#!/usr/bin/env python3 """Anki flashcard generator for Warsaw streets. Generates Anki-compatible flashcard decks with maps showing individual Warsaw streets highlighted on a city map. Usage: python -m python_pkg.anki_decks.warsaw_streets.warsaw_streets_anki Output: Creates a self-contained .apkg file that can be directly imported into Anki. """ from __future__ import annotations import argparse import hashlib from io import BytesIO from pathlib import Path import random import sys from typing import TYPE_CHECKING, Any sys.path.insert(0, str(Path(__file__).parent.parent)) import genanki from geo_data import get_warsaw_streets import geopandas as gpd import matplotlib.pyplot as plt from shapely.geometry import MultiLineString if TYPE_CHECKING: from collections.abc import Sequence from matplotlib.figure import Figure # Minimum street length in meters to include MIN_STREET_LENGTH = 500 def get_unique_streets( gdf: gpd.GeoDataFrame, ) -> list[tuple[str, gpd.GeoDataFrame, float]]: """Group street segments by name and merge geometries. Args: gdf: GeoDataFrame with street segments. Returns: List of (name, GeoDataFrame, length_m) tuples, sorted by length (longest first). """ # Group by street name streets: dict[str, list[Any]] = {} for _, row in gdf.iterrows(): name = row["name"] if name and name != "Unknown": if name not in streets: streets[name] = [] streets[name].append(row.geometry) # Merge geometries and calculate length result = [] for name, geometries in streets.items(): merged = geometries[0] if len(geometries) == 1 else MultiLineString(geometries) # Create a GeoDataFrame for this street street_gdf = gpd.GeoDataFrame( [{"name": name, "geometry": merged}], crs="EPSG:4326" ) # Calculate length in meters (approximate) street_gdf_proj = street_gdf.to_crs("EPSG:2180") # Polish coordinate system length = street_gdf_proj.geometry.length.iloc[0] if length >= MIN_STREET_LENGTH: result.append((name, street_gdf, length)) # Sort by length (longest first) result.sort(key=lambda x: x[2], reverse=True) return result def load_street_data() -> ( tuple[list[tuple[str, gpd.GeoDataFrame, float]], gpd.GeoDataFrame] ): """Load Warsaw streets and boundary. Returns: Tuple of (streets list sorted by length, warsaw boundary GeoDataFrame). """ streets_gdf = get_warsaw_streets(min_length=MIN_STREET_LENGTH) streets = get_unique_streets(streets_gdf) # Load Warsaw districts for boundary (reuse from warsaw_districts) districts_path = ( Path(__file__).parent.parent / "warsaw_districts" / "warszawa-dzielnice.geojson" ) if districts_path.exists(): warsaw_gdf = gpd.read_file(districts_path) # Get just Warsaw boundary warsaw_boundary = warsaw_gdf[warsaw_gdf["name"] == "Warszawa"] if len(warsaw_boundary) == 0: # Dissolve all districts warsaw_boundary = gpd.GeoDataFrame( geometry=[warsaw_gdf.union_all()], crs=warsaw_gdf.crs ) else: msg = "Warsaw boundary data not found" raise FileNotFoundError(msg) return streets, warsaw_boundary # Color for highlighted street STREET_COLOR = "#E74C3C" # Red def create_street_map( street_gdf: gpd.GeoDataFrame, warsaw_boundary: gpd.GeoDataFrame, ) -> Figure: """Create a map showing Warsaw with one street highlighted. Args: street_name: Name of the street. street_gdf: GeoDataFrame with the street geometry. warsaw_boundary: GeoDataFrame with Warsaw boundary. Returns: A matplotlib Figure object. """ fig, ax = plt.subplots(figsize=(10, 10)) ax.set_aspect("equal") ax.axis("off") fig.patch.set_alpha(0) ax.patch.set_alpha(0) # Plot Warsaw as a plain gray shape warsaw_boundary.plot(ax=ax, color="#D5D8DC", alpha=0.6) warsaw_boundary.boundary.plot(ax=ax, color="#2C3E50", linewidth=2) # Plot the highlighted street street_gdf.plot(ax=ax, color=STREET_COLOR, linewidth=4, alpha=0.9) # Set bounds to Warsaw bounds = warsaw_boundary.total_bounds ax.set_xlim(bounds[0], bounds[2]) ax.set_ylim(bounds[1], bounds[3]) return fig def generate_street_image_bytes( street_gdf: gpd.GeoDataFrame, warsaw_boundary: gpd.GeoDataFrame, ) -> bytes: """Generate a street map image as bytes. Args: street_gdf: GeoDataFrame with the street geometry. warsaw_boundary: GeoDataFrame with Warsaw boundary. Returns: PNG image data as bytes. """ fig = create_street_map(street_gdf, warsaw_boundary) buf = BytesIO() fig.savefig(buf, format="png", bbox_inches="tight", dpi=150) plt.close(fig) buf.seek(0) return buf.read() def generate_anki_package( streets: list[tuple[str, gpd.GeoDataFrame, float]], warsaw_boundary: gpd.GeoDataFrame, deck_name: str = "Warsaw Streets", ) -> genanki.Package: """Generate Anki package for Warsaw streets. Args: streets: List of (name, GeoDataFrame, length) tuples, sorted by length. warsaw_boundary: GeoDataFrame with Warsaw boundary. deck_name: Name for the Anki deck. Returns: genanki.Package object. """ model_id_hash = hashlib.md5(f"warsaw_streets_{deck_name}".encode()) # noqa: S324 model_id = int(model_id_hash.hexdigest()[:8], 16) card_css = """ .card { font-family: Arial, sans-serif; font-size: 24px; text-align: center; color: #333; background-color: #fff; } .card.night_mode { color: #eee; background-color: #2f2f2f; } .map-container { display: flex; justify-content: center; align-items: center; min-height: 80vh; } .map-container img { max-width: 100%; max-height: 80vh; object-fit: contain; } .answer-text { font-size: 32px; font-weight: bold; margin-top: 20px; color: #2C3E50; } .card.night_mode .answer-text { color: #ECF0F1; } """ my_model = genanki.Model( model_id, "Warsaw Street Model", fields=[ {"name": "StreetMap"}, {"name": "StreetName"}, ], templates=[ { "name": "Card 1", "qfmt": '