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app.py

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+import streamlit as st
+
+# Dil seçimini kaydetmek için session_state kullanımı
+if "language" not in st.session_state:
+    st.session_state.language = None  # Başlangıçta dil seçimi yapılmamış
+
+# Eğer dil seçilmemişse, kullanıcıdan dil seçimi istenir
+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"
+
+# Dil seçimi yapılmışsa, uygun programı çalıştır
+else:
+    if st.session_state.language == "turkish":
+        import turkce  # Türkçe programı çağır
+    elif st.session_state.language == "english":
+        import english  # İngilizce programı çağır
+    elif st.session_state.language == "arabic":
+        import arabic  # Arapça programı çağır

arapca.py

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+import streamlit as st
+import re
+import numpy as np
+import matplotlib.pyplot as plt
+from io import BytesIO
+
+# 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: alicemilozdemir7@gmail.com")
+
+# 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)

ingilizce.py

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+import streamlit as st
+import re
+import numpy as np
+import matplotlib.pyplot as plt
+from io import BytesIO
+
+# 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 alicemilozdemir7@gmail.com")
+
+# 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)

turkce.py

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+import streamlit as st
+import re
+import numpy as np
+import matplotlib.pyplot as plt
+from io import BytesIO
+
+# 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 alicemilozdemir7@gmail.com")
+
+# 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)