ruffによる指摘事項修正

Author: massongit

create_env.py

@@ -8,9 +8,7 @@
 def create_table() -> None:
     """テーブルを作成する"""
 
-    with open(
-        "postgres/docker-entrypoint-initdb.d/02_init.sql", encoding="UTF-8"
-    ) as init_sql:
+    with open("postgres/docker-entrypoint-initdb.d/02_init.sql", encoding="UTF-8") as init_sql:
         sql = ""
         for line in init_sql.readlines():
             sql += line

library/chat_gpt.py

@@ -21,7 +21,9 @@ def chat_gpt(message: str) -> Optional[str]:
         )
     except RateLimitError as e:
         if e.code == "insufficient_quota":
-            return "栄養が足りなくて頭がうまく働かないっぽ......。このコマンドを使いたい場合は飼い主に相談してくれっぽ。"
+            return (
+                "栄養が足りなくて頭がうまく働かないっぽ......。このコマンドを使いたい場合は飼い主に相談してくれっぽ。"
+            )
         else:
             raise e
 

library/clientclass.py

@@ -3,6 +3,7 @@
 """
 clientに使うclass
 """
+
 import os
 from abc import ABCMeta, abstractmethod
 
@@ -64,9 +65,7 @@ def post(self, message):
 
     def upload(self, file, filename):
         """ファイルを投稿する"""
-        self.client.files_upload_v2(
-            channel=self.slack_channel, file=file, filename=filename
-        )
+        self.client.files_upload_v2(channel=self.slack_channel, file=file, filename=filename)
 
     def get_send_user(self):
         """botを呼び出したユーザーを返す"""
@@ -126,9 +125,7 @@ def post(self, message):
 
     def upload(self, file, filename):
         """ファイルを投稿する"""
-        self.client.loop.create_task(
-            self.message.channel.send(file=discord.File(file, filename=filename))
-        )
+        self.client.loop.create_task(self.message.channel.send(file=discord.File(file, filename=filename)))
 
     def get_send_user(self):
         """botを呼び出したユーザーを返す"""

library/earthquake.py

@@ -52,8 +52,7 @@ def generate_map_img(
     """
 
     layers: List[Layer] = [
-        LineTrace(coords=[get_circle(lat, lng, d * 1000)], color=(100, 100, 100, 255))
-        for d in range(10, 60, 10)
+        LineTrace(coords=[get_circle(lat, lng, d * 1000)], color=(100, 100, 100, 255)) for d in range(10, 60, 10)
     ]
     layers.append(
         MarkerTrace(

library/geo.py

@@ -42,9 +42,7 @@ def get_yahoo_geo_data(place: str) -> Optional[Dict[str, str]]:
     else:
         url = "https://map.yahooapis.jp/geocode/V1/geoCoder"
 
-    res = requests.get(
-        url, {"appid": conf.YAHOO_API_TOKEN, "query": place, "output": "json"}
-    )
+    res = requests.get(url, {"appid": conf.YAHOO_API_TOKEN, "query": place, "output": "json"})
 
     if res.status_code != 200:
         return None
@@ -80,9 +78,7 @@ def get_gsi_geo_data(place: str) -> Optional[Dict[str, str]]:
     """
 
     place = unicodedata.normalize("NFKC", place)
-    res = requests.get(
-        "https://msearch.gsi.go.jp/address-search/AddressSearch", {"q": place}
-    )
+    res = requests.get("https://msearch.gsi.go.jp/address-search/AddressSearch", {"q": place})
 
     if res.status_code != 200:
         return None
@@ -91,9 +87,7 @@ def get_gsi_geo_data(place: str) -> Optional[Dict[str, str]]:
     partial_match_candidates = []
 
     for entry in res.json():
-        res_place = unicodedata.normalize(
-            "NFKC", entry.get("properties", {}).get("title", "")
-        )
+        res_place = unicodedata.normalize("NFKC", entry.get("properties", {}).get("title", ""))
         lon, lat = entry.get("geometry", {}).get("coordinates", [None, None])
         if lon is None or lat is None:
             continue

library/hatomap.py

@@ -54,25 +54,13 @@ def from_geocoord(cls, geocoord: GeoCoord, zoom: int) -> WebMercatorPixelCoord:
             256 * (1 << zoom) * (geocoord.lng + 180) / 360,
             256
             * (1 << zoom)
-            * (
-                0.5
-                - math.log(math.tan(math.pi / 4 + geocoord.lat * math.pi / 180 / 2))
-                / (2 * math.pi)
-            ),
+            * (0.5 - math.log(math.tan(math.pi / 4 + geocoord.lat * math.pi / 180 / 2)) / (2 * math.pi)),
             zoom,
         )
 
     def to_geocoord(self) -> GeoCoord:
         lng = (360 * self.pixel_x) / (1 << self.zoom_level * 256) - 180
-        lat = (
-            math.asin(
-                math.tanh(
-                    math.pi * (1 - 2 * self.pixel_y / (1 << self.zoom_level * 256))
-                )
-            )
-            * 180
-            / math.pi
-        )
+        lat = math.asin(math.tanh(math.pi * (1 - 2 * self.pixel_y / (1 << self.zoom_level * 256)))) * 180 / math.pi
         return GeoCoord(lat, lng)
 
     def belongs_tile(self) -> WebMercatorTilePixel:
@@ -103,12 +91,8 @@ def __post_init__(self):
 
     def covered_tiles(self) -> Tuple[WebMercatorTilePixel, WebMercatorTilePixel]:
         return (
-            WebMercatorPixelCoord(
-                self.pixel_x_west, self.pixel_y_north, self.zoom
-            ).belongs_tile(),
-            WebMercatorPixelCoord(
-                self.pixel_x_east, self.pixel_y_south, self.zoom
-            ).belongs_tile(),
+            WebMercatorPixelCoord(self.pixel_x_west, self.pixel_y_north, self.zoom).belongs_tile(),
+            WebMercatorPixelCoord(self.pixel_x_east, self.pixel_y_south, self.zoom).belongs_tile(),
         )
 
     def geocoord2pixel(self, geocoord: GeoCoord) -> Tuple[int, int]:
@@ -122,17 +106,10 @@ def geocoords2pixel_ndarray(self, geocoords: np.ndarray) -> np.ndarray:
         return (
             np.array(
                 [
-                    256 * (1 << self.zoom) * (geocoords[..., 1] + 180) / 360
-                    - self.pixel_x_west,
+                    256 * (1 << self.zoom) * (geocoords[..., 1] + 180) / 360 - self.pixel_x_west,
                     256
                     * (1 << self.zoom)
-                    * (
-                        0.5
-                        - np.log(
-                            np.tan(np.pi / 4 + geocoords[..., 0] * np.pi / 180 / 2)
-                        )
-                        / (2 * np.pi)
-                    )
+                    * (0.5 - np.log(np.tan(np.pi / 4 + geocoords[..., 0] * np.pi / 180 / 2)) / (2 * np.pi))
                     - self.pixel_y_north,
                 ]
             )
@@ -175,11 +152,7 @@ class RasterTileServer:
     def _get_image_content(url):
         return cv2.imdecode(
             np.asarray(
-                bytearray(
-                    requests.get(
-                        url, headers={"user-agent": f"hato-bot/{VERSION}"}
-                    ).content
-                ),
+                bytearray(requests.get(url, headers={"user-agent": f"hato-bot/{VERSION}"}).content),
                 dtype=np.uint8,
             ),
             -1,
@@ -191,22 +164,15 @@ def request(self, bbox: WebMercatorPixelBBox) -> np.ndarray:
         request_urls = []
         for x in range(tl_tilepx.tile.tile_x, rb_tilepx.tile.tile_x + 1):
             for y in range(tl_tilepx.tile.tile_y, rb_tilepx.tile.tile_y + 1):
-                request_urls.append(
-                    string.Template(self.url).safe_substitute(
-                        {"x": x, "y": y, "z": bbox.zoom}
-                    )
-                )
+                request_urls.append(string.Template(self.url).safe_substitute({"x": x, "y": y, "z": bbox.zoom}))
         with Pool(16) as p:
             imgs = list(p.imap(self._get_image_content, request_urls))
 
         tile_width_cnt = rb_tilepx.tile.tile_x + 1 - tl_tilepx.tile.tile_x
         tile_height_cnt = rb_tilepx.tile.tile_y + 1 - tl_tilepx.tile.tile_y
 
         concated = np.concatenate(
-            [
-                np.concatenate(imgs[i : i + tile_height_cnt], axis=0)
-                for i in range(0, len(imgs), tile_height_cnt)
-            ],
+            [np.concatenate(imgs[i : i + tile_height_cnt], axis=0) for i in range(0, len(imgs), tile_height_cnt)],
             axis=1,
         )
 
@@ -220,7 +186,6 @@ def request(self, bbox: WebMercatorPixelBBox) -> np.ndarray:
 
 @dataclass
 class Layer(metaclass=ABCMeta):
-
     @abstractmethod
     def get_image(self, bbox: WebMercatorPixelBBox) -> np.ndarray:
         pass
@@ -266,12 +231,7 @@ def get_image(self, bbox: WebMercatorPixelBBox) -> np.ndarray:
 
         px_coords = bbox.geocoords2pixel_ndarray(coords)
 
-        symbols = {
-            "thunder": np.array(
-                [[1, -3], [-0, -0.5], [2, -0.5], [-1, 3], [0, 0.5], [-2, 0.5]]
-            )
-            / 6
-        }
+        symbols = {"thunder": np.array([[1, -3], [-0, -0.5], [2, -0.5], [-1, 3], [0, 0.5], [-2, 0.5]]) / 6}
         if self.symbol == "circle":
             for c in px_coords:
                 print(c)
@@ -316,8 +276,7 @@ def get_image(self, bbox: WebMercatorPixelBBox) -> np.ndarray:
         elif self.symbol in symbols.keys():
             symbol_coords = symbols[self.symbol]
             px_coords = (
-                np.repeat(px_coords[:, np.newaxis, :], symbol_coords.shape[0], axis=1)
-                + symbol_coords * self.size
+                np.repeat(px_coords[:, np.newaxis, :], symbol_coords.shape[0], axis=1) + symbol_coords * self.size
             )
             px_coords = px_coords.astype(np.int32)
             for c in px_coords:
@@ -364,14 +323,10 @@ def get_image(self, bbox: WebMercatorPixelBBox) -> np.ndarray:
         layer_img = np.array(RasterTileServer(url).request(bbox), dtype=np.float32)
 
         if self.brightness != 1.0 or self.chroma != 1.0:
-            img_hsv = np.array(
-                cv2.cvtColor(layer_img, cv2.COLOR_BGR2HSV), dtype=np.float32
-            )
+            img_hsv = np.array(cv2.cvtColor(layer_img, cv2.COLOR_BGR2HSV), dtype=np.float32)
             img_hsv[..., 1] = img_hsv[..., 1] * self.brightness
             img_hsv[..., 2] = img_hsv[..., 2] * self.chroma
-            layer_img = np.array(
-                cv2.cvtColor(img_hsv, cv2.COLOR_HSV2BGR), dtype=np.float32
-            )
+            layer_img = np.array(cv2.cvtColor(img_hsv, cv2.COLOR_HSV2BGR), dtype=np.float32)
 
         if self.opacity != 1.0:
             layer_img[layer_img[..., 3] != 0, 3] = int(round(self.opacity * 256))
@@ -409,9 +364,7 @@ class HatoMap:
     layers: Optional[List[Layer]] = None
     title: Optional[str] = None
 
-    def update_layout(
-        self, mapbox: Optional[MapBox] = None, layers: Optional[List[Layer]] = None
-    ) -> None:
+    def update_layout(self, mapbox: Optional[MapBox] = None, layers: Optional[List[Layer]] = None) -> None:
         if mapbox is not None:
             self.mapbox = mapbox
         if layers is not None:
@@ -475,9 +428,9 @@ def get_image(self, height: int, width: int) -> np.ndarray:
             if body_img.shape == none_body_img_shape:
                 body_img = layer_img[..., :3]
             else:
-                body_img = body_img[..., :3] * (
-                    1 - layer_img[..., 3:] / 255
-                ) + layer_img[..., :3] * (layer_img[..., 3:] / 255)
+                body_img = body_img[..., :3] * (1 - layer_img[..., 3:] / 255) + layer_img[..., :3] * (
+                    layer_img[..., 3:] / 255
+                )
 
         img = np.zeros((height, width, 3), np.uint8)
         img.fill(255)
@@ -501,9 +454,7 @@ def get_circle(lat: float, lng: float, radius: float) -> np.ndarray:
     earth_e_sq = (2 * earth_f - 1) / earth_f**2
     c = 1 - (earth_e_sq * math.sin(lat) ** 2)
     meter_1deg_lat = math.pi * earth_radius * (1 - earth_e_sq) / (180 * c**1.5)
-    meter_1deg_lng = (
-        math.pi * earth_radius * math.cos(lat * math.pi / 180) / (180 * math.sqrt(c))
-    )
+    meter_1deg_lng = math.pi * earth_radius * math.cos(lat * math.pi / 180) / (180 * math.sqrt(c))
     lats = np.sin(np.radians(np.arange(0, 361, 1))) * radius / meter_1deg_lat + lat
     lngs = np.cos(np.radians(np.arange(0, 361, 1))) * radius / meter_1deg_lng + lng
     return np.array([lats, lngs]).T

library/jma_amedas.py

@@ -15,9 +15,7 @@ class Place:
 
 def get_jma_amedas(lat: float, lon: float) -> Optional[Dict]:
     nearest_place: Optional[Place] = None
-    place_res = requests.get(
-        "https://www.jma.go.jp/bosai/amedas/const/amedastable.json"
-    )
+    place_res = requests.get("https://www.jma.go.jp/bosai/amedas/const/amedastable.json")
 
     if place_res.status_code != 200:
         return None
@@ -32,17 +30,13 @@ def get_jma_amedas(lat: float, lon: float) -> Optional[Dict]:
     if nearest_place is None:
         return None
 
-    latest_datetime_res = requests.get(
-        "https://www.jma.go.jp/bosai/amedas/data/latest_time.txt"
-    )
+    latest_datetime_res = requests.get("https://www.jma.go.jp/bosai/amedas/data/latest_time.txt")
 
     if latest_datetime_res.status_code != 200:
         return None
 
     latest_datetime = datetime.datetime.fromisoformat(latest_datetime_res.text)
-    amedas_url = latest_datetime.strftime(
-        "https://www.jma.go.jp/bosai/amedas/data/map/%Y%m%d%H%M%S.json"
-    )
+    amedas_url = latest_datetime.strftime("https://www.jma.go.jp/bosai/amedas/data/map/%Y%m%d%H%M%S.json")
     amedas_res = requests.get(amedas_url)
 
     if amedas_res.status_code != 200:

library/jma_amesh.py

@@ -3,6 +3,7 @@
 """
 jma_amesh
 """
+
 import datetime
 import json
 from dataclasses import dataclass
@@ -60,13 +61,7 @@ def get_latest_timestamps() -> dict:
         [
             (
                 e,
-                max(
-                    [
-                        i.basetime
-                        for i in timejson
-                        if i.basetime == i.validtime and e in i.elements
-                    ]
-                ),
+                max([i.basetime for i in timejson if i.basetime == i.validtime and e in i.elements]),
             )
             for e in elements
         ]
@@ -90,7 +85,9 @@ def get_jma_image_server(timestamp: str) -> str:
 
 def get_liden(timestamp: str) -> List[Tuple[float, float, int]]:
     """気象庁落雷JSONを取得する"""
-    liden_json_url = f"https://www.jma.go.jp/bosai/jmatile/data/nowc/{timestamp}/none/{timestamp}/surf/liden/data.geojson"  # noqa: E501
+    liden_json_url = (
+        f"https://www.jma.go.jp/bosai/jmatile/data/nowc/{timestamp}/none/{timestamp}/surf/liden/data.geojson"  # noqa: E501
+    )
     response = requests.get(liden_json_url)
 
     if response.status_code == 200:
@@ -105,23 +102,16 @@ def get_liden(timestamp: str) -> List[Tuple[float, float, int]]:
     return [(0.0, 0.0, 0)]
 
 
-def jma_amesh(
-    lat: float, lng: float, zoom: int, around_tiles: int
-) -> Optional[Image.Image]:
+def jma_amesh(lat: float, lng: float, zoom: int, around_tiles: int) -> Optional[Image.Image]:
     """
     気象庁雨雲レーダーとOpenStreetMap画像を取得して結合する
     Usage: jma_amesh(lat=37, lng=139, zoom=8, around_tiles=2).save('res2.png')
     """
 
     jma_timestamp = get_latest_timestamps()
-    layers: List[Layer] = [
-        RasterLayer(
-            url=get_jma_image_server(jma_timestamp["hrpns_nd"]), opacity=128 / 256
-        )
-    ]
+    layers: List[Layer] = [RasterLayer(url=get_jma_image_server(jma_timestamp["hrpns_nd"]), opacity=128 / 256)]
     layers += [
-        LineTrace(coords=[get_circle(lat, lng, d * 1000)], color=(100, 100, 100, 255))
-        for d in range(10, 60, 10)
+        LineTrace(coords=[get_circle(lat, lng, d * 1000)], color=(100, 100, 100, 255)) for d in range(10, 60, 10)
     ]
     layers.append(
         MarkerTrace(
@@ -134,7 +124,7 @@ def jma_amesh(
     )
     h = HatoMap(
         basemap="open-street-map-dim",
-        title=f'雨雲:{timestamp2jst(jma_timestamp["hrpns_nd"])} 雷:{timestamp2jst(jma_timestamp["liden"])}',
+        title=f"雨雲:{timestamp2jst(jma_timestamp['hrpns_nd'])} 雷:{timestamp2jst(jma_timestamp['liden'])}",
         mapbox=MapBox(center=GeoCoord(lat, lng), zoom=zoom),
         layers=layers,
     )