Create RentPredictor.py

Author: rogers-cyber

House-rent-prediction-app/RentPredictor.py

@@ -0,0 +1,194 @@
+"""
+RentPredictor v1.0 - Smart Housing Intelligence Tool
+ML-powered house rent estimation with modern UI
+"""
+
+import os, sys, threading
+import tkinter as tk
+from tkinter import messagebox
+
+import numpy as np
+import joblib
+
+import ttkbootstrap as tb
+from ttkbootstrap.constants import *
+
+# ---------------------- UTIL ----------------------
+def resource_path(file_name):
+    base_path = getattr(sys, "_MEIPASS", os.path.dirname(os.path.abspath(__file__)))
+    return os.path.join(base_path, file_name)
+
+
+# ---------------------- ML WORKER ----------------------
+class PredictionWorker:
+    def __init__(self, model, features, callback):
+        self.model = model
+        self.features = features
+        self.callback = callback
+
+    def run(self):
+        try:
+            prediction = self.model.predict([self.features])[0]
+            self.callback(round(prediction, 2))
+        except Exception as e:
+            self.callback(None, str(e))
+
+
+# ---------------------- MAIN APP ----------------------
+class RentPredictorApp:
+    APP_NAME = "RentPredictor"
+    APP_VERSION = "1.0"
+
+    def __init__(self):
+        self.root = tb.Window(themename="darkly")
+        self.root.title(f"{self.APP_NAME} v{self.APP_VERSION}")
+        self.root.minsize(900, 520)
+
+        try:
+            self.root.iconbitmap(resource_path("logo.ico"))
+        except:
+            pass
+
+        self.model = self._load_model()
+        self._build_ui()
+
+    # ---------------------- LOAD MODEL ----------------------
+    def _load_model(self):
+        try:
+            return joblib.load(resource_path("rent_model.pkl"))
+        except:
+            # fallback dummy model
+            class DummyModel:
+                def predict(self, X):
+                    size, bhk, bath, city = X[0]
+                    return [size * 25 + bhk * 1500 + bath * 1000 + city * 2000]
+            return DummyModel()
+
+    # ---------------------- UI ----------------------
+    def _build_ui(self):
+        main = tb.Frame(self.root, padding=15)
+        main.pack(fill=BOTH, expand=True)
+
+        tb.Label(
+            main,
+            text="🏠 RentPredictor - Smart Rent Estimation",
+            font=("Segoe UI", 22, "bold")
+        ).pack(pady=(0, 5))
+
+        tb.Label(
+            main,
+            text="AI-powered house rent prediction engine",
+            font=("Segoe UI", 10, "italic"),
+            foreground="#9ca3af"
+        ).pack(pady=(0, 25))
+
+        form = tb.Labelframe(main, text="Property Details", padding=15)
+        form.pack(fill=X, pady=(0, 20))
+
+        # Inputs
+        self.size_var = tk.DoubleVar()
+        self.bhk_var = tk.IntVar()
+        self.bath_var = tk.IntVar()
+        self.city_var = tk.IntVar()
+
+        self._add_field(form, "House Size (sq ft)", self.size_var, 0)
+        self._add_field(form, "BHK", self.bhk_var, 1)
+        self._add_field(form, "Bathrooms", self.bath_var, 2)
+
+        tb.Label(form, text="City Category").grid(row=3, column=0, sticky=W, pady=5)
+        self.city_combo = tb.Combobox(
+            form,
+            values=["Small City", "Metro City"],
+            state="readonly"
+        )
+        self.city_combo.current(0)
+        self.city_combo.grid(row=3, column=1, sticky=EW, pady=5)
+
+        # Actions
+        actions = tb.Frame(main)
+        actions.pack(fill=X, pady=(0, 15))
+
+        self.predict_btn = tb.Button(
+            actions,
+            text="🔮 Predict Rent",
+            bootstyle=SUCCESS,
+            command=self.predict
+        )
+        self.predict_btn.pack(side=LEFT, padx=5)
+
+        tb.Button(
+            actions,
+            text="ℹ️ About",
+            bootstyle=INFO,
+            command=self.show_about
+        ).pack(side=LEFT, padx=5)
+
+        # Result
+        self.result_label = tb.Label(
+            main,
+            text="Estimated Monthly Rent: —",
+            font=("Segoe UI", 18, "bold"),
+            foreground="#22c55e"
+        )
+        self.result_label.pack(pady=20)
+
+    def _add_field(self, parent, label, var, row):
+        tb.Label(parent, text=label).grid(row=row, column=0, sticky=W, pady=5)
+        tb.Entry(parent, textvariable=var).grid(row=row, column=1, sticky=EW, pady=5)
+        parent.columnconfigure(1, weight=1)
+
+    # ---------------------- ACTIONS ----------------------
+    def predict(self):
+        try:
+            size = self.size_var.get()
+            bhk = self.bhk_var.get()
+            bath = self.bath_var.get()
+            city = 1 if self.city_combo.get() == "Metro City" else 0
+
+            if size <= 0 or bhk <= 0 or bath <= 0:
+                raise ValueError
+
+        except:
+            messagebox.showerror("Invalid Input", "Please enter valid numeric values")
+            return
+
+        self.result_label.config(text="Estimating rent…")
+
+        worker = PredictionWorker(
+            self.model,
+            [size, bhk, bath, city],
+            self.show_result
+        )
+
+        threading.Thread(target=worker.run, daemon=True).start()
+
+    def show_result(self, rent, error=None):
+        if error:
+            messagebox.showerror("Prediction Error", error)
+            self.result_label.config(text="Estimated Monthly Rent: —")
+        else:
+            self.result_label.config(
+                text=f"Estimated Monthly Rent: ₹ {rent:,}"
+            )
+
+    # ---------------------- ABOUT ----------------------
+    def show_about(self):
+        messagebox.showinfo(
+            f"About {self.APP_NAME}",
+            f"{self.APP_NAME} v{self.APP_VERSION}\n\n"
+            "• Machine Learning powered rent estimation\n"
+            "• Clean enterprise-grade UI\n"
+            "• Threaded predictions (no UI freeze)\n"
+            "• Supports trained ML models\n\n"
+            "🏢 Built by Mate Technologies"
+        )
+
+    # ---------------------- RUN ----------------------
+    def run(self):
+        self.root.mainloop()
+
+
+# ---------------------- START ----------------------
+if __name__ == "__main__":
+    app = RentPredictorApp()
+    app.run()