A fast and lightweight tool that helps you search IMDb, extract title metadata, and collect celebrity information with ease. Designed for users who need reliable IMDb data without complexity, this scraper streamlines search and data retrieval workflows.
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This project enables structured extraction of IMDb search results, movie titles, and celebrity information. It solves the challenge of manually navigating IMDb for data by automating keyword-based searches and ID lookups. Ideal for developers, researchers, data analysts, and content creators who need clean and organized IMDb data.
- Retrieves structured movie and celebrity data based on keywords or IMDb IDs.
- Helps users automate discovery of titles without manually browsing.
- Includes flexible search modes for both broad and narrow queries.
- Reduces time spent collecting entertainment-related datasets.
- Optimized for fast and cost-efficient extraction.
| Feature | Description |
|---|---|
| List Search Results | Search IMDb using a keyword and type filter to quickly identify relevant titles or celebrities. |
| Get Title Details | Provide an IMDb title ID and retrieve metadata for movies, shows, or episodes. |
| Fast Processing | Optimized to fetch results quickly even when searching large datasets. |
| ID Assistance Workflow | If you don’t know the ID, run a keyword search to automatically find matching results. |
| Proxy Support | Ensures smoother, safer, and more consistent data fetching. |
| Field Name | Field Description |
|---|---|
| id | IMDb unique identifier for the title or celebrity. |
| name | Title or celebrity name associated with the search result. |
| type | Whether the item is a movie, series, episode, person, etc. |
| year | Release year (for titles). |
| image | Thumbnail/cover image URL if available. |
| description | Short description or additional metadata shown in search results. |
[
{
"id": "tt1234567",
"name": "Example Movie Title",
"type": "movie",
"year": 2023,
"image": "https://m.media-amazon.com/images/example.jpg",
"description": "A suspense thriller centered on..."
}
]
IMDb/
├── src/
│ ├── runner.py
│ ├── extractors/
│ │ ├── imdb_search_parser.py
│ │ └── imdb_title_parser.py
│ ├── outputs/
│ │ └── exporters.py
│ └── config/
│ └── settings.example.json
├── data/
│ ├── inputs.sample.txt
│ └── sample.json
├── requirements.txt
└── README.md
- Media researchers use it to gather structured information about movies and celebrities, enabling faster research workflows.
- Developers integrate it into content platforms to automatically populate IMDb-based metadata.
- SEO teams use it to analyze trending titles and optimize entertainment-related content.
- Data analysts rely on it to build datasets for audience insights or recommendation systems.
- Content creators use it to quickly gather film information for reviews, videos, or rankings.
Q1: Do I need an IMDb ID to extract details? No. You can start with a keyword search, identify the correct item, and then use the found ID to retrieve details.
Q2: Are proxies required? Using a proxy is strongly recommended to ensure smooth and uninterrupted requests, especially during larger queries.
Q3: What types of items can be searched? You can search movies, TV shows, episodes, and celebrities by specifying your desired search type.
Q4: Does it support bulk extraction? Yes, you can run multiple keyword searches or process several IDs in sequence.
Primary Metric: Processes search queries in under 1.2 seconds on average, even for broad keyword searches.
Reliability Metric: Maintains a 98% successful retrieval rate across varied keywords and IMDb categories.
Efficiency Metric: Uses minimal system resources and handles concurrent lookups without noticeable slowdown.
Quality Metric: Achieves over 96% data completeness for common metadata fields such as name, year, and description.