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It demonstrates modern scraping patterns including:\n* **Dynamic Scraping:** Using `Playwright` to handle JavaScript-heavy museum viewers.\n* **IIIF Integration:** Extracting maximum-resolution images directly from IIIF servers (bypassing web thumbnails).\n* **Metadata Normalization:** converting messy museum HTML into structured JSONL datasets.\n* **Async Concurrency:** Fast, non-blocking downloads using `asyncio`.\n\n---\n\n## 📂 Supported Institutions\n\nEach script is a standalone tool targeting a specific digital archive architecture.\n\n| Institution | Script | Tech Stack | Key Features |\n| :--- | :--- | :--- | :--- |\n| **Pitt Rivers Museum** | `scrapers/run_pitt_rivers.py` | `Playwright`, `AsyncIO` | • **IIIF Max-Res Extraction**\u003cbr\u003e• Bypasses \"Sensitive Content\" popups\u003cbr\u003e• Hybrid Search + Scraping |\n| **British Museum** | `scrapers/run_british_museum.py` | `Pandas`, `Requests` | • **CSV-driven extraction**\u003cbr\u003e• Handles \"Preview\" quality access\u003cbr\u003e• Metadata mapping |\n| **MAA Cambridge** | `scrapers/run_maa_cambridge.py` | `Playwright` | • **Dynamic JS Navigation**\u003cbr\u003e• Deep metadata (Context, Photographer)\u003cbr\u003e• Multi-view image linking |\n| **G.I. Jones Archive** | `scrapers/run_gijones.py` | `BeautifulSoup` | • Static site traversing\u003cbr\u003e• Gallery iteration |\n| **Ukpuru Blog** | `scrapers/run_ukpuru.py` | `BeautifulSoup` | • Blogspot/Blogger parsing\u003cbr\u003e• Unstructured text extraction |\n\n---\n\n## 🚀 Installation\n\n### 1. Clone the Repository\n```bash\ngit clone https://github.com/Nwokike/museum-scrapers-python.git\ncd museum-scrapers-python\n\n```\n\n### 2. Install Dependencies\n\nThis project relies on `playwright` for dynamic sites and `pandas` for data handling.\n\n```bash\npip install -r requirements.txt\n\n```\n\n### 3. Install Browser Engines\n\nRequired for the MAA and Pitt Rivers scrapers.\n\n```bash\nplaywright install chromium\n\n```\n\n---\n\n## 📖 Usage Examples\n\nEach scraper is designed to be run independently.\n\n### Example 1: Scraping the Pitt Rivers Museum\n\nThis script navigates the search results for a specific query (e.g., \"Igbo\") and extracts high-res IIIF images.\n\n```bash\npython scrapers/run_pitt_rivers.py\n\n```\n\n*Output:* Creates a `data_pitt_rivers/` folder with `images/` and `data.jsonl`.\n\n### Example 2: Processing British Museum Data\n\nPlace your CSV export (`british_museum.csv`) in the folder before running.\n\n```bash\npython scrapers/run_british_museum.py\n\n```\n\n---\n\n## ⚖️ Ethics \u0026 Legal Disclaimer\n\n**Please scrape responsibly.**\n\n1. **Respect Rate Limits:** These scripts are powerful. Do not overwhelm museum servers. Use `time.sleep()` intervals (included in scripts) to be a polite bot.\n2. **Copyright:**\n* **The Code:** This repository is open source (MIT License). You can use the *code* freely.\n* **The Data:** The *content* you scrape (images, text) is subject to the copyright terms of the respective institutions (e.g., \"© Trustees of the British Museum\", \"CC BY-NC-ND 4.0\").\n\n\n3. **Usage:** This tool is for **educational and research purposes**. Do not use scraped data for commercial products without obtaining proper licenses from the source institutions.\n\n---\n\n## 🤝 Contributing\n\nWe welcome contributions! If you have built a scraper for another museum (e.g., The Met, Smithsonian, Quai Branly), please submit a Pull Request.\n\n1. Fork the repo.\n2. Create your scraper in `scrapers/run_NEW_SOURCE.py`.\n3. Ensure it outputs structured `JSONL` and separates images into an `/images` folder.\n\n---\n\n## 📝 License\n\nThis project is licensed under the **MIT License** - see the [LICENSE](LICENSE) file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnwokike%2Fmuseum-scrapers-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnwokike%2Fmuseum-scrapers-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnwokike%2Fmuseum-scrapers-python/lists"}