Merge pull request 'Kasia_test' (#1) from Kasia_test into master

Reviewed-on: #1

CenaMieszkaniaDesign.py

@@ -0,0 +1,79 @@
+from tkinter import *
+import joblib
+import pandas as pd
+
+root = Tk()
+
+def calculate_price():
+    # Get the selected values and entry input
+    stan = selected_stan.get()
+    liczba_pokoi = selected_liczba_pokoi.get()
+    metraz = entry1.get()
+    rynek = selected_rynek.get()
+
+    # Create a dictionary with the data
+    data = {'stan': [stan], 'l pokoi': [liczba_pokoi], 'metraż': [metraz], 'rynek': [rynek]}
+    
+    # Create a DataFrame from the dictionary
+    X = pd.DataFrame(data)
+
+    # Load the model and make predictions
+    loaded_model = joblib.load('ridge_model.sav')
+    result = loaded_model.predict(X)
+    result = result / float(metraz)
+
+    # Display the result
+    result_label.config(text=f"Predicted Price: {result[0]:.2f} PLN")
+    result_label.grid(row=6, column=1, padx=10, pady=5)
+
+
+root.geometry("500x500")
+root.title("Mieszkaneo")
+
+root.maxsize(900, 600)
+root.config(bg="#C3DEED")
+
+label1 = Label(root, text="Metraż", font=('Arial', 18))
+label1.grid(row=0, column=0, padx=10, pady=5)
+entry1 = Entry(root, font=('Arial', 18))
+entry1.grid(row=1, column=0, padx=10, pady=5)
+
+label2 = Label(root, text="Rynek", font=('Arial', 18))
+label2.grid(row=0, column=1, padx=10, pady=5)
+rynek_options = ["pierwotny", "wtórny"]
+selected_rynek = StringVar()
+selected_rynek.set(rynek_options[0])
+
+rynek_menu = OptionMenu(root, selected_rynek, *rynek_options)
+rynek_menu.config(font=('Arial', 18), bg='white', fg='black')  # Kolory tła i tekstu
+rynek_menu.grid(row=1, column=1, padx=10, pady=5)
+
+label3 = Label(root, text="Stan", font=('Arial', 18))
+label3.grid(row=2, column=0, padx=10, pady=5)
+stan_options = ["do zamieszkania", "do wykończenia","do remontu"]
+selected_stan = StringVar()
+selected_stan.set(stan_options[0])
+
+stan_menu = OptionMenu(root, selected_stan, *stan_options)
+stan_menu.config(font=('Arial', 18), bg='white', fg='black')  # Kolory tła i tekstu
+stan_menu.grid(row=3, column=0, padx=10, pady=5)
+
+label4 = Label(root, text="Liczba Pokoi", font=('Arial', 18))
+label4.grid(row=2, column=1, padx=10, pady=5)
+liczba_pokoi_options = [str(i) for i in range(1, 5)]
+selected_liczba_pokoi = StringVar()
+selected_liczba_pokoi.set(liczba_pokoi_options[0])
+
+liczba_pokoi_menu = OptionMenu(root, selected_liczba_pokoi, *liczba_pokoi_options)
+liczba_pokoi_menu.config(font=('Arial', 18), bg='white', fg='black')  # Kolory tła i tekstu
+liczba_pokoi_menu.grid(row=3, column=1, padx=10, pady=5)
+
+button = Button(root, text="Oblicz cenę mieszkania", font=('Arial', 18), command=calculate_price)
+button.config(bg='green', fg='white')  # Kolory tła i tekstu
+button.grid(row=4, columnspan=2, padx=10, pady=10)
+
+result_label = Label(root, text="", font=('Arial', 18))
+result_label.grid(row=5, columnspan=2, padx=10, pady=5)
+
+
+root.mainloop()

Jenkinsfile

@@ -0,0 +1,23 @@
+pipeline {
+    agent {
+        docker { image 'python:3.10.6-slim-bullseye' }
+    }
+
+    stages {
+        stage('Build') {
+            steps {
+                echo 'Building..'
+            }
+        }
+        stage('Test') {
+            steps {
+                sh 'check_flat_price.py'
+            }
+        }
+        stage('Deploy') {
+            steps {
+                echo 'Deploying....'
+            }
+        }
+    }
+}

README.md

@@ -1,5 +1,5 @@
 # Projekt_wyceny_mieszkan
-Systemy Informatyczne - Laboratorium 1
+## Systemy Informatyczne - Laboratorium 1
 
 Lider - Katarzyna Pierzyńska
 
@@ -25,13 +25,13 @@ Typ pracownika: A1
 
 Bartłomiej jest pracownikiem nastawionym na wykonanie zadania i posuwającym pracę do przodu. Motywuje go widoczny postęp wykonywanej pracy, lubi efektywnie wykorzystywać czas na wykonanie zadania i widzieć efekty swoich działań. Preferuje implementować swoje pomysły w życie i dopiero później rozwijać projekt o dalsze pomysły.
 
-Podręcznik użytkownika do zadania 2
+## Podręcznik użytkownika do zadania 2
 
-1. W celu uruchomienia programu przewidującego ceny mieszkania na podstawie jego podstawowych parametrów należy wejść w następujący link: https://colab.research.google.com/drive/1RDqiXalAJSScjc-JrW60DFmOZ9uExp97?usp=sharing .
+1. W celu uruchomienia programu przewidującego ceny mieszkania na podstawie jego podstawowych parametrów należy wejść w plik: Lab1_zad2.ipynb.
 
 2. Następnie należy uruchomić program poprzez wciśnięcie przycisku run lub poprzez skrót klawiszowy Ctrl + Enter.
 
-Podręcznik użytkownika do zadania 3
+## Podręcznik użytkownika do zadania 3
 
 1. Aplikacja Mieszkaneo pozwala na łatwe, szybkie i dostosowane do indywidualnych potrzeb znalezienie mieszkania na sprzedaż.
 

check_flat_price.py

@@ -0,0 +1,8 @@
+import pandas as pd
+import numpy as np
+
+ceny = pd.read_csv('expected.tsv', sep='\t', header=None)
+
+for cena in ceny:
+    if cena < 0:
+        print("cena ujemna, sprawdz cene")

dev-0/expected.tsv

@@ -0,0 +1,462 @@
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test-A/out.tsv

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