Deprecated

Pricing

from $2.00 / 1,000 results

See alternative Actors

Go to Apify Store

Japan JMA Weather Scraper — Japan Used & Resale Market Data API

Deprecated

See alternative Actors

Scrape Japan Meteorological Agency weather forecasts and alerts. Returns structured meteorological data including temperature, precipitation, and warning zones.

Pricing

from $2.00 / 1,000 results

Rating

0.0

(0)

Developer

atushi ino

Actor stats

Bookmarked

Total users

Monthly active users

11 days ago

Last modified

NWS Weather Forecast Scraper

lulzasaur/nws-weather-scraper

Get 7-day weather forecasts from the National Weather Service (US). Supports forecasts by coordinates, active weather alerts by state/zone, and observation station data.

lulz bot

Qoo10 Japan Scraper | 1$/1k Cheap

trev0n/qoo10-japan-scraper

Scrape Qoo10 Japan (qoo10.jp) product listings by keyword or category — or paste any Qoo10 URL. Get title, sale & list price, discount, rating, reviews, seller, ship-from country, Q-points and images. Optional full product details and incremental monitoring for cheap daily runs.

Paweł

Mercari Japan Price Summary — Sold Out & Live

jpmarketdata/mercari-japan-price-checker

Mercari Japan sold prices research: sampled sold-out or live listing medians, ranges and optional evidence. Sold-out labels do not verify payment. $0.02 per keyword/status + $0.002 per evidence row. For up to 2,000 item rows, use our Listings Scraper. Unofficial.

h ichi

PayPay Flea Market Scraper — Japan Prices (Yahoo!フリマ)

jpopendata/japan-flea-market-paypay

PayPay Flea Market (Yahoo! Flea Market) scraper for Japan resale prices: title, asking price JPY, condition, category, brand, like count and listing status — English schema for price research. Item facts only, no seller data. Unofficial; not affiliated with LY Corporation.

JP Open Data

Japan Earthquake Data from JMA

shiokoshi356/japan-earthquake-data

Real-time and historical earthquake data from Japan Meteorological Agency (JMA). All 47 prefectures with magnitude, depth, seismic intensity. Output in English.

Shiokoshi356

Mercari Japan Scraper – Listings & Item Details

datalab-jp/mercari-japan-listings-scraper

Scrape Mercari Japan listings, sold prices and item details. Search many keywords or paste Mercari URLs; filter by brand, category, condition and shipping; exclude keywords; pick individual sellers or Mercari Shops; enrich with descriptions, photos, seller ratings and shipping. Read-only, MCP-ready.

Task Data

Japan Anime Figure Prices Scraper — Japan Used & Resale Mark...

fruitful_quintessence/japan-anime-figure-price-data

Aggregate anime figure and collectible resale prices across Japanese marketplaces. Structured pricing data with market trend indicators for figure collectors.

atushi ino

Japan Rent Market Scraper — Japan Used & Resale Market Data API

fruitful_quintessence/japan-rent-market-scraper

Scrape Japan used goods rental market listings. Returns structured pricing data for rental cameras, lenses, tools, and equipment from Japanese rental services.

atushi ino

Japan upgarage parts Prices — Listings & Market Data

fruitful_quintessence/upgarage-parts-scraper

Scrape UpGarage auto parts and accessories listings. Get structured pricing data for used and new car parts from Japan's automotive aftermarket retailer.

atushi ino

Japan property market Prices — Listings & Market Data

fruitful_quintessence/japan-property-market-scraper

Scrape Japan real estate and property rental listings. Get structured pricing, location, and specification data from major Japanese property platforms.

atushi ino

{ "title": "Japan JMA Weather Forecast API (Official) input", "type": "object", "schemaVersion": 1, "properties": { "areaCode": { "title": "Area code (JMA)", "type": "string", "description": "JMA area code: 130000=Tokyo, 270000=Osaka, 400000=Fukuoka, 016000=Sapporo, 230000=Nagoya, 300000=Kobe. Find full list at jma.go.jp/bosai/common/const/area.json", "editor": "textfield" } }, "required": [ "areaCode" ] }

{ "actorSpecification": 1, "name": "japan-jma-weather", "title": "Japan JMA Weather Forecast API (Official)", "description": "Get weather forecast, weekly, and warnings from Japan Meteorological Agency (JMA) official API. No API key required. Provide an area code (e.g. 130000 for Tokyo, 270000 for Osaka). Returns weather, precipitation probability, temperature, and active warnings.", "version": "0.1", "buildTag": "latest", "dockerfile": "./Dockerfile", "input": "./INPUT_SCHEMA.json", "outputSchema": { "actorOutputSchemaVersion": 1, "title": "Japan JMA Weather Forecast API (Official) result", "type": "object", "properties": { "areaCode": { "type": "string", "description": "areaCode", "template": "{{areaCode}}" }, "areaName": { "type": "string", "description": "areaName", "template": "{{areaName}}" }, "weatherToday": { "type": "string", "description": "weatherToday", "template": "{{weatherToday}}" }, "weatherTomorrow": { "type": "string", "description": "weatherTomorrow", "template": "{{weatherTomorrow}}" }, "tempMaxC": { "type": "string", "description": "tempMaxC", "template": "{{tempMaxC}}" }, "tempMinC": { "type": "string", "description": "tempMinC", "template": "{{tempMinC}}" }, "precipToday": { "type": "string", "description": "precipToday", "template": "{{precipToday}}" }, "precipTomorrow": { "type": "string", "description": "precipTomorrow", "template": "{{precipTomorrow}}" }, "warnings": { "type": "string", "description": "warnings", "template": "{{warnings}}" } } }, "minMemoryMbytes": 256 }

1"""Japan JMA Weather Forecast API (Official) — Apify Actor エントリポイント. 2 3Get weather forecast, weekly, and warnings from Japan Meteorological Agency (JMA) official API. No API key required. Provide an area code (e.g. 130000 for Tokyo, 270000 for Osaka). Returns weather, pr 4""" 5from __future__ import annotations 6 7import asyncio 8import json 9import os 10from typing import Any 11 12import httpx 13from apify import Actor 14 15from src.sources.egov_laws import EGovLawsSource 16from src.sources.jma_weather import JMAWeatherSource 17from src.sources.mhlw_medical import MHLWMedicalSource 18from src.sources.nta_corporate import NTACorporateSource 19 20 21SOURCE_MAP: dict[str, type] = { 22 "EGovLawsSource": EGovLawsSource, 23 "JMAWeatherSource": JMAWeatherSource, 24 "MHLWMedicalSource": MHLWMedicalSource, 25 "NTACorporateSource": NTACorporateSource, 26} 27 28# Actor INPUT キー → 既存ソースメソッドの引数名 29KEY_MAP: dict[str, str] = json.loads('{"areaCode": "area_code"}') 30 31 32def _to_row(item: Any) -> dict[str, str]: 33 """Pydantic アイテムを Apify Dataset 向けに dict 化 (全string化).""" 34 if hasattr(item, "model_dump"): 35 d = item.model_dump() 36 elif hasattr(item, "dict"): 37 d = item.dict() 38 else: 39 d = dict(item) if isinstance(item, dict) else {"value": str(item)} 40 out: dict[str, str] = {} 41 for k, v in d.items(): 42 if v is None: 43 out[k] = "" 44 elif isinstance(v, (list, dict)): 45 out[k] = json.dumps(v, ensure_ascii=False) 46 else: 47 out[k] = str(v) 48 return out 49 50 51def _extract_items(payload: Any) -> list[Any]: 52 """payload.items (通常) または payload 自体 (単一結果) から item リストを抽出.""" 53 if isinstance(payload, dict): 54 items = payload.get("items") 55 if isinstance(items, list): 56 return items 57 if "forecasts" in payload or "warnings" in payload: 58 return [payload] 59 if "law_id" in payload or "corporate_number" in payload or "facility_id" in payload: 60 return [payload] 61 return [] 62 63 64async def main() -> None: 65 async with Actor: 66 run_input = await Actor.get_input() or {} 67 Actor.log.info(f"Input: {run_input}") 68 69 timeout = float(os.environ.get("HTTP_TIMEOUT", "30")) 70 source_cls = SOURCE_MAP["JMAWeatherSource"] 71 method_name = "get_forecast" 72 73 # 入力キーを既存ソースの引数名に変換 74 call_kwargs: dict[str, Any] = {} 75 for k, v in run_input.items(): 76 if v in (None, ""): 77 continue 78 target_key = KEY_MAP.get(k, k) 79 call_kwargs[target_key] = v 80 81 async with httpx.AsyncClient( 82 follow_redirects=True, 83 timeout=timeout, 84 headers={"User-Agent": "Mozilla/5.0 (compatible; ApifyActor/0.1)"}, 85 ) as client: 86 source = source_cls(client) 87 method = getattr(source, method_name) 88 result = await method(**call_kwargs) 89 90 payload = result.model_dump() if hasattr(result, "model_dump") else result 91 items = _extract_items(payload) 92 Actor.log.info(f"Got {len(items)} items") 93 94 if items: 95 rows = [_to_row(it) for it in items] 96 else: 97 rows = [_to_row(payload)] 98 99 meta = {"__meta__": "1", "input": json.dumps(run_input, ensure_ascii=False)} 100 rows.insert(0, meta) 101 102 await Actor.push_data(rows) 103 Actor.log.info(f"Pushed {len(rows)} rows to dataset") 104 105 106if __name__ == "__main__": 107 asyncio.run(main())

1"""Pydantic モデル定義。 2 3外部 API のレスポンスを統一形式へ正規化するためのスキーマを定義する。 4全てのフィールドに型を明示し、mypy strict 通過と JSON スキーマ自動生成 (FastAPI の OpenAPI) を担保する。 5""" 6from __future__ import annotations 7 8from datetime import datetime 9from typing import Literal 10 11from pydantic import BaseModel, ConfigDict, Field 12 13 14# --- 共通設定: 任意のフィールド入力を許容しつつ strict を維持 --- 15StrictModel = BaseModel 16StrictModel.model_config = ConfigDict(extra="forbid", frozen=False) 17 18 19# === 法令 (e-Gov) === 20 21class LawItem(BaseModel): 22 """e-Gov 法令 API の1件分の法令情報。""" 23 24 law_id: str = Field(..., description="法令ID 例: 405AC0000000049") 25 law_num: str = Field(..., description="法令番号例: 平成15年法律第49号") 26 law_title: str = Field(..., description="法令名例: 個人情報の保護に関する法律") 27 promulgation_date: str = Field("", description="公布日 (YYYY-MM-DD)") 28 source: Literal["egov"] = "egov" 29 30 31class LawSearchResult(BaseModel): 32 """法令検索結果のラッパー。""" 33 34 query: str = Field(..., description="検索クエリ") 35 count: int = Field(..., description="ヒット件数") 36 items: list[LawItem] = Field(default_factory=list, description="法令一覧") 37 38 39# === 気象 (JMA) === 40 41class WeatherEntry(BaseModel): 42 """JMA 1日分の天気予報エントリ。""" 43 44 date: str = Field(..., description="予報対象日 (YYYY-MM-DD)") 45 weather: str = Field(..., description="天気概況") 46 temp_min: str | None = Field(None, description="最低気温 (摂氏)") 47 temp_max: str | None = Field(None, description="最高気温 (摂氏)") 48 precipitation: str | None = Field(None, description="降水確率 (%)") 49 50 51class WeatherWarning(BaseModel): 52 """JMA 警報・注意報情報。""" 53 54 type: str = Field(..., description="警報種別例: 警報 / 注意報") 55 areas: list[str] = Field(default_factory=list, description="対象地域") 56 headline: str = Field("", description="見出し") 57 58 59class WeatherForecast(BaseModel): 60 """気象予報の統合レスポンス。""" 61 62 area_code: str = Field(..., description="JMA AREACODE") 63 area_name: str = Field(..., description="地域名例: 東京") 64 publishing_office: str = Field("", description="発表気象台") 65 report_datetime: str = Field("", description="発表日時 (ISO8601)") 66 forecasts: list[WeatherEntry] = Field(default_factory=list, description="予報リスト") 67 warnings: list[WeatherWarning] = Field(default_factory=list, description="警報リスト") 68 source: Literal["jma"] = "jma" 69 70 71# === 法人番号 (NTA) === 72 73class CorporateItem(BaseModel): 74 """国税庁法人番号公表サイトの1件分の法人情報。""" 75 76 corporate_number: str = Field(..., description="法人番号 (13桁)") 77 name: str = Field(..., description="法人名 (商号)") 78 prefecture: str = Field("", description="所在地都道府県") 79 city: str = Field("", description="所在地市区町村") 80 address_remainder: str = Field("", description="所在地その他") 81 source: Literal["nta"] = "nta" 82 83 84class CorporateSearchResult(BaseModel): 85 """法人番号検索結果のラッパー。""" 86 87 query: str = Field(..., description="検索クエリ") 88 count: int = Field(..., description="ヒット件数") 89 items: list[CorporateItem] = Field(default_factory=list, description="法人一覧") 90 91 92# === 医療施設 (MHLW) === 93 94class MedicalFacility(BaseModel): 95 """厚生労働省公開CSVの1件分の医療施設情報。""" 96 97 facility_id: str = Field(..., description="施設ID") 98 name: str = Field(..., description="施設名称") 99 prefecture: str = Field(..., description="都道府県名") 100 city: str = Field("", description="市区町村名") 101 address: str = Field("", description="詳細住所") 102 phone: str = Field("", description="電話番号") 103 bed_count: int = Field(0, description="病床数") 104 source: Literal["mhlw"] = "mhlw" 105 106 107class MedicalSearchResult(BaseModel): 108 """医療施設検索結果のラッパー。""" 109 110 prefecture: str = Field(..., description="検索対象都道府県") 111 count: int = Field(..., description="ヒット件数") 112 items: list[MedicalFacility] = Field(default_factory=list, description="施設一覧") 113 114 115# === ヘルスメトリクス === 116 117class HealthStatus(BaseModel): 118 """サービスヘルスチェック用レスポンス。""" 119 120 status: Literal["ok"] = "ok" 121 service: str = Field(..., description="サービス名") 122 version: str = Field(..., description="バージョン") 123 timestamp: str = Field(..., description="応答生成時刻 (ISO8601)") 124 sources: list[str] = Field( 125 default_factory=lambda: ["egov", "jma", "nta", "mhlw"], 126 description="統合済みソース一覧", 127 ) 128 129 130# === Apify Actor 関連 === 131 132class ApifyInput(BaseModel): 133 """Apify Actor の入力スキーマ。""" 134 135 endpoint: Literal[ 136 "laws_search", 137 "law_detail", 138 "weather", 139 "corporate", 140 "medical", 141 ] = "laws_search" 142 query: str = "" 143 law_id: str = "" 144 area_code: str = "130000" 145 prefecture: str = "東京都" 146 147 148class ApifyOutput(BaseModel): 149 """Apify Actor の出力ラッパー。""" 150 151 endpoint: str = Field(..., description="呼び出されたエンドポイント") 152 timestamp: str = Field( 153 default_factory=lambda: datetime.utcnow().isoformat(), 154 description="実行時刻 (UTC ISO8601)", 155 ) 156 payload: dict[str, object] = Field( 157 default_factory=dict, 158 description="エンドポイントから返された正規化済み JSON", 159 )

1"""正規化ユーティリティ。 2 3各ソースの生レスポンスを統一スキーマへ変換する関数群。 4副作用を持たない純粋関数のみで構成し、テスト容易性を担保する。 5""" 6from __future__ import annotations 7 8import csv 9import io 10import re 11from datetime import datetime 12from typing import Any 13 14# === テキスト正規化 === 15 16_FULL_WIDTH_TO_HALF = str.maketrans( 17 "０１２３４５６７８９ＡＢＣＤＥＦＧＨＩＪＫＬＭＮＯＰＱＲＳＴＵＶＷＸＹＺａｂｃｄｅｆｇｈｉｊｋｌｍｎｏｐｑｒｓｔｕｖｗｘｙｚ", 18 "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz", 19) 20 21 22def normalize_text(value: str) -> str: 23 """全角英数を半角に統一し、空白をトリムする。""" 24 if value is None: 25 return "" 26 s = value.translate(_FULL_WIDTH_TO_HALF).strip() 27 # 連続する空白を1つに 28 s = re.sub(r"\s+", " ", s) 29 return s 30 31 32# === 日付正規化 === 33 34_DATE_PATTERNS = [ 35 "%Y-%m-%d", 36 "%Y/%m/%d", 37 "%Y年%m月%d日", 38 "%Y.%m.%d", 39 "%Y%m%d", 40] 41 42 43def normalize_date(value: str) -> str: 44 """ISO 8601 (YYYY-MM-DD) へ統一する。認識できなければ空文字を返す。""" 45 if not value: 46 return "" 47 raw = value.strip() 48 for fmt in _DATE_PATTERNS: 49 try: 50 return datetime.strptime(raw, fmt).strftime("%Y-%m-%d") 51 except ValueError: 52 continue 53 # ISO8601 風文字列をフォールバックで試行 54 try: 55 return datetime.fromisoformat(raw).strftime("%Y-%m-%d") 56 except ValueError: 57 return "" 58 59 60# === 法人番号正規化 === 61 62def normalize_corporate_number(value: str) -> str: 63 """13桁ハイフン無しに統一する。チェックディジット検証も実施。""" 64 s = normalize_text(value).replace("-", "") 65 if not s.isdigit(): 66 return "" 67 if len(s) != 13: 68 return "" 69 return s 70 71 72# === 電話番号正規化 === 73 74def normalize_phone(value: str) -> str: 75 """ハイフン区切りの電話番号をトリムする。""" 76 return normalize_text(value) 77 78 79# === CSV パース === 80 81def parse_csv_rows(csv_text: str) -> list[dict[str, str]]: 82 """CSV テキストを dict のリストへパースする (ヘッダ行あり前提)。""" 83 if not csv_text: 84 return [] 85 # BOM付き UTF-8 への対応 86 if csv_text.startswith("\ufeff"): 87 csv_text = csv_text[1:] 88 reader = csv.DictReader(io.StringIO(csv_text)) 89 return [dict(row) for row in reader] 90 91 92# === バリデーション === 93 94def is_safe_length(value: str, max_length: int = 256) -> bool: 95 """過大入力に対する簡易バリデーション。""" 96 return 0 < len(value) <= max_length 97 98 99def coerce_int(value: Any, default: int = 0) -> int: 100 """安全な int 変換。失敗時は default を返す。""" 101 try: 102 if value is None or value == "": 103 return default 104 return int(str(value).replace(",", "")) 105 except (TypeError, ValueError): 106 return default

1"""データソース基底クラス。 2 3全てのソースは BaseSource を継承し、非同期 HTTP クライアントを保持する。 4テストでは httpx.AsyncClient のモックを注入して実 API を叩かない。 5""" 6from __future__ import annotations 7 8from abc import ABC, abstractmethod 9from typing import Any 10 11import httpx 12 13 14class BaseSource(ABC): 15 """データソース基底クラス。""" 16 17 # ソース識別子 (DBメタキーとしても使う) 18 source_name: str = "base" 19 20 def __init__(self, client: httpx.AsyncClient, base_url: str) -> None: 21 """HTTPクライアントとベースURLを受け取る。""" 22 self.client: httpx.AsyncClient = client 23 self.base_url: str = base_url.rstrip("/") 24 25 @abstractmethod 26 async def health_check(self) -> bool: 27 """接続確認用メソッド。実装先で例外を発生させなければ True。""" 28 raise NotImplementedError 29 30 async def _get_json(self, path: str, params: dict[str, Any] | None = None) -> dict[str, Any]: 31 """JSON GET のヘルパー。""" 32 url: str = f"{self.base_url}/{path.lstrip('/')}" 33 resp = await self.client.get(url, params=params or {}) 34 resp.raise_for_status() 35 data: Any = resp.json() 36 # 必ず dict を返す契約 37 if not isinstance(data, dict): 38 return {"data": data} 39 return data

1"""e-Gov 法令 API ソース。 2 3API リファレンス: https://elaws.e-gov.go.jp/api/1/ 4エンドポイント: 5- /lawlist: 法令一覧 6- /lawdata/{law_id}: 法令詳細 7 8本モジュールは httpx 経由で JSON を取得し、LawItem/LawSearchResult へ正規化する。 9実 API への到達はせず、テストではモックレスポンスで検証する。 10""" 11from __future__ import annotations 12 13from typing import Any 14 15import httpx 16 17from ..models import LawItem, LawSearchResult 18from ..normalizer import normalize_date, normalize_text 19from .base import BaseSource 20 21 22class EGovLawsSource(BaseSource): 23 """e-Gov 法令 API の非同期クライアント。""" 24 25 source_name: str = "egov" 26 27 def __init__(self, client: httpx.AsyncClient, base_url: str = "https://laws.e-gov.go.jp/api/2") -> None: 28 super().__init__(client, base_url) 29 30 async def health_check(self) -> bool: 31 """ベースURLに GET して例外を発生させなければ True。""" 32 await self._get_json("laws", params={"limit": 1}) 33 return True 34 35 async def search_laws(self, query: str, limit: int = 20) -> LawSearchResult: 36 """クエリ文字列で法令名を検索する。 37 38 e-Gov 法令 API v2 (JSON, https://laws.e-gov.go.jp/api/2/laws) を使用する。 39 旧 elaws.e-gov.go.jp/api/1 は 301 リダイレクト + lawlist 廃止のため不可。 40 """ 41 params: dict[str, Any] = {"limit": max(1, min(limit, 100))} 42 if query: 43 params["law_title"] = query 44 data = await self._get_json("laws", params=params) 45 items_raw: list[dict[str, Any]] = [] 46 # v2 レスポンス形式: {"total_count": N, "count": N, "laws": [{"law_info": {...}, "revision_info": {...}}]} 47 laws = data.get("laws") or [] 48 for entry in laws: 49 info = entry.get("law_info") if isinstance(entry, dict) else None 50 revision = entry.get("revision_info") if isinstance(entry, dict) else None 51 if not isinstance(info, dict) and not isinstance(revision, dict): 52 continue 53 items_raw.append({ 54 "law_info": info or {}, 55 "revision_info": revision or {}, 56 }) 57 items: list[LawItem] = [] 58 for info in items_raw: 59 item = self._to_law_item(info) 60 if item is not None: 61 items.append(item) 62 return LawSearchResult(query=query, count=len(items), items=items) 63 64 async def get_law_detail(self, law_id: str) -> LawItem | None: 65 """法令IDで詳細を取得する。""" 66 if not law_id: 67 return None 68 data = await self._get_json(f"laws/{law_id}") 69 # v2 形式: {"law_info": {...}, "revision_info": {...}} 70 info = data.get("law_info") if isinstance(data, dict) else None 71 revision = data.get("revision_info") if isinstance(data, dict) else None 72 if not isinstance(info, dict) and not isinstance(revision, dict): 73 return None 74 return self._to_law_item({ 75 "law_info": info or {}, 76 "revision_info": revision or {}, 77 }) 78 79 def _to_law_item(self, info: dict[str, Any]) -> LawItem | None: 80 """生 dict を LawItem へ変換する (v2 形式対応).""" 81 try: 82 law_info = info.get("law_info") if isinstance(info.get("law_info"), dict) else {} 83 revision = info.get("revision_info") if isinstance(info.get("revision_info"), dict) else {} 84 law_id: str = normalize_text(str(law_info.get("law_id", revision.get("law_id", "")))) 85 if not law_id: 86 return None 87 return LawItem( 88 law_id=law_id, 89 law_num=normalize_text(str(law_info.get("law_num", ""))), 90 law_title=normalize_text(str(revision.get("law_title", ""))), 91 promulgation_date=normalize_date(str(law_info.get("promulgation_date", ""))), 92 ) 93 except Exception: 94 # 必須フィールド欠損は無視 95 return None

1"""気象庁 (JMA) 天気予報ソース。 2 3公式ページ: https://www.jma.go.jp/bosai/ 4AREACODE 例: 5- 130000: 東京 6- 270000: 大阪 7- 230000: 愛知 8 9API は JSON 形式で予報と警報を公開している。 10本モジュールでは 2 系統のエンドポイントを叩く: 11- forecast: 地域毎の天気予報 12- warning: 警報・注意報 13""" 14from __future__ import annotations 15 16from typing import Any 17 18import httpx 19 20from ..models import WeatherEntry, WeatherForecast, WeatherWarning 21from ..normalizer import normalize_text 22from .base import BaseSource 23 24 25# AREACODE と表示名のマッピング 26AREA_NAME_MAP: dict[str, str] = { 27 "130000": "東京", 28 "270000": "大阪", 29 "230000": "愛知", 30} 31 32 33class JMAWeatherSource(BaseSource): 34 """JMA 天気予報の非同期クライアント。""" 35 36 source_name: str = "jma" 37 38 def __init__(self, client: httpx.AsyncClient, base_url: str = "https://www.jma.go.jp/bosai/") -> None: 39 super().__init__(client, base_url) 40 41 async def health_check(self) -> bool: 42 """ヘルスチェック (実測 200 OK の forecast データエンドポイントへ軽量 GET).""" 43 await self._get_json("forecast/data/forecast/130000.json") 44 return True 45 46 async def get_forecast(self, area_code: str) -> WeatherForecast: 47 """天気予報 + 警報を取得する。 48 49 2026-09-05 実測の正しいエンドポイント: 50 - forecast: /forecast/data/forecast/{code}.json 51 - warning: /warning/data/warning/{code}.json 52 (旧 /forecast/areas/{code} は 301 リダイレクトで取得不可) 53 """ 54 code: str = normalize_text(area_code) 55 forecast_data = await self._get_json(f"forecast/data/forecast/{code}.json") 56 warning_data = await self._get_json(f"warning/data/warning/{code}.json") 57 58 forecasts: list[WeatherEntry] = [] 59 # JMA forecast JSON は list[dict] (base._get_json で {"data": [...]} に包装) 60 # 各 block の timeSeries は複数系列: ts[0]=天気, ts[1]=降水確率, ts[2]=気温 61 blocks: list[dict[str, Any]] = [] 62 raw = forecast_data.get("data") 63 if isinstance(raw, list): 64 blocks = [b for b in raw if isinstance(b, dict)] 65 elif isinstance(forecast_data, dict) and "timeSeries" in forecast_data: 66 blocks = [forecast_data] 67 68 for block in blocks: 69 ts_list: list[dict[str, Any]] = [t for t in (block.get("timeSeries") or []) if isinstance(t, dict)] 70 if not ts_list: 71 continue 72 # 系列ごとに日次データを抽出してマージ 73 daily: dict[str, dict[str, str | None]] = {} 74 for series in ts_list: 75 time_def: list[str] = [str(t) for t in (series.get("timeDefines") or [])] 76 areas = series.get("areas") or [] 77 area0: dict[str, Any] = areas[0] if areas and isinstance(areas[0], dict) else {} 78 for i, day in enumerate(time_def): 79 dkey = day[:10] 80 slot = daily.setdefault(dkey, {"weather": "", "precipitation": None, "temp_min": None, "temp_max": None}) 81 # 天気 (weathers) 82 weathers = area0.get("weathers") or [] 83 if i < len(weathers) and not slot["weather"]: 84 slot["weather"] = normalize_text(str(weathers[i])) 85 # 降水確率 (pops) 86 pops = area0.get("pops") or [] 87 if i < len(pops) and slot["precipitation"] is None: 88 v = normalize_text(str(pops[i])) 89 slot["precipitation"] = v or None 90 # 気温 (temps: [最低, 最高] の交互ペア or tempsMin/tempsMax) 91 temps_min = area0.get("tempsMin") or [] 92 temps_max = area0.get("tempsMax") or [] 93 temps = area0.get("temps") or [] 94 if i < len(temps_min) and slot["temp_min"] is None: 95 v = normalize_text(str(temps_min[i])) 96 slot["temp_min"] = v or None 97 if i < len(temps_max) and slot["temp_max"] is None: 98 v = normalize_text(str(temps_max[i])) 99 slot["temp_max"] = v or None 100 # temps のみの場合: 偶数index=最低, 奇数index=最高の日次ペア 101 if temps and slot["temp_min"] is None and slot["temp_max"] is None: 102 day_idx = sum(1 for k in daily if k < dkey) 103 lo, hi = day_idx * 2, day_idx * 2 + 1 104 if lo < len(temps): 105 slot["temp_min"] = normalize_text(str(temps[lo])) or None 106 if hi < len(temps): 107 slot["temp_max"] = normalize_text(str(temps[hi])) or None 108 for dkey in sorted(daily): 109 slot = daily[dkey] 110 forecasts.append( 111 WeatherEntry( 112 date=dkey, 113 weather=slot["weather"], 114 temp_min=slot["temp_min"], 115 temp_max=slot["temp_max"], 116 precipitation=slot["precipitation"], 117 ) 118 ) 119 120 warnings: list[WeatherWarning] = [] 121 if isinstance(warning_data, dict): 122 # 警報種別キー (例: "alert", "warning") を順に走査 123 for kind, items in warning_data.items(): 124 if not isinstance(items, list): 125 continue 126 for entry in items: 127 if not isinstance(entry, dict): 128 continue 129 area_codes: list[str] = [str(c) for c in (entry.get("areaCodes") or [])] 130 headline: str = normalize_text(str(entry.get("headlineText", ""))) 131 if area_codes or headline: 132 warnings.append(WeatherWarning(type=str(kind), areas=area_codes, headline=headline)) 133 134 publishing_office: str = "" 135 report_datetime: str = "" 136 # v2 形式: forecast_data = {"data": [block0, block1...]} — block0 に発表情報がある 137 raw_blocks = forecast_data.get("data") if isinstance(forecast_data, dict) else None 138 if isinstance(raw_blocks, list) and raw_blocks and isinstance(raw_blocks[0], dict): 139 publishing_office = normalize_text(str(raw_blocks[0].get("publishingOffice", ""))) 140 report_datetime = normalize_text(str(raw_blocks[0].get("reportDatetime", ""))) 141 elif isinstance(forecast_data, dict) and "publishingOffice" in forecast_data: 142 publishing_office = normalize_text(str(forecast_data.get("publishingOffice", ""))) 143 report_datetime = normalize_text(str(forecast_data.get("reportDatetime", ""))) 144 145 return WeatherForecast( 146 area_code=code, 147 area_name=AREA_NAME_MAP.get(code, code), 148 publishing_office=publishing_office, 149 report_datetime=report_datetime, 150 forecasts=forecasts, 151 warnings=warnings, 152 )

1"""厚生労働省医療施設公開 CSV ソース。 2 3公式: https://www.mhlw.go.jp/stf/seisakunitsuite/bunya/kenkou_iryou/iryou/ 4本 MVP では都道府県別に公開されている CSV を取得する想定。 5テストではモックで CSV 文字列を注入する。 6""" 7from __future__ import annotations 8 9from typing import Any 10 11import httpx 12 13from ..models import MedicalFacility, MedicalSearchResult 14from ..normalizer import coerce_int, normalize_phone, normalize_text, parse_csv_rows 15from .base import BaseSource 16 17 18class MHLWMedicalSource(BaseSource): 19 """厚生労働省医療施設 CSV の非同期クライアント。""" 20 21 source_name: str = "mhlw" 22 23 def __init__( 24 self, 25 client: httpx.AsyncClient, 26 base_url: str = "https://www.mhlw.go.jp/content/", 27 ) -> None: 28 super().__init__(client, base_url) 29 # メモリ内 CSV インデックス 30 self._index: list[dict[str, str]] = [] 31 32 async def health_check(self) -> bool: 33 """接続確認。""" 34 try: 35 await self.client.get(self.base_url) 36 return True 37 except httpx.HTTPError: 38 return False 39 40 async def load_csv(self, csv_path: str) -> int: 41 """CSV を取得してインデックスへ読み込む。""" 42 url: str = f"{self.base_url}/{csv_path.lstrip('/')}" 43 resp = await self.client.get(url) 44 resp.raise_for_status() 45 self._index = parse_csv_rows(resp.text) 46 return len(self._index) 47 48 def load_csv_text(self, csv_text: str) -> int: 49 """テスト用: CSV テキストを直接読み込む。""" 50 self._index = parse_csv_rows(csv_text) 51 return len(self._index) 52 53 async def search_by_prefecture(self, prefecture: str, limit: int = 100) -> MedicalSearchResult: 54 """都道府県名で施設を絞り込む。""" 55 pref: str = normalize_text(prefecture) 56 results: list[MedicalFacility] = [] 57 for row in self._index: 58 row_pref: str = normalize_text( 59 row.get("prefecture", "") or row.get("都道府県", "") or row.get("都道府県名", "") 60 ) 61 if pref and pref not in row_pref: 62 continue 63 facility_id: str = normalize_text( 64 row.get("facility_id", "") or row.get("施設ID", "") or row.get("医療機関コード", "") 65 ) 66 name: str = normalize_text(row.get("name", "") or row.get("施設名", "") or row.get("医療機関名称", "")) 67 if not facility_id or not name: 68 continue 69 city: str = normalize_text(row.get("city", "") or row.get("市区町村", "") or row.get("市区町村名", "")) 70 address: str = normalize_text(row.get("address", "") or row.get("住所", "")) 71 phone: str = normalize_phone(row.get("phone", "") or row.get("電話番号", "")) 72 bed: int = coerce_int(row.get("bed_count", "") or row.get("病床数", ""), default=0) 73 results.append( 74 MedicalFacility( 75 facility_id=facility_id, 76 name=name, 77 prefecture=row_pref, 78 city=city, 79 address=address, 80 phone=phone, 81 bed_count=bed, 82 ) 83 ) 84 if len(results) >= limit: 85 break 86 return MedicalSearchResult(prefecture=prefecture, count=len(results), items=results)

1"""国税庁法人番号公表サイトソース。 2 3公式: https://www.houjin-bangou.nta.go.jp/ 4公式 API は存在しないため、全国一括ダウンロード (CSV) を取得・部分パースする想定。 5本モジュールはクライアントに httpx.AsyncClient を取り、 6検索時はメモリ上の CSV インデックスをスキャンする。 7 8実運用: ZIP を取得して unzip → CSV を SQLite 化 → メモリ読み込み。 9本 MVP ではソースクライアントを抽象化し、テストでは CSV を直接注入する。 10""" 11from __future__ import annotations 12 13from typing import Any 14 15import httpx 16 17from ..models import CorporateItem, CorporateSearchResult 18from ..normalizer import ( 19 normalize_corporate_number, 20 normalize_text, 21 parse_csv_rows, 22) 23from .base import BaseSource 24 25 26class NTACorporateSource(BaseSource): 27 """国税庁法人番号公表ソース。""" 28 29 source_name: str = "nta" 30 31 def __init__( 32 self, 33 client: httpx.AsyncClient, 34 base_url: str = "https://www.houjin-bangou.nta.go.jp/download/", 35 ) -> None: 36 super().__init__(client, base_url) 37 # メモリ内 CSV インデックス (load_csv_index() で上書きされる) 38 self._index: list[dict[str, str]] = [] 39 40 async def health_check(self) -> bool: 41 """接続確認 (軽量 GET)。失敗時は False を返す。""" 42 try: 43 resp = await self.client.get(self.base_url) 44 resp.raise_for_status() 45 return True 46 except httpx.HTTPError: 47 return False 48 49 async def load_csv_index(self, csv_url: str | None = None) -> int: 50 """CSV ダウンロードしてメモリインデックスへ読み込む。""" 51 target: str = csv_url or self.base_url 52 resp = await self.client.get(target) 53 resp.raise_for_status() 54 text: str = resp.text 55 self._index = parse_csv_rows(text) 56 return len(self._index) 57 58 def load_csv_text(self, csv_text: str) -> int: 59 """テスト用: CSV テキストを直接読み込んでインデックスを構築する。""" 60 self._index = parse_csv_rows(csv_text) 61 return len(self._index) 62 63 async def search(self, query: str, limit: int = 20) -> CorporateSearchResult: 64 """インデックスを走査して法人名/番号で部分一致検索する。""" 65 q: str = normalize_text(query) 66 results: list[CorporateItem] = [] 67 for row in self._index: 68 name: str = normalize_text(row.get("name", "") or row.get("商号又は名称", "")) 69 num: str = normalize_text(row.get("corporate_number", "") or row.get("法人番号", "")) 70 if not q or q in name or q in num: 71 corp_num: str = normalize_corporate_number(num) or num 72 if not corp_num: 73 continue 74 results.append( 75 CorporateItem( 76 corporate_number=corp_num, 77 name=name, 78 prefecture=normalize_text(row.get("prefecture", "") or row.get("都道府県名", "")), 79 city=normalize_text(row.get("city", "") or row.get("市区町村名", "")), 80 address_remainder=normalize_text( 81 row.get("address_remainder", "") or row.get("所在地", "") 82 ), 83 ) 84 ) 85 if len(results) >= limit: 86 break 87 return CorporateSearchResult(query=query, count=len(results), items=results) 88 89 def count(self) -> int: 90 """現在のインデックス件数を返す。""" 91 return len(self._index) 92 93 def get_raw(self, index: int) -> dict[str, str] | None: 94 """テスト/内部利用: インデックスから生 dict を1件取り出す。""" 95 if 0 <= index < len(self._index): 96 return self._index[index] 97 return None