📚 Study Tracker Dashboard

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A beautiful and personalized 📈 Study Progress Dashboard built using Streamlit with secure authentication. Designed for students preparing for any exam — to track daily goals, visualize subject-wise progress, and maintain consistency using real data, session-wise scheduling, and performance metrics.

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🚀 Live Demo

👉 LIVE APP!

📌 Main Dashboard View

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🖼️ Screenshots

🔍 Additional Views

Feature	Screenshot
🔐 Login Page 1
🔐 Login Page 2
🗓️ Main Dashboard
🗓️ Today’s Plan
✅ Daily Completion
📊 Time Usage
📈 Comparison Chart
📉 Analysis Table
📋 Tracker Grid
📦 Overall Summary
🧭 Time Distribution

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🔑 Features

• 🔐 Login & Registration using SQLite (users.db) with streamlit_authenticator
• 📅 Auto-Traced Study Sessions with date-driven scheduling
• ✅ Checkbox Grid to mark each session as done
• 📊 Subject-Wise Progress with donut & bar charts
• ⏳ Backlog Tracker for missed subjects
• 🔁 Auto-Rerun Logic before session starts
• 🧠 Per-user JSON Save State for progress
• 🧾 Daily Completion Table with tick marks
• 📌 Reset Button to start over anytime

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🗂️ Directory Structure

📁 study-tracker/

    ├── study\_tracker\_final.py             # Streamlit main app

    ├── auth\_db.py                           # SQLite-based authentication

    ├── users.db                             # Registered users stored here

    ├── \*.json                               # User progress files (per user)

    ├── credentials.yaml                     # (Optional) legacy credentials

    ├── Study\_Plan\_Schedule.csv              # Timetable (days × session slots)

    ├── Subject\_Study\_Time\_Table.csv         # Subjects with video hours

    ├── requirements.txt                     # Python dependencies

    └── README.md                            # You're reading it 🙂

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🛠️ Installation

1️⃣ Clone the Repo

git clone https://github.com/MohitGupta0123/Study_Tracker.git
cd Study_Tracker

2️⃣ Install Requirements

pip install -r requirements.txt

3️⃣ Run the App

streamlit run study_tracker_final.py --server.port 8501

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🧠 Tech Stack

• Frontend: Streamlit
• Auth: streamlit_authenticator + SQLite (users.db)
• Charts: Matplotlib
• Data Processing: Pandas, JSON
• Storage: CSV files for study data, JSON for user progress

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📁 Data Files

File	Description
Study_Plan_Schedule.csv	Weekly plan (Day-wise × Sessions)
Subject_Study_Time_Table.csv	Subjects with total video hours
<username>_progress.json	Per-user saved checkbox state

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📈 Dashboard Features in Action

📅 Today's Work

• Auto-detects what you need to study today based on the real calendar

🔁 Auto Rerun

• Reruns app 5 mins before session start to alert you

🧾 Progress Tracker Grid

• Tick off what you’ve studied; persists even after reload

🍩 Donut Charts

• See your completion % for each subject

🟥 Backlogs

• Automatically shows what you've missed in previous days

📊 Time Slot Analytics

• Frequency of time slots used across your plan

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📸 Visual Elements

• ✅ Checkbox table for sessions per day
• 📊 Bar chart for session frequency
• 🟡 Today's plan
• 🔴 Backlogs
• 📅 Dynamic live clock
• 📈 Donut & pie charts showing progress distribution

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🔐 Authentication System

• Uses SQLite-based DB (users.db) for login/signup
• Passwords are hashed using streamlit_authenticator
• Each user has their own progress file (<username>_progress.json)

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🙌 Acknowledgements

• Thanks to streamlit_authenticator for easy auth integration
• Inspired by real preparation needs of students
• Created with 💙 using Python and Streamlit

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👤 Author

• Mohit Gupta

  🔗 LinkedIn

  📧 Email

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🌟 Support

If this helped you stay productive and consistent, please ⭐️ this repo and share it with your peers!

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