Code Reference Library

import re

unit_designators_mapping = {
    "APARTMENT": "APT",
    "BASEMENT": "BSMT",
    "BUILDING": "BLDG",
    "DEPARTMENT": "DEPT",
    "FLOOR": "FL",
    "FRONT": "FRNT",
    "HANGER": "HNGR",
    "KEY": "KEY",
    "LOBBY": "LBBY",
    "LOT": "LOT",
    "LOWER": "LOWR",
    "OFFICE": "OFC",
    "PENTHOUSE": "PH",
    "PIER": "PIER",
    "REAR": "REAR",
    "ROOM": "RM",
    "SIDE": "SIDE",
    "SLIP": "SLIP",
    "SPACE": "SPC",
    "STOP": "STOP",
    "SUITE": "STE",
    "TRAILER": "TRLR",
    "UNIT": "UNIT",
    "UPPER": "UPPR",
    "#": "NUMBER"
}

# build sets of all designators (full words and abbreviations)
all_designators = set(unit_designators_mapping.keys()) | set(unit_designators_mapping.values())

# split into word-only vs symbol-containing
word_designators = [d for d in all_designators if re.match(r'^\w+$', d)]
symbol_designators = [d for d in all_designators if not re.match(r'^\w+$', d)]

# build two sub-patterns: one with \b…\b for word-designators, one raw for symbols
parts = []
if word_designators:
    parts.append(r"\b(?:" + "|".join(re.escape(d) for d in word_designators) + r")\b")
if symbol_designators:
    parts.append("|".join(re.escape(d) for d in symbol_designators))

# final pattern matches either case
unit_identifiers = r"(?:" + "|".join(parts) + r")"

def normalize_unit_number(unit_info: str) -> str:
    """
    Remove known designators (case-insensitive), then trim whitespace.
    """
    return re.sub(unit_identifiers, "", unit_info, flags=re.IGNORECASE).strip()

# example usage
if __name__ == "__main__":
    print(normalize_unit_number("Apartment 12B"))   # "12B"
    print(normalize_unit_number("#300"))           # "300"
    print(normalize_unit_number("# 300"))          # "300"
    print(normalize_unit_number("number 300"))     # "300"
    print(normalize_unit_number("Unit 12A"))       # "12A"
    print(normalize_unit_number("Suite 100"))      # "100"
    print(normalize_unit_number("Apt 5"))          # "5"
    print(normalize_unit_number("BSMT 1"))         # "1"
    print(normalize_unit_number("FL 3"))           # "3"
    print(normalize_unit_number("PH 2"))           # "2"
    print(normalize_unit_number("TRLR 4"))         # "4"
    print(normalize_unit_number("123"))            # "123" (no change)
    print(normalize_unit_number("  "))             # "" (empty string)

import requests

# Set the request headers with your API Key
headers = {"Authorization": "<YOUR_API_KEY>"}

# Define the API endpoint URL
url = "https://app.realie.ai/api/public/property/search/"

# Set the number of records to fetch per request (limit) and start cursor pagination
limit = 10
cursor = "start"

while True:
    # Define query parameters including limit, cursor, county, and state
    params = {"limit": limit, "cursor": cursor, "county": "MONTEREY", "state": "CA"}
    
    # Send a GET request to the API with the headers and parameters
    response = requests.get(url, headers=headers, params=params)
    
    # Check if the response returned a non-200 status code
    if response.status_code != 200:
        print("Error:", response.status_code, response.text)
        break

    # Parse the JSON response and extract the list of properties
    data = response.json()
    properties = data.get("properties", [])
    
    # Print how many properties were fetched
    print(f"Fetched {len(properties)} properties")
    
    # If no properties are returned, exit the loop
    if not properties:
        break

    # Loop through each property and print its details
    for prop in properties:
        print(prop)

    # Use the next cursor for the following page; null means no more results
    next_cursor = data.get("metadata", {}).get("nextCursor")
    if next_cursor is None:
        break
    cursor = next_cursor

# Print a final message after finishing the loop
print("Finished looping through parcels.")