Delete app.py

app.py

@@ -1,512 +0,0 @@
-import streamlit as st
-import re
-import numpy as np
-import matplotlib.pyplot as plt
-from io import BytesIO
-
-def run_turkish():
-    # Başlık
-    st.title("Note Analyzer Streamlit Uygulaması")
-
-    # Uygulamanın çalışma prensibi görüntüleme durumu
-    if "show_images" not in st.session_state:
-        st.session_state.show_images = True  # Varsayılan olarak resimler gösterilsin
-
-    # Kullanıcıdan veri alma (Sidebar sabit kalıyor)
-    st.sidebar.header("Girdi Alanları")
-
-    # Dosya yükleme veya metin girişi seçimi
-    input_method = st.sidebar.radio(
-        "Notları nasıl gireceksiniz?",
-        options=["Dosya Yükle", "Kopyala-Yapıştır"]
-    )
-
-    uploaded_file = None
-    text_input = None
-
-    if input_method == "Dosya Yükle":
-        uploaded_file = st.sidebar.file_uploader("Notlar Dosyasını Yükleyin (TXT)", type=["txt"])
-    elif input_method == "Kopyala-Yapıştır":
-        text_input = st.sidebar.text_area("Notları Yapıştırın", height=200)
-
-    # Diğer parametreler
-    lecture_name = st.sidebar.text_input("Ders Adı", value="Ders Adı")
-    perfect_score = st.sidebar.number_input("Sınav Puanı Üst Limiti", value=100, step=1)
-    my_note = st.sidebar.number_input("Benim Notum", value=0.0, step=0.1)
-    note_s_axis_diff = st.sidebar.number_input("Notlar X Ekseni Ortak Farkı", value=5, step=1)
-    amount_s_axis_diff = st.sidebar.number_input("Miktar Y Ekseni Ortak Farkı", value=1, step=1)
-    first_step = st.sidebar.number_input("İlk Adım", value=0, step=1)
-    increase_amount = st.sidebar.number_input("Artış Miktarı", value=1, step=1)
-
-    if st.sidebar.button("Analizi Çalıştır"):
-        # Butona basıldığında resimleri gizle
-        st.session_state.show_images = False
-
-    # Resimler yalnızca show_images True ise gösterilir
-    if st.session_state.show_images:
-        st.subheader("Uygulamanın Çalışma Prensibi")
-
-        # Resimlerin dosya isimlerini sırayla listele
-        image_files = ["turkish/a.png", "turkish/b.png", "turkish/c.png", "turkish/d.png"]
-
-        # Resimleri alt alta ekle
-        for image_file in image_files:
-            st.image(image_file, use_container_width=True)
-
-    # Notları yükleme ve işleme işlemleri (Butona basıldıysa çalışır)
-    if not st.session_state.show_images:
-        if input_method == "Dosya Yükle" and uploaded_file is None:
-            st.error("Lütfen bir dosya yükleyin!")
-        elif input_method == "Kopyala-Yapıştır" and not text_input:
-            st.error("Lütfen notları metin kutusuna yapıştırın!")
-        else:
-            try:
-                # Dosya veya metin kutusundan içerik okuma
-                if uploaded_file:
-                    content = uploaded_file.read().decode("utf-8")
-                elif text_input:
-                    content = text_input
-
-                # Veriyi işleme
-                result = re.split(r'[ \n]+', content)
-
-                # Strip fonksiyonu ve kaçış dizisi temizliği
-                notes_result = [x.strip() for x in result[first_step::increase_amount] if x.strip() != '∅' and x.strip() != "NA"]
-                notes_result = list(map(lambda x: float(x), notes_result))
-                notes_result = np.array(notes_result)
-
-                # İstatistikler
-                average_x = np.average(notes_result)
-                min_x = notes_result.min()
-                max_x = notes_result.max()
-                std = np.std(notes_result)
-                z_score = (my_note - average_x) / std
-
-                # İstatistikleri ekrana yazdırma
-                st.subheader("Genel Bilgiler")
-                st.write(f"Katilimci Sayısı: {len(notes_result)}")
-                st.write(f"En Düşük Not: {min_x:.2f}")
-                st.write(f"En Yüksek Not: {max_x:.2f}")
-                st.write(f"Ortalama Not: {average_x:.2f}")
-                st.write(f"Standart Sapma: {std:.2f}")
-                st.write(f"Z-Skoru: {z_score:.2f}")
-
-                # Grafik oluşturma
-                st.subheader("Not Dağılım Grafiği")
-                unique_values, counts = np.unique(notes_result, return_counts=True)
-                plt.figure(figsize=(10, 6))
-                bars = plt.bar(unique_values, counts, width=0.3)
-                plt.axvline(x=average_x, color='red', linestyle='--')
-                plt.text(average_x + 1.5, max(counts), 'Ortalama Not', color='red', rotation=0, ha='center', va='bottom')
-
-                if my_note in unique_values:
-                    plt.text(my_note, counts[unique_values == my_note][0], 'Benim\nNotum', color='green', rotation=0, ha='center', va='bottom')
-
-                for bar in bars:
-                    if bar.get_x() <= my_note < bar.get_x() + bar.get_width():
-                        bar.set_color('green')
-
-                plt.title(f'{lecture_name} Not Sayıları Grafiği')
-                plt.xlabel('Notlar')
-                plt.ylabel('Adet')
-                plt.xticks(range(0, int(perfect_score), note_s_axis_diff), rotation=90)
-                plt.yticks(range(0, max(counts), amount_s_axis_diff), rotation=0)
-
-                # Grafik bilgileri
-                info_text = (
-                    f"Katilimci sayısı: {len(notes_result)}\n"
-                    f"En düşük not: {min_x:.2f}\n"
-                    f"En yüksek not: {max_x:.2f}\n"
-                    f"Benim notum: {my_note:.2f}\n"
-                    f"Ortalama not: {average_x:.2f}\n"
-                    f"Standart sapma: {std:.2f}\n"
-                    f"Z-skoru: {z_score:.2f}"
-                )
-                plt.text(
-                    1.05 * max(unique_values), 0.8 * max(counts),
-                    info_text,
-                    fontsize=10,
-                    color="black",
-                    ha="left",
-                    va="top",
-                    bbox=dict(boxstyle="round,pad=0.3", edgecolor="blue", facecolor="lightgrey")
-                )
-                plt.subplots_adjust(left=0.055, bottom=0.065, right=0.90, top=0.962, wspace=0.2, hspace=0.2)
-
-                # Grafik gösterimi
-                st.pyplot(plt)
-
-                # Grafik indirme bağlantısı
-                buf = BytesIO()
-                plt.savefig(buf, format="png")
-                buf.seek(0)
-                st.download_button(
-                    label="Grafiği İndir",
-                    data=buf,
-                    file_name="not_dagilimi.png",
-                    mime="image/png"
-                )
-
-            except Exception as e:
-                st.error(f"Hata: {e}")
-
-    # Web sayfasının altına isim ve tarih
-    st.markdown("---")
-    st.write("Developed by: Ali Cemil Özdemir")
-    st.write("Date: 01.12.2024")
-    st.write("For feedback and suggestions, you can contact me at [email protected]")
-
-    # Grafiklerin sağ alt köşesine yazı ekleme
-    st.markdown("""
-        <p style="position:absolute; bottom:0px; right:0px; font-size: 12px; color: gray;">
-            Created with Note Analyzer
-        </p>
-        """, unsafe_allow_html=True)
-
-
-def run_arabic():
-    # العنوان
-    st.title("تطبيق محلل الدرجات باستخدام Streamlit")
-
-    # حالة عرض الصور
-    if "show_images" not in st.session_state:
-        st.session_state.show_images = True  # الافتراضي: يتم عرض الصور
-
-    # منطقة إدخال البيانات في الشريط الجانبي
-    st.sidebar.header("حقول الإدخال")
-
-    # اختيار رفع ملف أو إدخال النصوص يدويًا
-    input_method = st.sidebar.radio(
-        "كيف ستقدم الدرجات؟",
-        options=["رفع ملف", "نسخ ولصق"]
-    )
-
-    uploaded_file = None
-    text_input = None
-
-    if input_method == "رفع ملف":
-        uploaded_file = st.sidebar.file_uploader("قم برفع ملف الدرجات (TXT)", type=["txt"])
-    elif input_method == "نسخ ولصق":
-        text_input = st.sidebar.text_area("قم بلصق الدرجات هنا", height=200)
-
-    # المعلمات الأخرى
-    lecture_name = st.sidebar.text_input("اسم المادة", value="اسم المادة")
-    perfect_score = st.sidebar.number_input("الدرجة الكاملة", value=100, step=1)
-    my_note = st.sidebar.number_input("درجتي", value=0.0, step=0.1)
-    note_s_axis_diff = st.sidebar.number_input("حجم خطوات المحور السيني للدرجات", value=5, step=1)
-    amount_s_axis_diff = st.sidebar.number_input("حجم خطوات المحور الصادي للتكرار", value=1, step=1)
-    first_step = st.sidebar.number_input("الخطوة الأولى", value=0, step=1)
-    increase_amount = st.sidebar.number_input("مقدار الزيادة", value=1, step=1)
-
-    if st.sidebar.button("تشغيل التحليل"):
-        # إخفاء الصور عند النقر على الزر
-        st.session_state.show_images = False
-
-    # عرض الصور فقط إذا كانت show_images صحيحة
-    if st.session_state.show_images:
-        st.subheader("كيفية عمل التطبيق")
-
-        # قائمة بأسماء ملفات الصور بالترتيب
-        image_files = ["arabic/a.png", "arabic/b.png", "arabic/c.png", "arabic/d.png"]
-
-        # عرض الصور واحدة تحت الأخرى
-        for image_file in image_files:
-            st.image(image_file, use_container_width=True)
-
-    # تحميل ومعالجة الدرجات (يعمل فقط إذا تم النقر على الزر)
-    if not st.session_state.show_images:
-        if input_method == "رفع ملف" and uploaded_file is None:
-            st.error("يرجى رفع ملف!")
-        elif input_method == "نسخ ولصق" and not text_input:
-            st.error("يرجى لصق الدرجات في مربع النص!")
-        else:
-            try:
-                # قراءة المحتوى من الملف أو مربع النص
-                if uploaded_file:
-                    content = uploaded_file.read().decode("utf-8")
-                elif text_input:
-                    content = text_input
-
-                # معالجة البيانات
-                result = re.split(r'[ \n]+', content)
-
-                # تنظيف وتصنيف البيانات
-                notes_result = [x.strip() for x in result[first_step::increase_amount] if x.strip() != '∅' and x.strip() != "NA"]
-                notes_result = list(map(lambda x: float(x), notes_result))
-                notes_result = np.array(notes_result)
-
-                # الإحصائيات
-                average_x = np.average(notes_result)
-                min_x = notes_result.min()
-                max_x = notes_result.max()
-                std = np.std(notes_result)
-                z_score = (my_note - average_x) / std
-
-                # عرض الإحصائيات
-                st.subheader("المعلومات العامة")
-                st.write(f"عدد المشاركين: {len(notes_result)}")
-                st.write(f"أقل درجة: {min_x:.2f}")
-                st.write(f"أعلى درجة: {max_x:.2f}")
-                st.write(f"متوسط الدرجات: {average_x:.2f}")
-                st.write(f"الانحراف المعياري: {std:.2f}")
-                st.write(f"درجة Z: {z_score:.2f}")
-
-                # إنشاء الرسم البياني
-                st.subheader("رسم توزيع الدرجات")
-                unique_values, counts = np.unique(notes_result, return_counts=True)
-                plt.figure(figsize=(10, 6))
-                bars = plt.bar(unique_values, counts, width=0.3)
-                plt.axvline(x=average_x, color='red', linestyle='--')
-                plt.text(average_x + 1.5, max(counts), 'متوسط الدرجات', color='red', rotation=0, ha='center', va='bottom')
-
-                if my_note in unique_values:
-                    plt.text(my_note, counts[unique_values == my_note][0], 'درجتي', color='green', rotation=0, ha='center', va='bottom')
-
-                for bar in bars:
-                    if bar.get_x() <= my_note < bar.get_x() + bar.get_width():
-                        bar.set_color('green')
-
-                plt.title(f'رسم توزيع الدرجات لمادة {lecture_name}')
-                plt.xlabel('الدرجات')
-                plt.ylabel('التكرار')
-                plt.xticks(range(0, int(perfect_score), note_s_axis_diff), rotation=90)
-                plt.yticks(range(0, max(counts), amount_s_axis_diff), rotation=0)
-
-                # إضافة معلومات إلى الرسم البياني
-                info_text = (
-                    f"عدد المشاركين: {len(notes_result)}\n"
-                    f"أقل درجة: {min_x:.2f}\n"
-                    f"أعلى درجة: {max_x:.2f}\n"
-                    f"درجتي: {my_note:.2f}\n"
-                    f"متوسط الدرجات: {average_x:.2f}\n"
-                    f"الانحراف المعياري: {std:.2f}\n"
-                    f"درجة Z: {z_score:.2f}"
-                )
-                plt.text(
-                    1.05 * max(unique_values), 0.8 * max(counts),
-                    info_text,
-                    fontsize=10,
-                    color="black",
-                    ha="left",
-                    va="top",
-                    bbox=dict(boxstyle="round,pad=0.3", edgecolor="blue", facecolor="lightgrey")
-                )
-                plt.subplots_adjust(left=0.055, bottom=0.065, right=0.90, top=0.962, wspace=0.2, hspace=0.2)
-
-                # عرض الرسم البياني
-                st.pyplot(plt)
-
-                # زر لتحميل الرسم البياني
-                buf = BytesIO()
-                plt.savefig(buf, format="png")
-                buf.seek(0)
-                st.download_button(
-                    label="تحميل الرسم البياني",
-                    data=buf,
-                    file_name="score_distribution.png",
-                    mime="image/png"
-                )
-
-            except Exception as e:
-                st.error(f"خطأ: {e}")
-
-    # التذييل
-    st.markdown("---")
-    st.write("تم التطوير بواسطة: علي جميل أوزدمير")
-    st.write("التاريخ: 01.12.2024")
-    st.write("للتعليقات والاقتراحات، يمكنك التواصل عبر: [email protected]")
-
-    # إضافة ملاحظة أسفل الزاوية اليمنى
-    st.markdown("""
-        <p style="position:absolute; bottom:0px; right:0px; font-size: 12px; color: gray;">
-            تم الإنشاء باستخدام محلل الدرجات
-        </p>
-        """, unsafe_allow_html=True)
-
-
-def run_english():
-    # Title
-    st.title("Note Analyzer Streamlit Application")
-
-    # Image display state
-    if "show_images" not in st.session_state:
-        st.session_state.show_images = True  # Default: images are shown
-
-    # Sidebar input area
-    st.sidebar.header("Input Fields")
-
-    # File upload or text input selection
-    input_method = st.sidebar.radio(
-        "How will you provide the notes?",
-        options=["Upload File", "Copy-Paste"]
-    )
-
-    uploaded_file = None
-    text_input = None
-
-    if input_method == "Upload File":
-        uploaded_file = st.sidebar.file_uploader("Upload the Notes File (TXT)", type=["txt"])
-    elif input_method == "Copy-Paste":
-        text_input = st.sidebar.text_area("Paste the Notes Here", height=200)
-
-    # Other parameters
-    lecture_name = st.sidebar.text_input("Course Name", value="Course Name")
-    perfect_score = st.sidebar.number_input("Maximum Exam Score", value=100, step=1)
-    my_note = st.sidebar.number_input("My Score", value=0.0, step=0.1)
-    note_s_axis_diff = st.sidebar.number_input("Score X-Axis Step Size", value=5, step=1)
-    amount_s_axis_diff = st.sidebar.number_input("Frequency Y-Axis Step Size", value=1, step=1)
-    first_step = st.sidebar.number_input("First Step", value=0, step=1)
-    increase_amount = st.sidebar.number_input("Step Increase", value=1, step=1)
-
-    if st.sidebar.button("Run Analysis"):
-        # Hide images when the button is clicked
-        st.session_state.show_images = False
-
-    # Show images only if show_images is True
-    if st.session_state.show_images:
-        st.subheader("How the Application Works")
-
-        # List the image filenames in order
-        image_files = ["english/a.png", "english/b.png", "english/c.png", "english/d.png"]
-
-        # Display images one below the other
-        for image_file in image_files:
-            st.image(image_file, use_container_width=True)
-
-    # Load and process notes (Only works if the button is clicked)
-    if not st.session_state.show_images:
-        if input_method == "Upload File" and uploaded_file is None:
-            st.error("Please upload a file!")
-        elif input_method == "Copy-Paste" and not text_input:
-            st.error("Please paste the notes into the text area!")
-        else:
-            try:
-                # Read content from file or text area
-                if uploaded_file:
-                    content = uploaded_file.read().decode("utf-8")
-                elif text_input:
-                    content = text_input
-
-                # Process the data
-                result = re.split(r'[ \n]+', content)
-
-                # Clean and filter the data
-                notes_result = [x.strip() for x in result[first_step::increase_amount] if x.strip() != '∅' and x.strip() != "NA"]
-                notes_result = list(map(lambda x: float(x), notes_result))
-                notes_result = np.array(notes_result)
-
-                # Statistics
-                average_x = np.average(notes_result)
-                min_x = notes_result.min()
-                max_x = notes_result.max()
-                std = np.std(notes_result)
-                z_score = (my_note - average_x) / std
-
-                # Display statistics
-                st.subheader("General Information")
-                st.write(f"Number of Participants: {len(notes_result)}")
-                st.write(f"Lowest Score: {min_x:.2f}")
-                st.write(f"Highest Score: {max_x:.2f}")
-                st.write(f"Average Score: {average_x:.2f}")
-                st.write(f"Standard Deviation: {std:.2f}")
-                st.write(f"Z-Score: {z_score:.2f}")
-
-                # Create plot
-                st.subheader("Score Distribution Graph")
-                unique_values, counts = np.unique(notes_result, return_counts=True)
-                plt.figure(figsize=(10, 6))
-                bars = plt.bar(unique_values, counts, width=0.3)
-                plt.axvline(x=average_x, color='red', linestyle='--')
-                plt.text(average_x + 1.5, max(counts), 'Average Score', color='red', rotation=0, ha='center', va='bottom')
-
-                if my_note in unique_values:
-                    plt.text(my_note, counts[unique_values == my_note][0], 'My\nScore', color='green', rotation=0, ha='center', va='bottom')
-
-                for bar in bars:
-                    if bar.get_x() <= my_note < bar.get_x() + bar.get_width():
-                        bar.set_color('green')
-
-                plt.title(f'{lecture_name} Score Distribution')
-                plt.xlabel('Scores')
-                plt.ylabel('Count')
-                plt.xticks(range(0, int(perfect_score), note_s_axis_diff), rotation=90)
-                plt.yticks(range(0, max(counts), amount_s_axis_diff), rotation=0)
-
-                # Add graph information
-                info_text = (
-                    f"Number of participants: {len(notes_result)}\n"
-                    f"Lowest score: {min_x:.2f}\n"
-                    f"Highest score: {max_x:.2f}\n"
-                    f"My score: {my_note:.2f}\n"
-                    f"Average score: {average_x:.2f}\n"
-                    f"Standard deviation: {std:.2f}\n"
-                    f"Z-score: {z_score:.2f}"
-                )
-                plt.text(
-                    1.05 * max(unique_values), 0.8 * max(counts),
-                    info_text,
-                    fontsize=10,
-                    color="black",
-                    ha="left",
-                    va="top",
-                    bbox=dict(boxstyle="round,pad=0.3", edgecolor="blue", facecolor="lightgrey")
-                )
-                plt.subplots_adjust(left=0.055, bottom=0.065, right=0.90, top=0.962, wspace=0.2, hspace=0.2)
-
-                # Display the plot
-                st.pyplot(plt)
-
-                # Download button for the plot
-                buf = BytesIO()
-                plt.savefig(buf, format="png")
-                buf.seek(0)
-                st.download_button(
-                    label="Download Graph",
-                    data=buf,
-                    file_name="score_distribution.png",
-                    mime="image/png"
-                )
-
-            except Exception as e:
-                st.error(f"Error: {e}")
-
-    # Footer
-    st.markdown("---")
-    st.write("Developed by: Ali Cemil Özdemir")
-    st.write("Date: 01.12.2024")
-    st.write("For feedback and suggestions, you can contact me at [email protected]")
-
-    # Add a note at the bottom right corner of the page
-    st.markdown("""
-        <p style="position:absolute; bottom:0px; right:0px; font-size: 12px; color: gray;">
-            Created with Note Analyzer
-        </p>
-        """, unsafe_allow_html=True)
-
-# Session State'i başlat
-if "language" not in st.session_state:
-    st.session_state.language = None
-
-# Dil seçimi ekranı
-if st.session_state.language is None:
-    st.title("Select language / Dili seçin / اختر اللغة")
-    col1, col2, col3 = st.columns(3)
-
-    with col1:
-        if st.button("Türkçe"):
-            st.session_state.language = "turkish"
-    with col2:
-        if st.button("English"):
-            st.session_state.language = "english"
-    with col3:
-        if st.button("عربي"):
-            st.session_state.language = "arabic"
-
-# Seçilen dilin programını çalıştır
-else:
-    if st.session_state.language == "turkish":
-        run_turkish()
-    elif st.session_state.language == "english":
-        run_english()
-    elif st.session_state.language == "arabic":
-        run_arabic()