122 lines
2.3 KiB
Plaintext
122 lines
2.3 KiB
Plaintext
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# Local Movie Database
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A clean, fast, and fully offline web application to browse and search your personal movie database (built from TMDB data).
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The app displays movies in a beautiful card-based interface with posters, ratings, release years, full language names, and descriptions. Everything runs locally on your machine.
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---
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## Features
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* Beautiful movie cards with TMDB posters
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* Search by title or keyword
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* Filter by:
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* Genre (multi-select)
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* Language (shows full names like "English", "Japanese", "Greek", etc.)
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* Minimum rating
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* Minimum vote count
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* Year range
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* "Load More" button — loads 100 movies at a time
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* No artificial result limit — you can keep loading until all matching results are shown
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* Fully responsive 4-column layout
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* Completely local (no data sent online)
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---
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## Requirements
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* Python 3.10 or higher
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* `streamlit`
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* `pandas`
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* A prepared SQLite database file named `movies.db` (≈1.4 million movies)
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---
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## Installation
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### 1. Clone the repository
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```
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git clone <your-repo-url>
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cd movie-project
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```
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### 2. Install dependencies
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```
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pip install streamlit pandas
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```
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Or using the requirements file:
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```
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pip install -r requirements.txt
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```
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### 3. Add your database
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Place your `movies.db` file in the root folder (same directory as `movie_app.py`).
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**Important:** The database must contain a table named `movies` with at least these columns:
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* `title`
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* `release_date`
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* `vote_average`
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* `vote_count`
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* `overview`
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* `original_language`
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* `poster_path`
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* `genres`
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* `popularity`
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### 4. Run the app
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```
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streamlit run movie_app.py
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```
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The application will automatically open in your default web browser.
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---
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## Project Structure
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```
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movie-project/
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├── movie_app.py
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├── movies.db
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├── README.md
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├── requirements.txt
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└── .gitignore
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```
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---
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## requirements.txt
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```
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streamlit
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pandas
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```
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---
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## Notes
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* The first search may take a few seconds while the genre list is built.
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* Movie posters are loaded from TMDB’s public image server: [https://image.tmdb.org](https://image.tmdb.org)
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* You can keep clicking "Load More" until all matching results are displayed.
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* Best performance when the database has been cleaned (adult content removed).
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---
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## Tech Stack
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* UI Framework: Streamlit
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* Database: SQLite
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* Data Processing: pandas
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* Data Source: TMDB movie dataset
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