LinkScrape is a dynamic application designed to extract and collect essential links from specific websites. It operates by traversing through the pages of a designated site, meticulously capturing the names of embedded links along with their respective addresses.
To contribute to this project, you need to fork the repository to your GitHub account. Follow the steps below:
- Fork the repository:
- Click on the "Fork" button at the top right of this page. This will create a copy of the repository in your GitHub account.
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Clone the repository:
git clone https://github.com/yourusername/Linkscrape.git
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Navigate to the project directory:
cd myproject
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Create a virtual environment:
python -m venv myenv
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Activate the virtual environment:
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On Windows:
.\myenv\Scripts\activate
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On Unix or MacOS:
source myenv/bin/activate
- To install all the requirements:
pip3 install -r requirements.txt
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Run the development server:
python manage.py runserver
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Visit
http://127.0.0.1:8000/
in your browser. -
Database Migrations:
python3 manage.py makemigrations python3 manage.py migrate
To contribute to the project, it's recommended to create a new branch for each feature or bug fix. Follow these steps:
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Create a new branch:
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Navigate to your project's directory:
cd Linkscrape
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Create a new branch for your changes:
git checkout -b feature-or-bugfix-branch
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Make changes:
- Make the necessary changes to the code, add new features, or fix bugs.
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Stage and commit your changes:
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Stage your changes:
git add .
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Commit your changes with a meaningful message:
git commit -m "Add your meaningful commit message here"
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Push your branch to your fork:
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Push your changes to your forked repository:
git push origin feature-or-bugfix-branch
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Submit a Pull Request:
- Go to your forked repository on GitHub.
- Click on "Compare & pull request" for the branch you just pushed.
- Fill in the pull request details and submit it.
Open for contributions. Just clone and follow the installation. Create an issue, make changes and raise a PR detailing about the changes made.
- Content based Filtering
- UI/UX enhancement
- AI driven tags
- File extraction in CSV, JSON
- Adding geolocation
- Analytical Dashboard
This project is licensed under the MIT License - see the LICENSE file for details.