/QLReplicaonVAdata

An attempt at a replica working version of the Queenslander (by Whitelaw) Generous interface but using the V&A api. This obvioulsy has restictions and work aournds. This is created as a learning curve of how these features are created and work as part of a genrous interface.

Primary LanguageHTML


Logo

Replica Queenslander Generous Interface for V&A collection

This is a replica of the Queenslander Generous Interface for the V&A collection. The data is sourced from the V&A API and cached in a local JSON file. The idea for reproducing is to both learn about the features of generating a generous interface and to provide a useful tool for exploring the V&A collection. By using the api it has also raised a few issues (data clarity and consistency and also api request limits) to consider when createing generous interfaces.

(back to top)

Getting Started

To set up this project locally, follow these steps:

Prerequisites

  • Python 3.7+
  • pip (Python package installer)

Installation

  1. Clone the repo 
    git clone https://github.com/walshd/QLReplicaonVAdata
  2. Navigate to the project directory 
    cd QLReplicaonVAdata
  3. Create a virtual environment 
    python -m venv venv
  4. Activate the virtual environment 
    # On Windows
venv\Scripts\activate
# On macOS and Linux
source venv/bin/activate
  5. Install required packages 
    pip install -r requirements.txt
  6. Run the Flask application 
    flask run

The application should now be running on http://localhost:5000.

(back to top)

Usage

This Flask-based application provides a generous interface (attempt at a replica f Whitelaws Queenslander interface) for exploring the V&A collection. Here are some ways to use it:

  1. Open your web browser and navigate to http://localhost:5000.
  2. Browse the collection by category, material, or time period.
  3. Use the search function to find specific items or themes.
  4. Click on individual items to view detailed information and high-resolution images.
  5. Use the timeline feature to explore the collection chronologically.

The data is sourced from the V&A API and cached locally to improve performance and manage API request limits.

(back to top)

Roadmap

  • Basic Flask application setup
  • V&A API integration
  • Local data caching implementation
  • Add item grid view feature
  • Add timeline visualization feature
  • [-] Add wordcloud visualization feature
  • Improve UI/UX design
  • Optimize performance for large datasets
  • Add unit tests and integration tests

See the open issues for a full list of proposed features (and known issues).

(back to top)

License

Distributed under the MIT License. See LICENSE.txt for more information.

(back to top)

Contact

Your Name - @twitter_handle - email@email_client.com

Project Link: https://github.com/github_username/repo_name

(back to top)

Acknowledgments

(back to top)