{ "info": { "author": "Max Hully", "author_email": "max@mggg.org", "bugtrack_url": null, "classifiers": [ "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7" ], "description": "# Initial Reports\n\nThis Python package generates high-level overviews of spatial adjacency graphs.\nThe goal is to give the user visibility into any possible anamolies in their\nspatial data.\n\n## Installation\n\nYou can install this package from PyPI using `pip`:\n\n```console\npip install initial-report\n```\n\n## Usage\n\nIf you have the shapefile you're interested in saved at `./my_shapefile.shp`,\nyou can run\n\n```console\ninitial_report ./my_shapefile.shp\n```\n\nto generate a report, which will be saved as `output.html`.\n\n\n", "description_content_type": "text/markdown", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/mggg/initial-report", "keywords": "", "license": "", "maintainer": "", "maintainer_email": "", "name": "initial-report", "package_url": "https://pypi.org/project/initial-report/", "platform": "", "project_url": "https://pypi.org/project/initial-report/", "project_urls": { "Homepage": "https://github.com/mggg/initial-report" }, "release_url": "https://pypi.org/project/initial-report/0.1/", "requires_dist": [ "numpy", "pandas", "geopandas", "shapely", "maup", "gerrychain", "matplotlib", "jinja2" ], "requires_python": "", "summary": "High-level dashboard views of graphs and districting plans", "version": "0.1" }, "last_serial": 5502614, "releases": { "0.1": [ { "comment_text": "", "digests": { "md5": "8e089cb6facc45ba252f562e81007d3e", "sha256": "1eb7e1370da6ef3deaecde7705426187ec104617fd2083d97852f830055e357c" }, "downloads": -1, "filename": "initial_report-0.1-py3-none-any.whl", "has_sig": false, "md5_digest": "8e089cb6facc45ba252f562e81007d3e", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 8498, "upload_time": "2019-07-08T18:54:46", "url": "https://files.pythonhosted.org/packages/c9/24/2321da8b2da06ec6ef6953e8bd2656e69590c554f7c3ab2e1623499307fe/initial_report-0.1-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "4037e0e0f129d5b4f7714668b48013c0", "sha256": "99b3cc6c049caae4000c6acae6d119ad2ad858b18268ebda1942e7ba0b75c847" }, "downloads": -1, "filename": "initial_report-0.1.tar.gz", "has_sig": false, "md5_digest": "4037e0e0f129d5b4f7714668b48013c0", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 6240, "upload_time": "2019-07-08T18:54:48", "url": "https://files.pythonhosted.org/packages/da/03/84ef5a4a323b938c61b5edd18569054d1121b64d9dca42cccc1b13fd39e3/initial_report-0.1.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "8e089cb6facc45ba252f562e81007d3e", "sha256": "1eb7e1370da6ef3deaecde7705426187ec104617fd2083d97852f830055e357c" }, "downloads": -1, "filename": "initial_report-0.1-py3-none-any.whl", "has_sig": false, "md5_digest": "8e089cb6facc45ba252f562e81007d3e", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 8498, "upload_time": "2019-07-08T18:54:46", "url": "https://files.pythonhosted.org/packages/c9/24/2321da8b2da06ec6ef6953e8bd2656e69590c554f7c3ab2e1623499307fe/initial_report-0.1-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "4037e0e0f129d5b4f7714668b48013c0", "sha256": "99b3cc6c049caae4000c6acae6d119ad2ad858b18268ebda1942e7ba0b75c847" }, "downloads": -1, "filename": "initial_report-0.1.tar.gz", "has_sig": false, "md5_digest": "4037e0e0f129d5b4f7714668b48013c0", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 6240, "upload_time": "2019-07-08T18:54:48", "url": "https://files.pythonhosted.org/packages/da/03/84ef5a4a323b938c61b5edd18569054d1121b64d9dca42cccc1b13fd39e3/initial_report-0.1.tar.gz" } ] }