Make great documentation goal 1.2, and plan the README's reorganisation and the nested-template gaps #33
@@ -90,7 +90,7 @@ In [docs/decisions.md](docs/decisions.md):
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- A path is walked once without drawing before it is walked for real
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- A country's postal codes and streets are siblings under its locality
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- A locale package imports its country's geo package, and its `Modules()` returns both
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- The default embed holds every Swedish postort the import can place with all its streets, and of the US places that hold most of a postal code's land every state capital, every place of 100,000 and a population-weighted tenth of the rest, each with a quarter of its streets, at least ten
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- The default embed holds every Swedish postort the import can place with all its streets, and of the US places that hold most of a postal code's land a population-weighted tenth, every state capital and every place of 100,000, each with a quarter of its streets, at least ten
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- A locale's `address` binds its country's record once and prints it whole
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- A postort's kommun comes from its name, its tätort or its codes, never from distance
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- A highway designation is not a street, and a US postal code belongs to the place holding most of its land inside places
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+4
-4
@@ -95,10 +95,10 @@ replacement, and each removed path, column or flag.
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`en_US.address.street` no longer carries `name` and `suffix`, and a locale's `address`
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reads its country's `geo` module. Every Swedish postort the import can place and give
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a street ships with all its streets. Of the US incorporated places that hold most of
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some postal code's land, every state capital but Honolulu, every place of 100,000 or
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more, and a tenth of the rest drawn by population down to villages of a hundred people
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ship, so a smaller city may be missing; each carries a quarter of its streets, at least
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ten.
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some postal code's land, a tenth drawn by population down to villages of a hundred
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people ships, and every state capital but Honolulu and every place of 100,000 or more
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beside, so a smaller city may be missing; each carries a quarter of its streets, at
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least ten.
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- `{date(from,to,'layout')}` and `{time('layout')}`: a second between two days, or
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within one, in a single-quoted Go layout, drawn in UTC; `from` may equal `to`.
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`sv_SE.date`, `en_US.date`, `sv_SE.time` and `en_US.time` render through them, so
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@@ -313,14 +313,14 @@ neighbouring one.
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| `municipality` | kommun, by code or name | county, by FIPS code or name | population |
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| `locality` | postort, by name; [`geo-se.py`](data-import/geo-se.py)'s `localities` picks the candidates, and one with no street is dropped | incorporated place, by GEOID or name; Hawaii has none | tätort population, the kommun's where the postort names it, else 200; place population |
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| `postal-code` | postnummer with street delivery, by code | ZCTA, by code | one; address ranges |
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| `street` | gatunamn, every one | street name, per place the quarter with most address ranges, at least ten | segments; address ranges |
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| `street` | gatunamn, every one; [`geo-se.py`](data-import/geo-se.py)'s `street_name` drops a name that is not a street's | street name, per place the quarter with most address ranges, at least ten | segments; address ranges |
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`geo.SE.region[Skåne län].municipality` draws a kommun in Skåne,
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`geo.SE.locality[Lund].street` a street in Lund, and
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`geo.US.region[IL].locality[Springfield]` settles which Springfield. The US places are
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the incorporated places that hold most of some postal code's land: every state capital,
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every place of 100,000 or more, and a tenth of the rest drawn with odds by population,
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so a smaller city may be missing: look one up in
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the incorporated places that hold most of some postal code's land: a tenth of them drawn
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with odds by population, and every state capital but Honolulu and every place of 100,000
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or more beside, so a smaller city may be missing: look one up in
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[`locality.tsv`](data/geo/US/locality.tsv) before selecting it. A region row
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carries its `timezone`, the state's predominant zone, and a locality its `lat` and
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`lon`. What ports across countries is the five table names, the `name` column,
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@@ -28,18 +28,18 @@ ZCTA_PLACE = "https://www2.census.gov/geo/docs/maps-data/data/rel2020/zcta520/ta
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TIGER = "https://www2.census.gov/geo/tiger/TIGER2025/{0}/tl_2025_{1}_{2}.zip"
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ESTIMATE = "POPESTIMATE2025"
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CDP = "57"
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# Each state's capital from Wikidata (CC0), with the capital's GNIS ids, which the Gazetteer carries as ANSICODE.
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# Each state's capital from Wikidata, with the capital's GNIS ids, which the Gazetteer carries as ANSICODE.
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CAPITALS = "https://query.wikidata.org/sparql?" + urllib.parse.urlencode({"query": """
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SELECT ?iso ?capitalLabel ?gnis WHERE {
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?state wdt:P31 wd:Q35657; wdt:P300 ?iso; wdt:P36 ?capital.
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OPTIONAL { ?capital wdt:P590 ?gnis. }
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SERVICE wikibase:label { bd:serviceParam wikibase:language "en". }
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}"""})
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ALWAYS = 100000
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SHIPPED_POPULATION = 100000
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HIGHWAY = re.compile(r"\b(I- |Hwy |Highway |Loop |Rte |Route |Rd )\d")
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SUFFIX = re.compile(r" (city and borough|city|town|village|borough|municipality|comunidad|zona urbana|metropolitan government|metro government|consolidated government|unified government|urban county|corporation|plantation)( \(balance\))?$")
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# Places whose Census name is not the postal city an address carries.
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NAMES = {"1303440": "Athens", "1304204": "Augusta", "1349008": "Macon", "1608830": "Boise", "2148006": "Louisville", "3011397": "Butte", "4732742": "Hartsville", "4752006": "Nashville"}
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NAMES = {"0665042": "Ventura", "1303440": "Athens", "1304204": "Augusta", "1349008": "Macon", "1608830": "Boise", "2146027": "Lexington", "2148006": "Louisville", "3011397": "Butte", "4732742": "Hartsville", "4744382": "Lynchburg", "4752006": "Nashville"}
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TIMEZONES = {
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"AK": "America/Anchorage", "AL": "America/Chicago", "AR": "America/Chicago", "AZ": "America/Phoenix",
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"CA": "America/Los_Angeles", "CO": "America/Denver", "CT": "America/New_York", "DC": "America/New_York",
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@@ -137,9 +137,12 @@ def localities(cache, counties):
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def capitals(cache, places, counties):
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"""The codes of the places that are a state's capital, matched by any of its GNIS ids, else by name inside the state."""
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"""The codes of the places that are a state's capital, matched by any of its GNIS ids, else by a name no other place in the state carries."""
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by_gnis = {p["gnis"]: code for code, p in places.items()}
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by_name = {(counties[p["municipality"]]["region"], p["name"]): code for code, p in places.items()}
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named = collections.defaultdict(list)
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for code, p in places.items():
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named[(counties[p["municipality"]]["region"], p["name"])].append(code)
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by_name = {key: codes[0] for key, codes in named.items() if len(codes) == 1}
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gnis_of = collections.defaultdict(set)
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for r in csv.DictReader(io.StringIO(text(source.fetch(CAPITALS, cache, "capitals.csv", magic=b"iso,", headers={"Accept": "text/csv"})))):
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gnis_of[(r["iso"].removeprefix("US-"), r["capitalLabel"])].add(int(r["gnis"] or 0))
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@@ -211,7 +214,7 @@ def main():
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owners = {p: places[p] for p in set(owner_of_zcta.values())}
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for code in sorted(capital_codes - set(owners)):
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print(f"{code} {places[code]['name']}: capital owns no ZCTA, dropped", file=sys.stderr)
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places = drawn(owners, a.place_share) | {code: p for code, p in owners.items() if code in capital_codes or p["population"] >= ALWAYS}
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places = drawn(owners, a.place_share) | {code: p for code, p in owners.items() if code in capital_codes or p["population"] >= SHIPPED_POPULATION}
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locality_of_zcta = {zcta: p for zcta, p in owner_of_zcta.items() if p in places}
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named, addresses = streets(cache, sorted({l["municipality"] for l in places.values()}), locality_of_zcta, a.street_share, a.min_streets)
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zctas = collections.defaultdict(list)
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+2
-2
@@ -376,8 +376,8 @@ func TestShippedAddressIsOneNamedPick(t *testing.T) {
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}
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}
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// TestShippedPlacesSpreadAddresses pins that Göteborg ships every street, Los Angeles a
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// quarter of its streets, and that some US place holds under 2,500 people.
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// TestShippedPlacesSpreadAddresses pins that Göteborg ships 1,500 streets or more, Los
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// Angeles 2,500 or more, and that some US place holds under 2,500 people.
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func TestShippedPlacesSpreadAddresses(t *testing.T) {
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for country, city := range map[string]struct {
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key string
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+3
-3
@@ -603,7 +603,7 @@ providing `geo.SE`'s paths, and without one `sv_SE.address` fails at first reach
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`FS` works against goal 6.2. Every package exports `Modules()`, so one spelling loads any of
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them; a data package imports only the packages it reads.
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## The default embed holds every Swedish postort the import can place with all its streets, and of the US places that hold most of a postal code's land every state capital, every place of 100,000 and a population-weighted tenth of the rest, each with a quarter of its streets, at least ten
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## The default embed holds every Swedish postort the import can place with all its streets, and of the US places that hold most of a postal code's land a population-weighted tenth, every state capital and every place of 100,000, each with a quarter of its streets, at least ten
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2026-10-11, Lilleman auf Larv; revised the same day, after a tenth of the streets gave
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Göteborg 163 and Stockholm 37. Goals 2 and 14: ten streets per place put 500 Stockholm
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@@ -615,8 +615,8 @@ postal code. The draw alone kept 310 of the 343 places of 100,000 or more and le
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or name`; every capital and every place of 100,000 now ships beside the draw, and its
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smallest place holds 93 people. The capitals are each state's `capital` (P36) in
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[Wikidata](https://www.wikidata.org/), matched to a Census place by its GNIS id and
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else by name in its state. Honolulu, a census-designated place, is the one capital and
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the one place of 100,000 that cannot ship. Every Swedish street is 174k rows; a quarter
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else by a name no other place in its state carries. No census-designated place ships,
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so Honolulu is the one capital missing. Every Swedish street is 174k rows; a quarter
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of the US streets 475k. On 2026-10-11 the embed grew from 5.2 MB to 16 MB, and a CLI
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run printing the first `en_US.address` took 145 ms, `sv_SE.address` 95 ms and
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`misc.territory` 3 ms, within goal 13. `--place-share`, `--street-share` and
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Reference in New Issue
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