLE_PROXY_USERNAME")
password: str | None = _env_optional_str("DUBIZZLE_PROXY_PASSWORD")
@property
def enabled(self) -> bool:
return bool(self.server)
def to_playwright_dict(self) -> dict[str, str] | None:
if not self.server:
return None
result: dict[str, str] = {"server": self.server}
if self.username:
result["username"] = self.username
if self.password:
result["password"] = self.password
return result
# Главный объект настроек: собирает все блоки конфигурации
@dataclass(slots=True)
class Settings:
home_url: str = "https://www.dubizzle.com/"
default_timeout_ms: int = _env_int("DUBIZZLE_TIMEOUT_MS", 45000)
network_settle_ms: int = _env_int("DUBIZZLE_NETWORK_SETTLE_MS", 400)
fast_path_timeout_ms: int = _env_int("DUBIZZLE_FAST_PATH_TIMEOUT_MS", 5000)
fast_path_max_attempts: int = _env_int("DUBIZZLE_FAST_PATH_MAX_ATTEMPTS", 1)
fallback_navigation_timeout_ms: int = _env_int("DUBIZZLE_FALLBACK_NAV_TIMEOUT_MS", 15000)
max_retries: int = _env_int("DUBIZZLE_MAX_RETRIES", 3)
retry_delay_seconds: float = _env_float("DUBIZZLE_RETRY_DELAY_SECONDS", 2.5)
retry_backoff_multiplier: float = _env_float("DUBIZZLE_RETRY_BACKOFF_MULTIPLIER", 2.0)
retry_jitter_seconds: float = _env_float("DUBIZZLE_RETRY_JITTER_SECONDS", 0.25)
headless: bool = _env_bool("DUBIZZLE_HEADLESS", True)
browser_engine: str = _env_str("DUBIZZLE_BROWSER_ENGINE", "auto")
log_level: str = _env_str("DUBIZZLE_LOG_LEVEL", "INFO")
log_file: str | None = _env_optional_str("DUBIZZLE_LOG_FILE")
enable_trace_id_logs: bool = _env_bool("DUBIZZLE_ENABLE_TRACE_ID_LOGS", True)
sync_only_new: bool = _env_bool("DUBIZZLE_SYNC_ONLY_NEW", False)
raw_output_json: str | None = _env_optional_str("DUBIZZLE_RAW_OUTPUT_JSON")
tokens_file: str | None = _env_path_str("DUBIZZLE_TOKENS_FILE")
runtime_config_file: str | None = _env_path_str("DUBIZZLE_RUNTIME_CONFIG_FILE")
scheduler_interval_minutes: int = _env_int("DUBIZZLE_SCHEDULER_INTERVAL_MINUTES", 60)
fingerprint: FingerprintConfig = field(default_factory=FingerprintConfig)
capture: CaptureConfig = field(default_factory=CaptureConfig)
pace: HumanPaceConfig = field(default_factory=HumanPaceConfig)
listing: ListingConfig = field(default_factory=ListingConfig)
database: DatabaseConfig = field(default_factory=DatabaseConfig)
redis: RedisConfig = field(default_factory=RedisConfig)
celery: CeleryConfig = field(default_factory=CeleryConfig)
proxy: ProxyConfig = field(default_factory=ProxyConfig)
discovery: DiscoveryConfig = field(default_factory=DiscoveryConfig)
algolia: AlgoliaConfig = field(default_factory=AlgoliaConfig)
@property
def parallel_tabs(self) -> int:
return self.celery.parallel_tabs
@property
def block_resources(self) -> bool:
return self.celery.block_resources
# Глобальный синглтон — используется по умолчанию во всех модулях.
settings = Settings()

View File

@@ -0,0 +1,14 @@
class ScraperError(Exception):
"""Базовое исключение скрапера."""
class AntiBotDetectedError(ScraperError):
"""Вызывается, когда сайт блокирует автоматизацию."""
class SiteStructureChangedError(ScraperError):
"""Вызывается, когда структура страницы изменилась и данных не хватает."""
class ListingResumeError(ScraperError):
"""Вызывается, когда resume по checkpoint больше недостижим."""

View File

@@ -0,0 +1,39 @@
import logging
import sys
from contextvars import ContextVar
# Храним trace_id текущего потока/корутины.
TRACE_ID: ContextVar[str] = ContextVar("trace_id", default="-")
class TraceIdFilter(logging.Filter):
# Добавляет trace_id в каждую запись лога для сквозной трассировки.
def filter(self, record: logging.LogRecord) -> bool:
record.trace_id = TRACE_ID.get()
return True
def set_trace_id(trace_id: str) -> None:
TRACE_ID.set(trace_id)
def setup_logging(level: str = "INFO", log_file: str | None = None) -> None:
# stderr — Docker и Celery prefork корректно его подхватывают.
handlers: list[logging.Handler] = [logging.StreamHandler(sys.stderr)]
if log_file:
handlers.append(logging.FileHandler(log_file, encoding="utf-8"))
trace_filter = TraceIdFilter()
for handler in handlers:
handler.addFilter(trace_filter)
handler.setLevel(getattr(logging, level.upper(), logging.INFO))
root = logging.getLogger()
root.setLevel(getattr(logging, level.upper(), logging.INFO))
# Убираем старые хендлеры, чтобы не дублировать после fork.
root.handlers.clear()
for handler in handlers:
root.addHandler(handler)
fmt = logging.Formatter(
"%(asctime)s | %(levelname)s | %(name)s | trace=%(trace_id)s | %(message)s"
)
for handler in root.handlers:
handler.setFormatter(fmt)

View File

@@ -0,0 +1,53 @@
import logging
import random
import time
from collections.abc import Callable
from functools import wraps
from typing import Any
from playwright.sync_api import Error, TimeoutError as PlaywrightTimeoutError
from .exceptions import AntiBotDetectedError
logger = logging.getLogger("dubizzle_scraper.retry")
# Типы исключений, при которых retry имеет смысл.
RETRYABLE_EXCEPTIONS = (
PlaywrightTimeoutError,
Error,
ConnectionError,
OSError,
TimeoutError,
AntiBotDetectedError,
)
def retryable(
max_attempts: int,
delay_seconds: float = 2.5,
backoff_multiplier: float = 2.0,
jitter_seconds: float = 0.0,
) -> Callable[[Callable[..., Any]], Callable[..., Any]]:
def decorator(func: Callable[..., Any]) -> Callable[..., Any]:
@wraps(func)
def wrapper(*args: Any, **kwargs: Any) -> Any:
last_error: Exception | None = None
for attempt in range(1, max_attempts + 1):
try:
return func(*args, **kwargs)
except RETRYABLE_EXCEPTIONS as exc:
last_error = exc
logger.warning("%s failed on attempt %s/%s: %s", func.__name__, attempt, max_attempts, exc)
if attempt < max_attempts:
sleep_for = delay_seconds * (backoff_multiplier ** (attempt - 1))
if jitter_seconds > 0:
sleep_for += random.uniform(0, jitter_seconds)
logger.debug("Retrying %s in %.2fs", func.__name__, sleep_for)
time.sleep(sleep_for)
if last_error is not None:
raise last_error
raise RuntimeError("Retry wrapper failed without a captured exception")
return wrapper
return decorator

View File

@@ -0,0 +1,301 @@
import json
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any
logger = logging.getLogger("dubizzle_scraper.runtime_config")
def _normalize_text(value: str) -> str:
return value.strip().casefold()
def _text_tuple(values: Any) -> tuple[str, ...]:
return tuple(
str(item).strip()
for item in (values or [])
if str(item).strip()
)
def _int_tuple(values: Any) -> tuple[int, ...]:
result: list[int] = []
for value in values or []:
try:
result.append(int(value))
except (TypeError, ValueError):
continue
return tuple(result)
def _optional_int(value: Any) -> int | None:
if value in (None, ""):
return None
try:
return int(value)
except (TypeError, ValueError):
return None
def _optional_bool(value: Any) -> bool | None:
if value is None:
return None
if isinstance(value, bool):
return value
if isinstance(value, str):
normalized = value.strip().casefold()
if normalized in {"1", "true", "yes", "on"}:
return True
if normalized in {"0", "false", "no", "off"}:
return False
return None
@dataclass(slots=True)
class RuntimeSyncConfig:
name: str | None = None
ids_initial_size: int | None = None
ids_next_size: int | None = None
ids_max_pages: int | None = None
condition_check_enabled: bool | None = None
lane: str | None = None
only_new: bool | None = None
limit: int | None = None
@classmethod
def from_dict(cls, data: dict[str, Any] | None) -> "RuntimeSyncConfig":
data = data or {}
name = str(data.get("name")).strip() if data.get("name") else None
lane = str(data.get("lane")).strip() if data.get("lane") else None
return cls(
name=name or None,
ids_initial_size=_optional_int(data.get("ids_initial_size")),
ids_next_size=_optional_int(data.get("ids_next_size")),
ids_max_pages=_optional_int(data.get("ids_max_pages")),
condition_check_enabled=_optional_bool(data.get("condition_check_enabled")),
lane=lane or None,
only_new=_optional_bool(data.get("only_new")),
limit=_optional_int(data.get("limit")),
)
@dataclass(slots=True)
class RuntimeListingConfig:
make: str | None = None
model: str | None = None
@classmethod
def from_dict(cls, data: dict[str, Any] | None) -> "RuntimeListingConfig":
data = data or {}
make = str(data.get("make")).strip() if data.get("make") else None
model = str(data.get("model")).strip() if data.get("model") else None
return cls(make=make or None, model=model or None)
@dataclass(slots=True)
class RuntimeFieldFilters:
brands: tuple[str, ...] = ()
models: tuple[str, ...] = ()
years: tuple[int, ...] = ()
body_types: tuple[str, ...] = ()
colors: tuple[str, ...] = ()
drives: tuple[str, ...] = ()
gearboxes: tuple[str, ...] = ()
locations: tuple[str, ...] = ()
@classmethod
def from_dict(cls, data: dict[str, Any] | None) -> "RuntimeFieldFilters":
data = data or {}
return cls(
brands=_text_tuple(data.get("brands")),
models=_text_tuple(data.get("models")),
years=_int_tuple(data.get("years")),
body_types=_text_tuple(data.get("body_types")),
colors=_text_tuple(data.get("colors")),
drives=_text_tuple(data.get("drives")),
gearboxes=_text_tuple(data.get("gearboxes")),
locations=_text_tuple(data.get("locations")),
)
def is_empty(self) -> bool:
return not any([
self.brands,
self.models,
self.years,
self.body_types,
self.colors,
self.drives,
self.gearboxes,
self.locations,
])
def matches(self, values: dict[str, Any]) -> bool:
return all([
self._match_text(self.brands, values.get("brand")),
self._match_text(self.models, values.get("model")),
self._match_int(self.years, values.get("year")),
self._match_text(self.body_types, values.get("body_type")),
self._match_text(self.colors, values.get("color")),
self._match_text(self.drives, values.get("drive")),
self._match_text(self.gearboxes, values.get("gearbox")),
self._match_text(self.locations, values.get("location")),
])
@staticmethod
def _match_text(allowed: tuple[str, ...], value: Any) -> bool:
if not allowed:
return True
normalized = _normalize_text(str(value or ""))
return normalized in {_normalize_text(item) for item in allowed}
@staticmethod
def _match_int(allowed: tuple[int, ...], value: Any) -> bool:
if not allowed:
return True
parsed = _optional_int(value)
return parsed in set(allowed)
@dataclass(slots=True)
class RuntimeRangeFilter:
min: int | None = None
max: int | None = None
@classmethod
def from_dict(cls, data: dict[str, Any] | None) -> "RuntimeRangeFilter":
data = data or {}
return cls(min=_optional_int(data.get("min")), max=_optional_int(data.get("max")))
def is_empty(self) -> bool:
return self.min is None and self.max is None
def matches(self, value: Any) -> bool:
parsed = _optional_int(value)
if parsed is None:
return self.is_empty()
if self.min is not None and parsed < self.min:
return False
if self.max is not None and parsed > self.max:
return False
return True
@dataclass(slots=True)
class RuntimeFlagFilters:
damaged_only: bool | None = None
run_and_drive: bool | None = None
@classmethod
def from_dict(cls, data: dict[str, Any] | None) -> "RuntimeFlagFilters":
data = data or {}
return cls(
damaged_only=_optional_bool(data.get("damaged_only")),
run_and_drive=_optional_bool(data.get("run_and_drive")),
)
def is_empty(self) -> bool:
return self.damaged_only is None and self.run_and_drive is None
def matches(self, values: dict[str, Any]) -> bool:
if self.damaged_only is not None and _optional_bool(values.get("is_damaged")) is not self.damaged_only:
return False
if self.run_and_drive is not None and _optional_bool(values.get("run_and_drive")) is not self.run_and_drive:
return False
return True
@dataclass(slots=True)
class RuntimeFiltersConfig:
include: RuntimeFieldFilters = field(default_factory=RuntimeFieldFilters)
exclude: RuntimeFieldFilters = field(default_factory=RuntimeFieldFilters)
price: RuntimeRangeFilter = field(default_factory=RuntimeRangeFilter)
mileage: RuntimeRangeFilter = field(default_factory=RuntimeRangeFilter)
flags: RuntimeFlagFilters = field(default_factory=RuntimeFlagFilters)
@classmethod
def from_dict(cls, data: dict[str, Any] | None) -> "RuntimeFiltersConfig":
data = data or {}
legacy_fields = RuntimeFieldFilters.from_dict(data)
include_payload = data.get("include")
exclude_payload = data.get("exclude")
flat_exclude_payload = {
"brands": data.get("exclude_brands"),
"models": data.get("exclude_models"),
"years": data.get("exclude_years"),
"body_types": data.get("exclude_body_types"),
"colors": data.get("exclude_colors"),
"drives": data.get("exclude_drives"),
"gearboxes": data.get("exclude_gearboxes"),
"locations": data.get("exclude_locations"),
}
include = RuntimeFieldFilters.from_dict(include_payload) if include_payload is not None else legacy_fields
exclude = (
RuntimeFieldFilters.from_dict(exclude_payload)
if exclude_payload is not None
else RuntimeFieldFilters.from_dict(flat_exclude_payload)
)
return cls(
include=include,
exclude=exclude,
price=RuntimeRangeFilter.from_dict(data.get("price")),
mileage=RuntimeRangeFilter.from_dict(data.get("mileage")),
flags=RuntimeFlagFilters.from_dict(data.get("flags")),
)
def is_empty(self) -> bool:
return all([
self.include.is_empty(),
self.exclude.is_empty(),
self.price.is_empty(),
self.mileage.is_empty(),
self.flags.is_empty(),
])
def matches(self, values: dict[str, Any]) -> bool:
if not self.include.matches(values):
return False
if not self._matches_exclude(values):
return False
if not self.price.matches(values.get("price")):
return False
if not self.mileage.matches(values.get("mileage")):
return False
if not self.flags.matches(values):
return False
return True
def _matches_exclude(self, values: dict[str, Any]) -> bool:
if self.exclude.is_empty():
return True
return not self.exclude.matches(values)
@dataclass(slots=True)
class RuntimeConfig:
sync: RuntimeSyncConfig = field(default_factory=RuntimeSyncConfig)
listing: RuntimeListingConfig = field(default_factory=RuntimeListingConfig)
filters: RuntimeFiltersConfig = field(default_factory=RuntimeFiltersConfig)
@classmethod
def from_file(cls, config_path: str | None) -> "RuntimeConfig":
if not config_path:
return cls()
path = Path(config_path)
if not path.exists():
logger.info("Runtime config file not found: %s", path)
return cls()
try:
payload = json.loads(path.read_text(encoding="utf-8"))
except Exception as exc:
logger.warning("Failed to read runtime config %s: %s", path, exc)
return cls()
return cls(
sync=RuntimeSyncConfig.from_dict(payload.get("sync")),
listing=RuntimeListingConfig.from_dict(payload.get("listing")),
filters=RuntimeFiltersConfig.from_dict(payload.get("filters")),
)

View File

@@ -0,0 +1,72 @@
import json
import re
from pathlib import Path
from typing import Any, Callable, Iterable
def save_to_json(data: Any, filename: str | Path) -> None:
path = Path(filename)
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
def first_non_empty(values: Iterable[Any]) -> Any | None:
for value in values:
if value not in (None, "", [], {}, ()):
return value
return None
# Регулярные выражения для VIN, lot и price.
VIN_RE = re.compile(r"\b([A-HJ-NPR-Z0-9]{17})\b", re.IGNORECASE)
LOT_RE = re.compile(r"\b(\d{7,10})\b")
PRICE_RE = re.compile(r"\$\s?([\d,]+(?:\.\d{1,2})?)")
def deep_find_key(obj, target_keys: set[str], max_depth: int = 64, _depth: int = 0) -> list:
# Рекурсивно ищет значения по набору ключей в произвольном JSON-дереве.
found = []
if _depth >= max_depth:
return found
if isinstance(obj, dict):
for key, value in obj.items():
if key.lower() in target_keys:
found.append(value)
found.extend(deep_find_key(value, target_keys, max_depth=max_depth, _depth=_depth + 1))
elif isinstance(obj, list):
for item in obj:
found.extend(deep_find_key(item, target_keys, max_depth=max_depth, _depth=_depth + 1))
return found
def deep_find_all_keys(
payloads: list,
field_map: dict[str, set[str]],
max_depth: int = 64,
) -> dict[str, list]:
"""Извлекает все нужные поля за один проход по JSON."""
# Готовим обратную карту: нормализованный ключ -> имя поля.
reverse: dict[str, str] = {}
for field_name, keys in field_map.items():
for k in keys:
reverse[k.lower()] = field_name
result: dict[str, list] = {f: [] for f in field_map}
def _recurse(obj: Any, depth: int) -> None:
if depth >= max_depth:
return
if isinstance(obj, dict):
for k, v in obj.items():
field = reverse.get(k.lower())
if field is not None:
result[field].append(v)
_recurse(v, depth + 1)
elif isinstance(obj, list):
for item in obj:
_recurse(item, depth + 1)
for payload in payloads:
_recurse(payload, 0)
return result