{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/4"}],"enrichment":{"capability":"fastdtw computes approximate Dynamic Time Warping (DTW) alignments between sequences with linear O(N) time and memory complexity, returning both the distance and alignment path.","skillfed_tags":["time-series","sequence-alignment","algorithm"],"use_cases":["Compare time-series data to find similarity despite temporal distortions.","Align sequences for preprocessing in signal or pattern recognition workflows.","Match gesture or motion sequences for action recognition tasks.","Cluster or classify sequences where timing variations exist but overall shape should match.","Detect anomalies by computing DTW distance between a test sequence and a reference baseline."],"what_it_does":"fastdtw is a Python implementation of the FastDTW algorithm, an approximate Dynamic Time Warping method that aligns two sequences while maintaining linear time and memory complexity. Unlike standard DTW which has quadratic complexity, fastdtw trades some accuracy for speed, producing optimal or near-optimal alignments suitable for time-series comparison tasks.\n\nThe package depends on numpy and accepts sequences as arrays, computing both the alignment distance and the path that maps one sequence to the other. You provide a distance function to measure point-to-point dissimilarity. The project has not been actively maintained since 2019, so it is stable but receives no updates.","worth_installing":"Yes, if you need fast approximate DTW for time-series alignment and can accept a stable but unmaintained package. The algorithm is well-established, the code is relatively simple, and there are no known vulnerabilities. Install friction is moderate due to compiled wheels. Suitable for research, prototyping, and production use where DTW is the right tool and you do not require ongoing maintenance."},"id":"fastdtw","links":{"html":"https://skillfed.io/packages/fastdtw","md":"https://skillfed.io/packages/fastdtw.md","pypi":"https://pypi.org/project/fastdtw/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2019-10-07","license_spdx":null,"license_treatment":"permissive","name":"fastdtw","python_support":"unspecified","summary":"Dynamic Time Warping (DTW) algorithm with an O(N) time and memory complexity."},"popularity":{"monthly_downloads":482686,"position":6421,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.3.4"}