access
Calculate spatial accessibility metrics.
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has no known vulnerabilities, installs with low friction, and uses a permissive license. It fills a specific niche in spatial analysis with a stable API and clear documentation. Install it if you need to compute accessibility metrics; skip it if your workflow doesn't involve measuring service proximity.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.11 or later; geopandas and scipy must be installed for spatial operations.
- Low friction install with a pure Python wheel.
- Active maintenance with recent commits and a stable production-ready status.
License · maintenance · safety
BSD 3-Clause (permissive) — BSD 3-Clause permissive license allows commercial and private use with minimal restrictions.
last release 2025-12-12 (245 days) · last repo commit 2026-05-11 · 27 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 104,415 downloads/mo, #12,750 on PyPI
Alternatives
Verify before relying
pip install access
import access
# Use geopandas and pandas to load spatial data, then call accessibility measures
import geopandas as gpd
import pandas as pd- Specific accessibility measures available (classical vs. novel methods not detailed in excerpt)
- Performance characteristics with large datasets or high-dimensional spatial data
- Integration patterns with common GIS workflows beyond basic import
What it is and what it does
Access is a spatial analysis package that computes measures of how accessible services are from different geographic locations. It builds on geopandas, numpy, pandas, and scipy to work with spatial data and calculate both established and novel accessibility metrics. The package is part of the PySAL ecosystem and targets researchers, educators, and developers working with geographic information systems and spatial statistics.
You would use this package when you need to quantify service accessibility—for instance, measuring how far residents are from hospitals, schools, or transit hubs, or analyzing whether service distribution is equitable across a region. It handles the spatial calculations required to turn geographic coordinates and service locations into accessibility indices.
Use it for
- Measure hospital or healthcare facility accessibility for urban planning and equity analysis.
- Analyze public transit accessibility to identify underserved neighborhoods.
- Evaluate school or educational facility distribution and reachability across a region.
- Assess food desert conditions by measuring distance to grocery stores or markets.
- Support research on spatial inequality and service distribution patterns.
- Benchmark accessibility improvements after infrastructure changes.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has no known vulnerabilities, installs with low friction, and uses a permissive license. It fills a specific niche in spatial analysis with a stable API and clear documentation. Install it if you need to compute accessibility metrics; skip it if your workflow doesn't involve measuring service proximity.
Install
access on PyPI
Before you install
Low friction install with a pure Python wheel. Active maintenance with recent commits and a stable production-ready status.
Requires Python 3.11 or later; geopandas and scipy must be installed for spatial operations.
License in practice
BSD 3-Clause permissive license allows commercial and private use with minimal restrictions.
Quickstart
pip install access
import access
# Use geopandas and pandas to load spatial data, then call accessibility measures
import geopandas as gpd
import pandas as pdVerify before relying
- Specific accessibility measures available (classical vs. novel methods not detailed in excerpt)
- Performance characteristics with large datasets or high-dimensional spatial data
- Integration patterns with common GIS workflows beyond basic import
Package facts
| License | BSD 3-Clause permissive |
| Python support | Supports the current Python release >=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesgeopandasnumpypandasscipy |
| Maintenance | Actively maintained 245 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 104,415 / month, #12,750 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Science/ResearchLicense :: OSI Approved :: BSD LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3Topic :: Scientific/Engineering :: GIS |
Evidence: access-1.1.10.post3-py3-none-any.whl
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See also inequality · spatial-access · pysal · segregation · cityseer · spm-calculator · momepy · arcgis · esda · libpysal