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Frequently Asked Questions
A: Lescatit is a project developed in Go, Mongo, Docker, and Kubernetes technologies, providing URL crawling and categorization functionality.
A: To install Lescatit, you can follow the installation guide provided in the Wiki.
A: Once the installation is complete, Lescatit automatically starts running. You can interact with Lescatit by making API requests to the available services.
A: Yes, contributions to Lescatit are welcome and encouraged. Refer to the Contributing Guidelines in the Wiki for more information on how to contribute.
A: The Lescatit Wiki serves as a comprehensive resource for information about Lescatit. You can find detailed documentation, installation guides, usage examples, troubleshooting tips, and more in the Wiki.
A: If you encounter any issues or difficulties while using Lescatit, you can refer to the Troubleshooting section in the Wiki. If you are still unable to resolve the issue, consider seeking help from the Lescatit community or project maintainers.
A: Lescatit is designed to provide URL crawling and categorization functionality. It enables users to retrieve content from URLs, categorize them, and generate classification models.
A: The API documentation for Lescatit can be found in the docs folder of the project repository. It provides detailed information about the available endpoints, request structure, and expected responses.
A: Yes, Lescatit offers flexibility for customization. You can define your own rules, categories, and classification models based on your specific requirements.
A: Yes, Lescatit is designed to support concurrent crawling of multiple URLs. It utilizes parallel processing techniques to optimize the crawling performance.
A: The frequency of updating the classification model depends on the dynamics of your data and the accuracy requirements. It is recommended to periodically evaluate the model's performance and update it as needed.
A: Yes, Lescatit is built to handle large-scale crawling tasks efficiently. It leverages distributed computing capabilities provided by technologies like Docker and Kubernetes to scale horizontally and handle high volumes of URLs.
A: Lescatit is designed to provide near real-time categorization capabilities. However, the actual response time depends on factors such as the size of the crawled content and the complexity of the classification rules.
A: Contributions to Lescatit are welcome! You can contribute by submitting bug reports, suggesting new features, or even creating pull requests. Refer to the Contributing Guidelines in the project repository for more details.
A: Yes, Lescatit provides APIs that allow integration with other systems or tools. You can utilize the API endpoints to fetch categorized URLs, retrieve classification models, or update URL categories programmatically.
A: You can find community support for Lescatit through the GitHub Discussions feature. The Lescatit GitHub repository hosts discussions where you can engage with other users, ask questions, and share your experiences. The project maintainers and the community actively participate in these discussions and provide assistance to users.
To access the discussions, visit the Lescatit GitHub Discussions page. You can browse through existing discussions or start a new one to seek help or share your insights. This is a valuable resource to connect with the Lescatit community and get support for any questions or issues you may have.
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Need help? Feel free to open an issue on GitHub.