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        "description": "# spatial_access: Compute travel times and spatial access metrics at scale\nCompute travel times and spatial access measures at scale (millions of origin-destination pairs in minutes). \nTravel times for three modes: walking, biking, driving. \nSpatial access measures: provider-to-people ratio, avg. time to nearest provider, count/attribute sum of nearby providers, weighted access scores and floating catchment areas.\n<table>\n<tr>\n  <td>Latest Release</td>\n  <td>\n    <a href=\"https://pypi.org/project/spatial-access/\">\n    <img src=\"https://img.shields.io/pypi/v/spatial-access.svg\" alt=\"latest release\" />\n    </a>\n  </td>\n</tr>    \n<tr>\n  <td>Build Status</td>\n  <td>\n    <a href=\"https://travis-ci.org/GeoDaCenter/spatial_access\">\n    <img src=\"https://travis-ci.org/GeoDaCenter/spatial_access.svg?branch=master\" alt=\"travis build status\" />\n  </td>\n</tr>\n\n<tr>\n  <td>Documentation</td>\n  <td>\n      <a href=\"https://readthedocs.org/projects/spatial-acccess\">\n    <img src=\"https://readthedocs.org/projects/spatial-acccess/badge\" alt=\"read the docs\" />\n  </td>\n</tr>\n\n<tr>\n  <td>Tested Operating Systems</td>\n  <td>\n       Ubuntu, macOS\n  </td>\n</tr>\n</table>\n\n\nComponents of spatial_access :\n----\nspatial_access has two submodules:\n- p2p: Generate many to many matrices with travel times for sets of coordinates. Use `walk` ,`bike` or `drive` network types (import `transit` from other sources), or get the distance in meters.\n- Models: Contains a suite of models for calculating spatial accessibility to amenities.\n \nTo use this service as a ReST API, see: https://github.com/GeoDaCenter/spatial_access_api \n\nIf you are a Windows user, instructions for installing Ubuntu on a virtual machine are at the bottom of the Readme.\n\n\nInstallation \n----\n0. A modern compiler like `gcc` or `clang`.\n\n1. Dependencies \n\n    - MacOS:\n\n        `brew install spatialindex`\n\n    - Ubuntu:\n\n        `sudo apt-get install libspatialindex-dev`\n    \n        `sudo apt-get install python-tk`\n \n2. Package \n\n    `pip3 install spatial_access`\n\n\nUsage\n---\nSee the iPython notebooks in `docs/` for example usage, or https://readthedocs.org/projects/spatial-acccess/ for technical documentation.\n\n### Overwriting default configuration values\np2p provides default configuration values for edge weights and node impedence (see spatial_access/configs.py).\nYou can overwrite these as follows:\n```\nfrom spatial_access.p2p import TransitMatrix\nfrom spatial_access.Configs import Configs\ncustom_config = Configs()\n# set fields of custom_cofig\ntm = TransitMatrix(..., configs=custom_config)\n# continue with computation \n```\n\n\nMaintainance\n---\n\n### Instructions for building locally (only for developers):\n\n- Additional requirements: `cython` and `jinja2`\n- To regenerate .pyx files, run: `bash cythonize_extension.sh` (TravisCI will do this automatically on deployment)\n- To install locally, run: `sudo python3 setup.py install ` from spatial_access root directory\n- Unit tests require the `pytest` package. From package root directory, run `python3 -m pytest tests/` to run all unit tests.\n\n### PyPi Maintenance\nThe package lives at: `https://pypi.org/project/spatial-access/`\n\nWhen a branch is pulled into Master and builds/passes all unit tests,\nTravis CI will automatically deploy the build to PyPi. \n\n\nTo update PyPi access credentials, see .travis.yml and follow the instructions at https://docs.travis-ci.com/user/deployment/pypi/\nto generate a new encrypted password.\n\n\n### Installing Ubuntu 18 LTS with dependencies from scratch (recommended for Windows users)\n\n1. Follow the instructions at this link: https://linus.nci.nih.gov/bdge/installUbuntu.html to set up a virtual machine\n2. `sudo apt-get update`\n3. `sudo add-apt-repository universe`\n4. `sudo apt-get -y install python3-pip`\n5. Continue with Installation Instructions (above)\n\n### Questions/Feedback?\n\nlnoel@uchicago.edu or spatial@uchicago.edu\n\n### Acknowledgments\n\nDeveloped by Logan Noel at the University of Chicago's Center for Spatial Data Science (CSDS) with support from the Public Health National Center for Innovations (PHNCI), the University of Chicago, and CSDS.",
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