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feat(maps): add guest_house, camp_site, and dual-key bakery lookup (#13398)
Small follow-up inspired by stale PR #2421 (@poojandpatel). - bakery now searches both shop=bakery AND amenity=bakery in one Overpass query so indie bakeries tagged either way are returned. Reproduces #2421's Lawrenceville, NJ test case (The Gingered Peach, WildFlour Bakery). - Adds tourism=guest_house and tourism=camp_site as first-class categories. - CATEGORY_TAGS entries can now be a list of (key, value) tuples; new _tags_for() normaliser + tag_pairs= kwarg on build_overpass_nearby/bbox union the results in one query. Old single-tuple call sites unchanged (back-compat preserved). - SKILL.md: 44 → 46 categories, list updated.
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2 changed files with 71 additions and 26 deletions
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@ -2,7 +2,7 @@
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name: maps
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description: >
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Location intelligence — geocode a place, reverse-geocode coordinates,
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find nearby places (44 POI categories), driving/walking/cycling
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find nearby places (46 POI categories), driving/walking/cycling
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distance + time, turn-by-turn directions, timezone lookup, bounding
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box + area for a named place, and POI search within a rectangle.
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Uses OpenStreetMap + Overpass + OSRM. Free, no API key.
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@ -83,12 +83,13 @@ python3 $MAPS nearby --near "90210" --category pharmacy
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python3 $MAPS nearby --near "downtown austin" --category restaurant --category bar --limit 10
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```
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44 categories: restaurant, cafe, bar, hospital, pharmacy, hotel, supermarket,
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atm, gas_station, parking, museum, park, school, university, bank, police,
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fire_station, library, airport, train_station, bus_stop, church, mosque,
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synagogue, dentist, doctor, cinema, theatre, gym, swimming_pool, post_office,
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convenience_store, bakery, bookshop, laundry, car_wash, car_rental,
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bicycle_rental, taxi, veterinary, zoo, playground, stadium, nightclub.
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46 categories: restaurant, cafe, bar, hospital, pharmacy, hotel, guest_house,
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camp_site, supermarket, atm, gas_station, parking, museum, park, school,
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university, bank, police, fire_station, library, airport, train_station,
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bus_stop, church, mosque, synagogue, dentist, doctor, cinema, theatre, gym,
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swimming_pool, post_office, convenience_store, bakery, bookshop, laundry,
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car_wash, car_rental, bicycle_rental, taxi, veterinary, zoo, playground,
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stadium, nightclub.
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Each result includes: `name`, `address`, `lat`/`lon`, `distance_m`,
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`maps_url` (clickable Google Maps link), `directions_url` (Google Maps
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@ -58,7 +58,9 @@ CATEGORY_TAGS = {
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"restaurant": ("amenity", "restaurant"),
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"cafe": ("amenity", "cafe"),
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"bar": ("amenity", "bar"),
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"bakery": ("shop", "bakery"),
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# bakery is tagged as shop=bakery in the OSM wiki, but some mappers use
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# amenity=bakery. Search both so small indie bakeries aren't missed.
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"bakery": [("shop", "bakery"), ("amenity", "bakery")],
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"convenience_store": ("shop", "convenience"),
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# Health
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"hospital": ("amenity", "hospital"),
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@ -68,6 +70,8 @@ CATEGORY_TAGS = {
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"veterinary": ("amenity", "veterinary"),
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# Accommodation
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"hotel": ("tourism", "hotel"),
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"guest_house": ("tourism", "guest_house"),
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"camp_site": ("tourism", "camp_site"),
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# Shopping & Services
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"supermarket": ("shop", "supermarket"),
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"bookshop": ("shop", "books"),
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@ -120,6 +124,19 @@ RELIGION_FILTER = {
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VALID_CATEGORIES = sorted(CATEGORY_TAGS.keys())
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def _tags_for(category):
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"""Return the CATEGORY_TAGS entry as a list of (key, value) pairs.
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Most categories map to a single (tag_key, tag_val) tuple, but some
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(e.g. ``bakery``) are tagged under more than one OSM key and are
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represented as a list of tuples. Normalise both forms to a list.
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"""
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entry = CATEGORY_TAGS[category]
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if isinstance(entry, list):
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return list(entry)
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return [entry]
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OSRM_PROFILES = {
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"driving": "driving",
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"walking": "foot",
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@ -338,36 +355,63 @@ def geocode_single(query):
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# ---------------------------------------------------------------------------
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def build_overpass_nearby(tag_key, tag_val, lat, lon, radius, limit,
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religion=None):
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"""Build an Overpass QL query for nearby POIs around a point."""
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religion=None, tag_pairs=None):
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"""Build an Overpass QL query for nearby POIs around a point.
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If ``tag_pairs`` is provided, the query unions across every
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``(key, value)`` pair (used for categories like ``bakery`` that are
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tagged under more than one OSM key). Otherwise falls back to the
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single ``tag_key``/``tag_val`` pair for back-compat.
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"""
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pairs = tag_pairs if tag_pairs else [(tag_key, tag_val)]
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religion_filter = ""
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if religion:
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religion_filter = f'["religion"="{religion}"]'
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body_lines = []
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for k, v in pairs:
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body_lines.append(
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f' node["{k}"="{v}"]{religion_filter}'
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f'(around:{radius},{lat},{lon});'
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)
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body_lines.append(
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f' way["{k}"="{v}"]{religion_filter}'
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f'(around:{radius},{lat},{lon});'
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)
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body = "\n".join(body_lines)
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return (
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f'[out:json][timeout:25];\n'
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f'(\n'
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f' node["{tag_key}"="{tag_val}"]{religion_filter}'
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f'(around:{radius},{lat},{lon});\n'
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f' way["{tag_key}"="{tag_val}"]{religion_filter}'
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f'(around:{radius},{lat},{lon});\n'
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f'{body}\n'
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f');\n'
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f'out center {limit};\n'
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)
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def build_overpass_bbox(tag_key, tag_val, south, west, north, east, limit,
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religion=None):
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"""Build an Overpass QL query for POIs within a bounding box."""
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religion=None, tag_pairs=None):
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"""Build an Overpass QL query for POIs within a bounding box.
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See ``build_overpass_nearby`` for ``tag_pairs`` semantics.
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"""
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pairs = tag_pairs if tag_pairs else [(tag_key, tag_val)]
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religion_filter = ""
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if religion:
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religion_filter = f'["religion"="{religion}"]'
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body_lines = []
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for k, v in pairs:
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body_lines.append(
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f' node["{k}"="{v}"]{religion_filter}'
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f'({south},{west},{north},{east});'
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)
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body_lines.append(
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f' way["{k}"="{v}"]{religion_filter}'
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f'({south},{west},{north},{east});'
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)
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body = "\n".join(body_lines)
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return (
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f'[out:json][timeout:25];\n'
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f'(\n'
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f' node["{tag_key}"="{tag_val}"]{religion_filter}'
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f'({south},{west},{north},{east});\n'
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f' way["{tag_key}"="{tag_val}"]{religion_filter}'
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f'({south},{west},{north},{east});\n'
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f'{body}\n'
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f');\n'
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f'out center {limit};\n'
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)
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@ -605,10 +649,10 @@ def cmd_nearby(args):
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# appear twice.
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merged = {}
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for category in categories:
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tag_key, tag_val = CATEGORY_TAGS[category]
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tag_pairs = _tags_for(category)
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religion = RELIGION_FILTER.get(category)
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query = build_overpass_nearby(tag_key, tag_val, lat, lon, radius, limit,
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religion=religion)
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query = build_overpass_nearby(None, None, lat, lon, radius, limit,
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religion=religion, tag_pairs=tag_pairs)
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raw = overpass_query(query)
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elements = raw.get("elements", [])
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for place in parse_overpass_elements(elements, ref_lat=lat, ref_lon=lon):
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@ -945,10 +989,10 @@ def cmd_bbox(args):
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if limit <= 0:
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error_exit("Limit must be a positive integer.")
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tag_key, tag_val = CATEGORY_TAGS[category]
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tag_pairs = _tags_for(category)
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religion = RELIGION_FILTER.get(category)
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query = build_overpass_bbox(tag_key, tag_val, south, west, north, east,
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limit, religion=religion)
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query = build_overpass_bbox(None, None, south, west, north, east,
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limit, religion=religion, tag_pairs=tag_pairs)
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raw = overpass_query(query)
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