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Move warsaw_bridges, warsaw_districts, warsaw_landmarks, warsaw_metro, warsaw_osiedla, warsaw_streets, and car_brand_logos into the existing python_pkg/anki_decks/ directory alongside the polish_* generators. Also move preview_all.html into anki_decks/. Update all import paths, filesystem references in geo_data.py, docstrings, READMEs, test imports, and .gitignore accordingly.
357 lines
10 KiB
Python
Executable File
357 lines
10 KiB
Python
Executable File
#!/usr/bin/env python3
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"""Anki flashcard generator for Warsaw streets.
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Generates Anki-compatible flashcard decks with maps showing individual
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Warsaw streets highlighted on a city map.
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Usage:
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python -m python_pkg.anki_decks.warsaw_streets.warsaw_streets_anki
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Output:
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Creates a self-contained .apkg file that can be directly imported into Anki.
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"""
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from __future__ import annotations
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import argparse
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import hashlib
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from io import BytesIO
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from pathlib import Path
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import random
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import sys
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from typing import TYPE_CHECKING, Any
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sys.path.insert(0, str(Path(__file__).parent.parent))
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import genanki
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from geo_data import get_warsaw_streets
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import geopandas as gpd
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import matplotlib.pyplot as plt
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from shapely.geometry import MultiLineString
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if TYPE_CHECKING:
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from collections.abc import Sequence
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from matplotlib.figure import Figure
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# Minimum street length in meters to include
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MIN_STREET_LENGTH = 500
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def get_unique_streets(
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gdf: gpd.GeoDataFrame,
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) -> list[tuple[str, gpd.GeoDataFrame, float]]:
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"""Group street segments by name and merge geometries.
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Args:
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gdf: GeoDataFrame with street segments.
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Returns:
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List of (name, GeoDataFrame, length_m) tuples, sorted by length (longest first).
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"""
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# Group by street name
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streets: dict[str, list[Any]] = {}
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for _, row in gdf.iterrows():
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name = row["name"]
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if name and name != "Unknown":
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if name not in streets:
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streets[name] = []
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streets[name].append(row.geometry)
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# Merge geometries and calculate length
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result = []
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for name, geometries in streets.items():
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merged = geometries[0] if len(geometries) == 1 else MultiLineString(geometries)
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# Create a GeoDataFrame for this street
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street_gdf = gpd.GeoDataFrame(
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[{"name": name, "geometry": merged}], crs="EPSG:4326"
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)
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# Calculate length in meters (approximate)
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street_gdf_proj = street_gdf.to_crs("EPSG:2180") # Polish coordinate system
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length = street_gdf_proj.geometry.length.iloc[0]
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if length >= MIN_STREET_LENGTH:
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result.append((name, street_gdf, length))
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# Sort by length (longest first)
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result.sort(key=lambda x: x[2], reverse=True)
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return result
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def load_street_data() -> (
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tuple[list[tuple[str, gpd.GeoDataFrame, float]], gpd.GeoDataFrame]
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):
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"""Load Warsaw streets and boundary.
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Returns:
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Tuple of (streets list sorted by length, warsaw boundary GeoDataFrame).
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"""
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streets_gdf = get_warsaw_streets(min_length=MIN_STREET_LENGTH)
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streets = get_unique_streets(streets_gdf)
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# Load Warsaw districts for boundary (reuse from warsaw_districts)
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districts_path = (
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Path(__file__).parent.parent / "warsaw_districts" / "warszawa-dzielnice.geojson"
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)
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if districts_path.exists():
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warsaw_gdf = gpd.read_file(districts_path)
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# Get just Warsaw boundary
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warsaw_boundary = warsaw_gdf[warsaw_gdf["name"] == "Warszawa"]
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if len(warsaw_boundary) == 0:
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# Dissolve all districts
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warsaw_boundary = gpd.GeoDataFrame(
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geometry=[warsaw_gdf.union_all()], crs=warsaw_gdf.crs
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)
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else:
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msg = "Warsaw boundary data not found"
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raise FileNotFoundError(msg)
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return streets, warsaw_boundary
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# Color for highlighted street
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STREET_COLOR = "#E74C3C" # Red
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def create_street_map(
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street_gdf: gpd.GeoDataFrame,
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warsaw_boundary: gpd.GeoDataFrame,
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) -> Figure:
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"""Create a map showing Warsaw with one street highlighted.
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Args:
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street_name: Name of the street.
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street_gdf: GeoDataFrame with the street geometry.
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warsaw_boundary: GeoDataFrame with Warsaw boundary.
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Returns:
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A matplotlib Figure object.
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"""
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fig, ax = plt.subplots(figsize=(10, 10))
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ax.set_aspect("equal")
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ax.axis("off")
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fig.patch.set_alpha(0)
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ax.patch.set_alpha(0)
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# Plot Warsaw as a plain gray shape
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warsaw_boundary.plot(ax=ax, color="#D5D8DC", alpha=0.6)
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warsaw_boundary.boundary.plot(ax=ax, color="#2C3E50", linewidth=2)
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# Plot the highlighted street
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street_gdf.plot(ax=ax, color=STREET_COLOR, linewidth=4, alpha=0.9)
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# Set bounds to Warsaw
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bounds = warsaw_boundary.total_bounds
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ax.set_xlim(bounds[0], bounds[2])
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ax.set_ylim(bounds[1], bounds[3])
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return fig
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def generate_street_image_bytes(
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street_gdf: gpd.GeoDataFrame,
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warsaw_boundary: gpd.GeoDataFrame,
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) -> bytes:
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"""Generate a street map image as bytes.
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Args:
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street_gdf: GeoDataFrame with the street geometry.
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warsaw_boundary: GeoDataFrame with Warsaw boundary.
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Returns:
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PNG image data as bytes.
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"""
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fig = create_street_map(street_gdf, warsaw_boundary)
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buf = BytesIO()
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fig.savefig(buf, format="png", bbox_inches="tight", dpi=150)
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plt.close(fig)
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buf.seek(0)
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return buf.read()
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def generate_anki_package(
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streets: list[tuple[str, gpd.GeoDataFrame, float]],
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warsaw_boundary: gpd.GeoDataFrame,
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deck_name: str = "Warsaw Streets",
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) -> genanki.Package:
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"""Generate Anki package for Warsaw streets.
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Args:
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streets: List of (name, GeoDataFrame, length) tuples, sorted by length.
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warsaw_boundary: GeoDataFrame with Warsaw boundary.
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deck_name: Name for the Anki deck.
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Returns:
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genanki.Package object.
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"""
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model_id_hash = hashlib.md5(f"warsaw_streets_{deck_name}".encode()) # noqa: S324
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model_id = int(model_id_hash.hexdigest()[:8], 16)
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card_css = """
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.card {
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font-family: Arial, sans-serif;
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font-size: 24px;
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text-align: center;
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color: #333;
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background-color: #fff;
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}
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.card.night_mode {
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color: #eee;
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background-color: #2f2f2f;
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}
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.map-container {
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display: flex;
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justify-content: center;
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align-items: center;
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min-height: 80vh;
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}
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.map-container img {
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max-width: 100%;
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max-height: 80vh;
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object-fit: contain;
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}
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.answer-text {
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font-size: 32px;
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font-weight: bold;
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margin-top: 20px;
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color: #2C3E50;
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}
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.card.night_mode .answer-text {
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color: #ECF0F1;
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}
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"""
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my_model = genanki.Model(
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model_id,
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"Warsaw Street Model",
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fields=[
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{"name": "StreetMap"},
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{"name": "StreetName"},
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],
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templates=[
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{
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"name": "Card 1",
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"qfmt": '<div class="map-container">{{StreetMap}}</div>',
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"afmt": '<div class="map-container">{{StreetMap}}</div>'
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'<hr id="answer">'
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'<div class="answer-text">{{StreetName}}</div>',
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},
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],
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css=card_css,
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)
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deck_id = random.randrange(1 << 30, 1 << 31) # noqa: S311
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my_deck = genanki.Deck(deck_id, deck_name)
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media_files = []
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# Streets are already sorted by length (longest first)
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for street_name, street_gdf, _length in streets:
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image_data = generate_street_image_bytes(street_gdf, warsaw_boundary)
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filename = f"street_{street_name.replace(' ', '_').replace('/', '_')}.png"
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note = genanki.Note(
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model=my_model,
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fields=[f'<img src="{filename}">', street_name],
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tags=["geography", "warsaw", "streets"],
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)
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my_deck.add_note(note)
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temp_path = Path(f"/tmp/{filename}") # noqa: S108
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temp_path.write_bytes(image_data)
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media_files.append(str(temp_path))
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package = genanki.Package(my_deck)
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package.media_files = media_files
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return package
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def main(argv: Sequence[str] | None = None) -> int:
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"""Main entry point."""
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parser = argparse.ArgumentParser(
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description="Generate Anki flashcards for Warsaw streets.",
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)
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parser.add_argument(
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"--output",
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"-o",
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type=str,
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default=None,
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help="Output file path (default: warsaw_streets.apkg)",
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)
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parser.add_argument(
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"--deck-name",
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"-d",
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type=str,
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default="Warsaw Streets",
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help="Name for the Anki deck",
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)
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parser.add_argument(
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"--min-length",
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"-m",
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type=int,
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default=MIN_STREET_LENGTH,
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help=f"Minimum street length in meters (default: {MIN_STREET_LENGTH})",
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)
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parser.add_argument(
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"--preview",
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"-p",
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type=str,
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default=None,
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help="Export preview images to specified directory",
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)
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parser.add_argument(
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"--preview-count",
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type=int,
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default=5,
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help="Number of preview images to export (default: 5)",
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)
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args = parser.parse_args(argv)
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output_path = Path(args.output) if args.output else Path("warsaw_streets.apkg")
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try:
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sys.stdout.write("Loading street data...\n")
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streets, warsaw_boundary = load_street_data()
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num_streets = len(streets)
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sys.stdout.write(f"Generating flashcards for {num_streets} Warsaw streets...\n")
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package = generate_anki_package(streets, warsaw_boundary, args.deck_name)
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package.write_to_file(str(output_path))
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# Export preview images if requested (top N longest streets)
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if args.preview:
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preview_dir = Path(args.preview)
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preview_dir.mkdir(parents=True, exist_ok=True)
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preview_streets = streets[: args.preview_count]
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sys.stdout.write(
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f"Exporting {len(preview_streets)} preview images "
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f"(longest streets) to {preview_dir}...\n"
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)
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for street_name, street_gdf, length_m in preview_streets:
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image_data = generate_street_image_bytes(street_gdf, warsaw_boundary)
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safe_name = street_name.replace(" ", "_").replace("/", "_")
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preview_path = preview_dir / f"{safe_name}.png"
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preview_path.write_bytes(image_data)
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sys.stdout.write(f" Saved: {preview_path.name} ({length_m:.0f}m)\n")
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sys.stdout.write("\n")
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sys.stdout.write("=" * 60 + "\n")
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sys.stdout.write("FLASHCARD GENERATION COMPLETE\n")
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sys.stdout.write("=" * 60 + "\n")
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sys.stdout.write(f"Streets: {num_streets}\n")
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sys.stdout.write(f"Output file: {output_path.absolute()}\n")
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if args.preview:
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sys.stdout.write(f"Preview images: {args.preview}\n")
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except (OSError, ValueError, RuntimeError) as e:
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sys.stderr.write(f"Error: {e}\n")
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return 1
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else:
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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