Use ruff rules COM, F, I, RUF, UP (#17)

* Use pyupgrade (UP) rule

* Use pyflakes (F) rule

* Use isort (I) rule

* Use ruff-specific (RUF) rules

* Use flake8-commas (COM) rule

* Fix UP043 Unnecessary default type arguments

src/geo_assistant/agent/graph.py

@@ -1,12 +1,13 @@
 import datetime
 
-from langgraph.checkpoint.memory import InMemorySaver
 from langchain.agents import create_agent
-from geo_assistant.agent.state import GeoAssistantState
+from langgraph.checkpoint.memory import InMemorySaver
+
 from geo_assistant.agent.llms import llm
+from geo_assistant.agent.state import GeoAssistantState
+from geo_assistant.tools.buffer import get_search_area
 from geo_assistant.tools.naip import fetch_naip_img
 from geo_assistant.tools.overture import get_place
-from geo_assistant.tools.buffer import get_search_area
 from geo_assistant.tools.summarize import summarize_sat_img
 
 SYSTEM_PROMPT = """
@@ -36,7 +37,7 @@ async def create_graph():
             summarize_sat_img,
         ],
         system_prompt=SYSTEM_PROMPT.format(
-            now=datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+            now=datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
         ),
         state_schema=GeoAssistantState,
         checkpointer=checkpointer,

src/geo_assistant/agent/llms.py

@@ -1,6 +1,6 @@
 import os
-from dotenv import load_dotenv
 
+from dotenv import load_dotenv
 from langchain_ollama import ChatOllama
 
 # Load environment variables from env file

src/geo_assistant/agent/state.py

@@ -1,6 +1,7 @@
-from langchain.agents import AgentState
+from typing import NotRequired
+
 from geojson_pydantic import Feature
-from typing_extensions import NotRequired
+from langchain.agents import AgentState
 from pydantic import Field
 
 
@@ -8,5 +9,6 @@ class GeoAssistantState(AgentState):
     place: NotRequired[Feature | None] = None
     search_area: NotRequired[Feature | None] = None
     naip_png_path: NotRequired[str | None] = Field(
-        default=None, description="Path to the saved NAIP RGB PNG image"
+        default=None,
+        description="Path to the saved NAIP RGB PNG image",
     )

src/geo_assistant/api/app.py

@@ -1,11 +1,12 @@
 import json
+import logging
+from collections.abc import AsyncGenerator
 from contextlib import aclosing, asynccontextmanager
-from typing import Any, AsyncGenerator, Dict
+from typing import Any
 
 from fastapi import FastAPI, Request
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import StreamingResponse
-import logging
 from pydantic import UUID4
 
 from geo_assistant.agent.graph import create_graph
@@ -43,11 +44,11 @@ async def stream_chat(
     thread_id: UUID4,
     chatbot: Any,
     request: Request,
-) -> AsyncGenerator[bytes, None]:
-    config: Dict[str, Any] = {
+) -> AsyncGenerator[bytes]:
+    config: dict[str, Any] = {
         "configurable": {
             "thread_id": str(thread_id),
-        }
+        },
     }
 
     state_updates = {}
@@ -69,7 +70,7 @@ async def stream_chat(
                     {
                         "content": f"Manually selected data for field {key}: {description}",
                         "type": "human",
-                    }
+                    },
                 )
 
     # Add UI messages to the existing messages if they exist

src/geo_assistant/api/schemas/chat.py

@@ -1,4 +1,5 @@
 from pydantic import BaseModel
+
 from geo_assistant.agent.state import GeoAssistantState
 
 

src/geo_assistant/frontend/app.py

@@ -2,10 +2,10 @@ import json
 import os
 import uuid
 
+import folium
 import httpx
 import streamlit as st
 import streamlit.components.v1 as components
-import folium
 from dotenv import load_dotenv
 
 # Load environment variables from .env file
@@ -137,7 +137,10 @@ def stream_chat(user_message: str):
                 # Fit map to bounds if we have coordinates
                 if all_lons and all_lats:
                     m.fit_bounds(
-                        [[min(all_lats), min(all_lons)], [max(all_lats), max(all_lons)]]
+                        [
+                            [min(all_lats), min(all_lons)],
+                            [max(all_lats), max(all_lons)],
+                        ],
                     )
 
                 # Display the map

src/geo_assistant/tools/buffer.py

@@ -1,12 +1,14 @@
+from typing import Annotated
+
 import geopandas as gpd
-from langgraph.types import Command
-from langgraph.prebuilt import InjectedState
-from langchain_core.tools.base import InjectedToolCallId
+from geojson_pydantic import Feature
 from langchain_core.messages import ToolMessage
 from langchain_core.tools import tool
-from typing import Annotated
+from langchain_core.tools.base import InjectedToolCallId
+from langgraph.prebuilt import InjectedState
+from langgraph.types import Command
+
 from geo_assistant.agent.state import GeoAssistantState
-from geojson_pydantic import Feature
 
 
 @tool
@@ -26,9 +28,9 @@ async def get_search_area(
                     ToolMessage(
                         content="No place defined in the agent state to create a search area around.",
                         tool_call_id=tool_call_id,
-                    )
+                    ),
                 ],
-            }
+            },
         )
 
     # Convert GeoJSON feature to GeoDataFrame
@@ -38,7 +40,7 @@ async def get_search_area(
     gdf_m = gdf.to_crs(epsg=3857)  # latlon to Web Mercator for meter-based buffering
 
     gdf_m["geometry"] = gdf_m["geometry"].buffer(
-        buffer_size_km * 1000
+        buffer_size_km * 1000,
     )  # Buffer in meters
     gdf = gdf_m.to_crs(epsg=4326)  # Back to WGS84
 
@@ -46,7 +48,7 @@ async def get_search_area(
     if len(gdf) != 1:
         raise ValueError(
             f"{len(gdf)} features found after buffer operation, should be just 1. "
-            "Was a Multi-Point/LineString/Polygon geometry passed in?"
+            "Was a Multi-Point/LineString/Polygon geometry passed in?",
         )
     buffer_feature = Feature(
         type="Feature",
@@ -61,7 +63,7 @@ async def get_search_area(
                 ToolMessage(
                     content=f"Created search area geometry buffer of {buffer_size_km} km around the place.",
                     tool_call_id=tool_call_id,
-                )
+                ),
             ],
-        }
+        },
     )

src/geo_assistant/tools/naip.py

@@ -1,19 +1,18 @@
 # tools/naip_mpc_tools.py
-from typing import Dict, Any, Optional, Annotated
-from pathlib import Path
-
 from concurrent.futures import ThreadPoolExecutor
-import numpy as np
-import xarray as xr
-import matplotlib.pyplot as plt
-from langchain_core.tools import tool
-from pystac_client import Client
-from odc.stac import stac_load
-from langgraph.types import Command
-from langchain_core.messages import ToolMessage
-from langchain_core.tools.base import InjectedToolCallId
+from pathlib import Path
+from typing import Annotated, Any
 
 import dotenv
+import matplotlib.pyplot as plt
+import numpy as np
+import xarray as xr
+from langchain_core.messages import ToolMessage
+from langchain_core.tools import tool
+from langchain_core.tools.base import InjectedToolCallId
+from langgraph.types import Command
+from odc.stac import stac_load
+from pystac_client import Client
 
 dotenv.load_dotenv()
 
@@ -23,10 +22,10 @@ E84_STAC_URL = "https://earth-search.aws.element84.com/v1"
 
 @tool("fetch_naip_img")
 async def fetch_naip_img(
-    aoi_geojson: Dict[str, Any],
+    aoi_geojson: dict[str, Any],
     start_date: str,
     end_date: str,
-    tool_call_id: Annotated[Optional[str], InjectedToolCallId] = None,
+    tool_call_id: Annotated[str | None, InjectedToolCallId] = None,
 ) -> Command:
     """
     Query Microsoft Planetary Computer for NAIP imagery intersecting an AOI and
@@ -56,10 +55,10 @@ async def fetch_naip_img(
                     ToolMessage(
                         content="No NAIP imagery found for the specified area and date range.",
                         tool_call_id=tool_call_id,
-                    )
+                    ),
                 ],
                 "naip_png_path": None,
-            }
+            },
         )
 
         # --- 2. Load as xarray cube with odc.stac ---
@@ -81,14 +80,14 @@ async def fetch_naip_img(
                     ToolMessage(
                         content="Unable to load NAIP RGB image, dataset has no time dimension",
                         tool_call_id=tool_call_id,
-                    )
+                    ),
                 ],
                 "naip_png_path": None,
-            }
+            },
         )
 
     # --- 3. Build an RGB composite from the cube ---
-    # For the PNG, we’ll just use the first time slice (you can swap in “latest”
+    # For the PNG, we'll just use the first time slice (you can swap in “latest”
     # or a temporal reduction if you prefer).
     red = ds["Red"].isel(time=0)
     green = ds["Green"].isel(time=0)
@@ -121,8 +120,8 @@ async def fetch_naip_img(
                 ToolMessage(
                     content=f"NAIP RGB image saved to {out_path.as_posix()}",
                     tool_call_id=tool_call_id,
-                )
+                ),
             ],
             "naip_png_path": out_path.as_posix(),
-        }
+        },
     )

src/geo_assistant/tools/overture.py

@@ -4,11 +4,11 @@ from typing import Annotated
 
 import duckdb
 from dotenv import load_dotenv
+from geojson_pydantic import Feature
 from langchain_core.messages import ToolMessage
 from langchain_core.tools import tool
 from langchain_core.tools.base import InjectedToolCallId
 from langgraph.types import Command
-from geojson_pydantic import Feature
 
 # Load environment variables
 load_dotenv()
@@ -34,7 +34,8 @@ def create_database_connection():
 
 @tool
 async def get_place(
-    place_name: str, tool_call_id: Annotated[str, InjectedToolCallId] = ""
+    place_name: str,
+    tool_call_id: Annotated[str, InjectedToolCallId] = "",
 ) -> Command:
     """Get place location from Overture Maps based on user input place name."""
 
@@ -65,7 +66,7 @@ async def get_place(
       WHERE jaro_winkler_similarity(LOWER(names.primary), LOWER('{place_name}')) > 0.5
       ORDER BY similarity_score DESC
       LIMIT 1;
-  """
+  """,
     ).fetchall()
 
     db_connection.close()
@@ -89,7 +90,7 @@ async def get_place(
                 ToolMessage(
                     content=f"Found place with Overture name: {location_results[0][2]} based on user query. Socials: {location_results[0][4]}",
                     tool_call_id=tool_call_id,
-                )
+                ),
             ],
         },
     )

src/geo_assistant/tools/summarize.py

@@ -1,14 +1,14 @@
 """Tools for summarizing satellite images using LLM-based analysis."""
 
 import os
-from typing import Annotated, Optional
-import dspy
-from langchain_core.tools import tool
-from langgraph.types import Command
-from langchain_core.messages import ToolMessage
-from langchain_core.tools.base import InjectedToolCallId
+from typing import Annotated
 
 import dotenv
+import dspy
+from langchain_core.messages import ToolMessage
+from langchain_core.tools import tool
+from langchain_core.tools.base import InjectedToolCallId
+from langgraph.types import Command
 
 dotenv.load_dotenv()
 
@@ -68,7 +68,7 @@ _SUMMARIZER_AGENT = SatImgSummaryAgent()
 @tool
 async def summarize_sat_img(
     img_url: str,
-    tool_call_id: Annotated[Optional[str], InjectedToolCallId] = None,
+    tool_call_id: Annotated[str | None, InjectedToolCallId] = None,
 ) -> Command:
     """Summarize the contents of a satellite image using an LLM.
 
@@ -96,7 +96,7 @@ async def summarize_sat_img(
                     content=message_content,
                     artifact=artifact,
                     tool_call_id=tool_call_id,
-                )
-            ]
-        }
+                ),
+            ],
+        },
     )