{"categories":[{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/3"}],"enrichment":{"capability":"Computes travel times and spatial access metrics at scale for millions of origin-destination pairs across walking, biking, and driving modes, plus measures like provider-to-people ratios and floating catchment areas.","skillfed_tags":["geospatial-analysis","accessibility-metrics","network-routing"],"use_cases":["Measure healthcare facility accessibility by computing average travel times from residential locations to nearest providers.","Analyze food desert coverage by calculating provider-to-people ratios for grocery stores using floating catchment area methods.","Evaluate transit equity by generating travel time matrices for walking and biking routes to employment centers.","Assess school accessibility by computing catchment areas and counting nearby schools within travel time thresholds.","Model geographic disparities in service access by comparing weighted accessibility scores across regions."],"what_it_does":"spatial_access is a geospatial analysis library that calculates travel times and accessibility metrics for large sets of coordinate pairs. It splits into two main submodules: p2p generates many-to-many travel time matrices across walking, biking, and driving networks, while Models computes spatial accessibility measures like average time to nearest provider, provider-to-people ratios, and two-stage floating catchment areas. The package is built on a heavy stack of geospatial and scientific dependencies (geopandas, shapely, rtree, scipy, scikit-learn) and requires compiled spatial indexing libraries at the system level.\n\nThe package is designed for bulk computation and is typically used in public health, urban planning, and equity research to measure access to amenities. However, the project has been abandoned since 2022-01-11 with no active maintenance, meaning dependency conflicts, Python version incompatibilities, and unresolved bugs are likely on modern systems.","worth_installing":"No, unless maintaining legacy code. The package is abandoned (last update 2022-01-11, 1676 days without commits), carries 17 heavy dependencies prone to version conflicts, requires system-level compilation, and has no Python version support specification. For new projects, seek actively maintained alternatives. If you must use it, expect significant dependency resolution work and thorough testing."},"id":"spatial-access","links":{"html":"https://skillfed.io/packages/spatial-access","md":"https://skillfed.io/packages/spatial-access.md","pypi":"https://pypi.org/project/spatial-access/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2022-01-11","license_spdx":null,"license_treatment":"permissive","name":"spatial-access","python_support":"unspecified","summary":null},"popularity":{"monthly_downloads":152147,"position":10910,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.0.2"}