cdncheck is a Go library and CLI tool for identifying whether an IP address or domain belongs to a CDN, WAF, or cloud provider. It uses embedded CIDR range data (compiled from ASN, URL, and static CIDR sources) and efficient IP matching via the `bart` radix tree. The library provides a clean `Client` interface with methods like `CheckCDN`, `CheckCloud`, `CheckWAF`, and `CheckDomainWithFallback` that also resolve DNS and check CNAME suffixes. The CLI wraps this with input/output handling, filtering, and JSON output. The codebase is well-structured, with clear separation between core logic, data generation, and CLI runner. It is actively maintained by ProjectDiscovery and used in their security scanning ecosystem.
The sentinel2-cloud-detector repository provides a Python package (s2cloudless) for detecting clouds in Sentinel-2 satellite imagery. It implements a pixel-based cloud detector using a pre-trained LightGBM model that takes Sentinel-2 spectral bands as input and outputs cloud probability maps or binary masks with optional post-processing (convolution and dilation). The package is designed as a reusable library for integration into remote sensing workflows. The architecture consists of three core modules: cloud_detector.py (containing the main S2PixelCloudDetector class), pixel_classifier.py (a generic wrapper for applying pixel-wise classifiers over image data), and utils.py (helper functions for data loading and image processing operations). The PixelClassifier class is particularly notable for its reusability, as it decouples the classification logic from the specific model and can work with any classifier adhering to the scikit-learn API (e.g., scikit-learn models, LightGBM). The package includes comprehensive unit tests, CI/CD pipelines for multiple Python versions, and follows modern packaging standards for distribution via PyPI and Conda. The package actively maintains compatibility with current dependencies (lightgbm, numpy, opencv, sentinelhub) and avoids deprecated APIs. It demonstrates strong software engineering practices through clear separation of concerns, type hints, and comprehensive documentation. While the S2PixelCloudDetector class is tailored to the specific cloud detection use case, the underlying PixelClassifier utility represents a broadly applicable pattern for pixel-wise image classification tasks.