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1from fastapi import FastAPI, HTTPException, Header
2from pydantic import BaseModel
3from typing import Optional
4import secrets
5import random
6from datetime import datetime, timedelta
7import math
8 
9app = FastAPI()
10 
11users = {}
12tokens = {}
13properties = {}
14comps_data = {}
15market_trends = {}
16next_user_id = 1
17next_property_id = 1
18 
19class SignupRequest(BaseModel):
20    email: str
21    password: str
22 
23class LoginRequest(BaseModel):
24    email: str
25    password: str
26 
27class PropertyCreate(BaseModel):
28    address: str
29    price: float
30    sqft: float
31    beds: int
32    baths: int
33    zip_code: str
34 
35class CompResponse(BaseModel):
36    property_id: int
37    address: str
38    sold_price: float
39    price_per_sqft: float
40    days_on_market: int
41    sold_date: str
42 
43class MarketTrend(BaseModel):
44    month: str
45    median_price: float
46 
47def get_current_user(authorization: str = Header(None)):
48    if not authorization:
49        raise HTTPException(status_code=401, detail="Missing auth header")
50    token = authorization.replace("Bearer ", "")
51    user_id = tokens.get(token)
52    if not user_id:
53        raise HTTPException(status_code=401, detail="Invalid token")
54    return user_id
55 
56@app.post("/signup")
57def signup(req: SignupRequest):
58    global next_user_id
59    for u in users.values():
60        if u["email"] == req.email:
61            raise HTTPException(status_code=400, detail="Email already exists")
62    user_id = next_user_id
63    next_user_id += 1
64    users[user_id] = {"id": user_id, "email": req.email, "password": req.password}
65    return {"user_id": user_id, "email": req.email}
66 
67@app.post("/login")
68def login(req: LoginRequest):
69    for u in users.values():
70        if u["email"] == req.email and u["password"] == req.password:
71            token = secrets.token_hex(16)
72            tokens[token] = u["id"]
73            return {"token": token}
74    raise HTTPException(status_code=401, detail="Invalid credentials")
75 
76@app.post("/properties")
77def create_property(prop: PropertyCreate, authorization: str = Header(None)):
78    get_current_user(authorization)
79    global next_property_id
80    prop_id = next_property_id
81    next_property_id += 1
82    properties[prop_id] = {
83        "id": prop_id,
84        "address": prop.address,
85        "price": prop.price,
86        "sqft": prop.sqft,
87        "beds": prop.beds,
88        "baths": prop.baths,
89        "zip_code": prop.zip_code,
90        "created_at": datetime.now().isoformat()
91    }
92    return properties[prop_id]
93 
94@app.get("/properties/{property_id}")
95def get_property(property_id: int, authorization: str = Header(None)):
96    get_current_user(authorization)
97    prop = properties.get(property_id)
98    if not prop:
99        raise HTTPException(status_code=404, detail="Property not found")
100    return prop
101 
102@app.get("/properties/{property_id}/comps")
103def get_comps(property_id: int, authorization: str = Header(None)):
104    get_current_user(authorization)
105    prop = properties.get(property_id)
106    if not prop:
107        raise HTTPException(status_code=404, detail="Property not found")
108    
109    if property_id not in comps_data:
110        seed = property_id * 42
111        rng = random.Random(seed)
112        comps = []
113        base_price = prop["price"]
114        base_sqft = prop["sqft"]
115        for i in range(5):
116            comp_id = property_id * 100 + i
117            price_mult = 0.8 + rng.random() * 0.4
118            sqft_mult = 0.85 + rng.random() * 0.3
119            sold_price = round(base_price * price_mult, 2)
120            sqft = round(base_sqft * sqft_mult, 1)
121            price_per_sqft = round(sold_price / sqft, 2)
122            days = rng.randint(10, 120)
123            sold_date = (datetime.now() - timedelta(days=days)).strftime("%Y-%m-%d")
124            comps.append({
125                "property_id": comp_id,
126                "address": f"{100 + i} Similar St, {prop['zip_code']}",
127                "sold_price": sold_price,
128                "price_per_sqft": price_per_sqft,
129                "days_on_market": days,
130                "sold_date": sold_date
131            })
132        comps_data[property_id] = comps
133    
134    return {"comps": comps_data[property_id]}
135 
136@app.get("/market/trends")
137def get_market_trends(authorization: str = Header(None)):
138    get_current_user(authorization)
139    
140    if not market_trends:
141        rng = random.Random(42)
142        base_price = 450000
143        trends = []
144        for i in range(12):
145            month_date = datetime.now() - timedelta(days=30 * (11 - i))
146            month_str = month_date.strftime("%Y-%m")
147            variation = 1 + (rng.random() - 0.5) * 0.1
148            trend_price = round(base_price * (1 + i * 0.005) * variation, 2)
149            trends.append({
150                "month": month_str,
151                "median_price": trend_price
152            })
153        market_trends["data"] = trends
154    
155    return {"trends": market_trends["data"]}

1fastapi
2uvicorn
3pydantic