[DMANET] New Python package: HITSpy: High-Performance Tabu Search in Python - max score estimator

Dear all, I would like to announce that the Python package HITSpy is available on GitHub, a sister project to the recently announced R package HITSr. The aim is to compute efficiently the maximum score estimator of Manski (1975) in Python, with C++ under the hood for efficiency using OpenMP parallelization. The package supports large sample size and number of parameters. It uses the Hyperplanes Intersection Tabu Search Algorithm (Florios et al., 2025). The Python package is designed to work just like HITSr R package, but for Python users. Key technical features: - Feature 1: HITS algorithm, https://doi.org/10.1016/j.softx.2025.102164, added OpenMP functionality during the neighborhood exploration step - Feature 2: C++ under the hood for efficiency, Python interface for ease of use - Feature 3: pybind11 integration - Feature 4: Solves the estimation of Manski (1975) estimator, https://doi.org/10.1016/0304-4076(75)90032-9, without proving optimality, but supports large datasets (sample size, number of parameters) - Feature 5: Multiple-start runs demo example is provided in Python Repository: https://github.com/kflorios/hitspy Feedback on API design, portability, accuracy and speed is welcome. Best regards, Kostas Florios PhD Operational Research National Technical University of Athens ********************************************************** * * Contributions to be spread via DMANET are submitted to * * DMANET@zpr.uni-koeln.de * * Replies to a message carried on DMANET should NOT be * addressed to DMANET but to the original sender. The * original sender, however, is invited to prepare an * update of the replies received and to communicate it * via DMANET. * * DISCRETE MATHEMATICS AND ALGORITHMS NETWORK (DMANET) * http://www.zaik.uni-koeln.de/AFS/publications/dmanet/ * **********************************************************