EiSiMo
d13f9c5b6e
Adds a collapsible 12-Bezirk checkbox list to the filter tab. The UI speaks Bezirke; internally the match runs on the PLZ extracted from flat.address and resolved to a dominant Bezirk via a curated 187-PLZ map (berlin_districts.py). - Migration 0011 adds user_filters.districts (CSV of selected names) - Empty stored value = no filter = all Bezirke ticked in the UI. Submitting "all ticked" or "none ticked" both normalise to empty so the defaults and the nuclear state mean the same thing. - When a Bezirk filter is active, flats with an unknown/unmapped PLZ are excluded — if the user bothered to narrow by district, sneaking in unplaceable flats would be the wrong default. - Filter summary on the Wohnungen page shows "N Bezirke" so it's visible the filter is active. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
120 lines
3.6 KiB
Python
120 lines
3.6 KiB
Python
"""Berlin-Bezirke taxonomy + PLZ lookup.
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The user-visible taxonomy is the 12 Berlin Bezirke. We derive the Bezirk
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from the flat's freeform address by extracting the 5-digit PLZ and
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looking it up in PLZ_TO_DISTRICT.
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Some PLZs straddle two Bezirke in reality. Each is mapped to its
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dominant Bezirk — close enough for a list filter. Unmapped PLZs / flats
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without a parseable address resolve to None; the filter treats those as
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"unknown" and excludes them when any Bezirk filter is active.
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"""
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import re
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DISTRICTS: list[str] = [
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"Mitte",
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"Friedrichshain-Kreuzberg",
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"Pankow",
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"Charlottenburg-Wilmersdorf",
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"Spandau",
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"Steglitz-Zehlendorf",
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"Tempelhof-Schöneberg",
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"Neukölln",
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"Treptow-Köpenick",
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"Marzahn-Hellersdorf",
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"Lichtenberg",
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"Reinickendorf",
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]
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_DISTRICT_PLZ: dict[str, tuple[str, ...]] = {
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"Mitte": (
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"10115", "10117", "10119", "10178", "10179",
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"10551", "10553", "10555", "10557", "10559",
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"13347", "13349", "13351", "13353", "13355", "13357", "13359",
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),
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"Friedrichshain-Kreuzberg": (
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"10243", "10245", "10247", "10249",
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"10961", "10963", "10965", "10967", "10969",
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"10997", "10999",
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),
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"Pankow": (
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"10405", "10407", "10409",
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"10435", "10437", "10439",
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"13086", "13088", "13089",
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"13125", "13127", "13129",
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"13156", "13158", "13159",
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"13187", "13189",
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),
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"Charlottenburg-Wilmersdorf": (
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"10585", "10587", "10589",
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"10623", "10625", "10627", "10629",
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"10707", "10709", "10711", "10713", "10715", "10717", "10719",
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"10789",
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"14050", "14052", "14053", "14055", "14057", "14059",
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"14193", "14195", "14197", "14199",
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),
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"Spandau": (
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"13581", "13583", "13585", "13587", "13589",
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"13591", "13593", "13595", "13597", "13599",
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"14089",
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),
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"Steglitz-Zehlendorf": (
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"12157", "12159", "12161", "12163", "12165", "12167", "12169",
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"12203", "12205", "12207", "12209",
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"12247", "12249",
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"14109", "14129",
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"14163", "14165", "14167", "14169",
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),
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"Tempelhof-Schöneberg": (
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"10777", "10779", "10781", "10783", "10785", "10787",
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"10823", "10825", "10827", "10829",
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"12099", "12101", "12103", "12105", "12107", "12109",
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"12277", "12279",
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"12305", "12307", "12309",
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),
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"Neukölln": (
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"12043", "12045", "12047", "12049",
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"12051", "12053", "12055", "12057", "12059",
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"12347", "12349",
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"12351", "12353", "12355", "12357", "12359",
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),
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"Treptow-Köpenick": (
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"12435", "12437", "12439",
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"12459", "12487", "12489",
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"12524", "12526", "12527",
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"12555", "12557", "12559",
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"12587", "12589",
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),
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"Marzahn-Hellersdorf": (
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"12619", "12621", "12623", "12627", "12629",
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"12679", "12681", "12683", "12685", "12687", "12689",
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),
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"Lichtenberg": (
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"10315", "10317", "10318",
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"10365", "10367", "10369",
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"13051", "13053", "13055", "13057", "13059",
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),
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"Reinickendorf": (
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"13403", "13405", "13407", "13409",
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"13435", "13437", "13439",
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"13465", "13467", "13469",
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"13503", "13505", "13507", "13509",
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),
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}
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PLZ_TO_DISTRICT: dict[str, str] = {
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plz: district
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for district, plzs in _DISTRICT_PLZ.items()
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for plz in plzs
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}
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_PLZ_RE = re.compile(r"\b(\d{5})\b")
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def district_for_address(address: str | None) -> str | None:
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if not address:
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return None
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m = _PLZ_RE.search(address)
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if not m:
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return None
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return PLZ_TO_DISTRICT.get(m.group(1))
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