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This compact tool enables extraction and analysis of information from open-source projects on GitHub using both REST and GraphQL APIs, providing an efficient way to save and examine data.

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rukivbruki/GitHub-Data-Extractor-Analyzer

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LAUNCH OF CONTAINERIZED APPLICATION:

Console utility:

  1. Clone the repository.
  2. Obtain an access token on the GitHub platform (https://docs.github.com/en/free-pro-team@latest/github/authenticating-to-github/creating-a-personal-access-token).
  3. Add a .env file in the root folder of the backend and include the directive TOKEN = your_token.
  4. Create and run the application container (do not close the tab):
    • docker-compose build
    • docker-compose up
  5. In a new tab from the project directory, run the command docker ps and copy the ID of the running container (container_ID).
  6. Run the command docker exec -it container_ID /bin/bash.
  7. Run the command npm run crawler. Note: To successfully save data to the local machine, you need to grant Docker access to the folder where MongoDB saves data. In our case, this is: /usr/local/var/mongodb

Web client:

  1. Follow steps 1-3 from the console application launch instruction.
  2. Go to http://localhost:8080/ and use the web interface to start the application.

LAUNCH OF LOCAL APPLICATION:

Console utility:

  1. Install the npm package manager, Node.js platform, and MongoDB database in your system.
  2. Start MongoDB.
  3. Follow steps 1-3 from the containerized application launch instruction.
  4. From the backend folder, run the command node service/service --crawler (you can specify the logging level as the second parameter, for example, DEBUG or ERROR).

Web client:

  1. Install the npm package manager, Node.js platform, and MongoDB database in your system.
  2. Start MongoDB.
  3. Follow steps 1-3 from the containerized application launch instruction.
  4. From the backend folder, run the command node service/service --server (you can specify the logging level as the second parameter, for example, DEBUG or ERROR).
  5. From the frontend folder, run the command npm run serve.
  6. Go to http://localhost:8080/ and use the web interface to start the application.

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This compact tool enables extraction and analysis of information from open-source projects on GitHub using both REST and GraphQL APIs, providing an efficient way to save and examine data.

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