{ "info": { "author": "Henry Senyondo, Andrew Zhang, Ethan White", "author_email": "ethan@weecology.org", "bugtrack_url": null, "classifiers": [ "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Operating System :: Microsoft :: Windows", "Operating System :: POSIX", "Operating System :: Unix", "Programming Language :: Python", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: Implementation :: PyPy", "Topic :: Database", "Topic :: Scientific/Engineering :: GIS", "Topic :: Scientific/Engineering :: Information Analysis", "Topic :: Software Development :: Libraries :: Python Modules" ], "description": "\"logo\"\n\n[![Build Status](https://api.travis-ci.org/weecology/pydataweaver.svg?branch=master)](https://travis-ci.org/weecology/pydataweaver)\n[![Build status (windows)](https://ci.appveyor.com/api/projects/status/x9a6ol3dl5mf2wr7/branch/master?svg=true)](https://ci.appveyor.com/project/ethanwhite/pydataweaver/branch/master)\n[![Documentation Status](https://readthedocs.org/projects/pydataweaver/badge/?version=latest)](http://pydataweaver.readthedocs.io/en/latest/?badge=latest)\n[![License](http://img.shields.io/badge/license-MIT-blue.svg)](https://raw.githubusercontent.com/weecology/pydataweaver/master/LICENSE)\n[![Join the chat at https://gitter.im/weecology/pydataweaver](https://badges.gitter.im/weecology/pydataweaver.svg)](https://gitter.im/weecology/retriever?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)\n\n# The Pydata Weaver Project\n\nThe Pydataweaver is a Python tool that offers a simple to use, clean and a robust data integration platform.\n\nThe PydataWeaver supports data integration of spatial datasets (Raster and Vector data), as well as tabular datasets.\n\nProblem solving in science involves and requires studying entities using a broad range of associations among the entities under study. These associations are obtained through collecting and integrating various sources and forms of data.\n\nSince these heterogenous datasets are collected by various scientists, the datasets are domain based or centered around a unique subset of problems.\n\nThe pydataweaver bridges the gap scientist's face of not having readily unified datasets that can be used for multi dimension feature analysis. The data weaver handles the finding and integration of heterogeneous datasets forming a new dataset.\n\nDependencies\n------------\n\nThis package requires Python 3.5+, recommends Python 3.6+ and depends on the following packages:\n\n retriever\n PyMySQL>=0.4\n psycopg2-binary\n gdal\n future\n numpydoc\n pandas\n\n\nThey can be installed using ``pip``.\n\n```shell\n sudo pip install -r requirements.txt\n```\n\nThe package supports the following database management systems (DBMS):\n\n| DBMS | Spatial Datasets | Tabular Datasets |\n|------------|-----------------:|-----------------:|\n| PostgreSQL | Yes | Yes |\n| SQLite | No | Yes |\n\nInstalling\n----------\n\n```shell\n pip install pydataweaver\n```\n\nInstalling From Source\n----------------------\n\nEither use pip to install directly from GitHub:\n\n```shell\n pip install git+https://git@github.com/weecology/pydataweaver.git\n```\n\nor:\n\n1. Clone the repository\n2. From the directory containing setup.py, run the following command: `pip\n install .`. You may need to include `sudo` at the beginning of the\n command depending on your system (i.e., `sudo pip install .`).\n\nMore extensive documentation for those that are interested in developing can be found [here](http://pydataweaver.readthedocs.io/en/latest/?badge=latest)\n\nUsing the Command Line\n----------------------\n\nAfter installing the package, run `pydataweaver` update to download the latest available dataset scripts.\nTo see the full list of command line options and datasets run `pydataweaver --help`.\n\n$ pydataweaver --help\n\n```shell\n\n usage: pydataweaver [-h] [-v] [-q] {help,ls,citation,license,join,update} ...\n\n positional arguments:\n {help,ls,citation,license,join,update}\n sub-command help\n help\n ls display a list all available datasets\n citation view citation\n license view dataset licenses\n join integrate data using a data package script\n update download updated versions of data package scripts\n\n optional arguments:\n -h, --help show this help message and exit\n -v, --version show program's version number and exit\n -q, --quiet suppress command-line output\n\n```\n\nTo get a list of available dataset use `pydataweaver ls`\n\n$ pydataweaver ls\n\n```shell\n\n Available datasets : 11\n\n breed-bird-routes-bioclim\n mammal-community-bioclim\n mammal-community-masses\n mammal-community-sites-all-bioclim\n mammal-community-sites-bioclim\n mammal-community-sites-harvard-linear-features\n mammal-community-sites-harvard-linear-features-soils\n mammal-community-sites-harvard-soil\n mammal-diet-mammal-life-history\n mammal-sites-bioclim-1-2\n portal-plot-species\n\n .\n ...\n```\n\nTo view the citaion of the datasets use `pydataweaver citation [dataset-name]\nRunning pydataweaver with no citation will provide the citation for the tool.\n\n\n`$ pydataweaver citation mammal-diet-mammal-life-history`\n\n```shell\n\n Dataset: mammal-diet-mammal-life-history\n Description: Integrated data set of mammal-life-hist and mammal-diet\n Citations:\n mammal-life-hist: S. K. Morgan Ernest. 2003. ....\n mammal-diet: Kissling WD, Dalby L, Flojgaard C, Lenoir J, ...\n\n```\n\nIntegrating Data\n----------------\nTo integrate data, run pydataweaver join [data package name] and provide the connection configurations.\n\n\n```shell\n\n pydataweaver join postgres -h\n usage: pydataweaver join postgres [-h] [--user [USER]] [--password [PASSWORD]]\n [--host [HOST]] [--port [PORT]]\n [--database [DATABASE]]\n [--database_name [DATABASE_NAME]]\n [--table_name [TABLE_NAME]]\n dataset\n\n positional arguments:\n dataset file name\n\n optional arguments:\n -h, --help show this help message and exit\n --user [USER], -u [USER]\n Enter your PostgreSQL username\n --password [PASSWORD], -p [PASSWORD]\n Enter your password\n --host [HOST], -o [HOST]\n Enter your PostgreSQL host\n --port [PORT], -r [PORT]\n Enter your PostgreSQL port\n --database [DATABASE], -d [DATABASE]\n Enter your PostgreSQL database name\n --database_name [DATABASE_NAME], -a [DATABASE_NAME]\n Format of schema name\n --table_name [TABLE_NAME], -t [TABLE_NAME]\n Format of table name\n\n```\n\nTo use the pydataweaver with postges .pgpass file set\n\n```shell\n pydataweaver join postgres\n```\n\nor with command line configurations supplied\n\n```shell\n pydataweaver join postgres -u name-of-user -h host-name -d database-to-use\n```\n\nContribution\n------------\n\nIf you find any operation that is not supported by this package, feel free to create a Github issue. Additionally, you are more than welcome to submit a pull request for a bug fix or additional feature.\n\nIf you find any operation that is not supported by this package, feel\nfree to create a Github issue. Additionaly you are more than welcome to submit\na pull request for a bug fix or additional feature.\n\nPlease take a look at the [Code of Conduct](https://github.com/weecology/pydataweaver/blob/master/docs/code_of_conduct.rst) governing contributions to this project.\n\nAcknowledgments\n---------------\n\nDevelopment of this software was funded by [the Gordon and Betty Moore\nFoundation's Data-Driven Discovery\nInitiative](http://www.moore.org/programs/science/data-driven-discovery) through [Grant GBMF4563](http://www.moore.org/grants/list/GBMF4563) to Ethan White.\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/weecology/pydataweaver", "keywords": "", "license": "", "maintainer": "", "maintainer_email": "", "name": "pydataweaver", "package_url": "https://pypi.org/project/pydataweaver/", "platform": "", "project_url": "https://pypi.org/project/pydataweaver/", "project_urls": { "Homepage": "https://github.com/weecology/pydataweaver" }, "release_url": "https://pypi.org/project/pydataweaver/1.0.0/", "requires_dist": [ "xlrd", "future", "argcomplete" ], "requires_python": "", "summary": "Pydata Weaver", "version": "1.0.0" }, "last_serial": 5507536, "releases": { "1.0.0": [ { "comment_text": "", "digests": { "md5": "73f0019b94170ef08eb8914396d96533", "sha256": "ee5c3d5667e5f6f4951a1ca68434c70e22cc17a32d8c5a058a1c21bb5cdd576b" }, "downloads": -1, "filename": "pydataweaver-1.0.0-py3-none-any.whl", "has_sig": false, "md5_digest": "73f0019b94170ef08eb8914396d96533", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 38848, "upload_time": "2019-07-09T14:30:10", "url": "https://files.pythonhosted.org/packages/65/af/3eae5488a41923e7dcf8bd70717a9f5f9144f1e60121e58b77e91e14230d/pydataweaver-1.0.0-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "7e05d79f3397458d6cc6f5d99b3c8cf2", "sha256": "c57c371adf2f7fdd5443d21979e1c0617a226440230961e683119013ddd0f6a4" }, "downloads": -1, "filename": "pydataweaver-1.0.0.tar.gz", "has_sig": false, "md5_digest": "7e05d79f3397458d6cc6f5d99b3c8cf2", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 37452, "upload_time": "2019-07-09T14:30:12", "url": "https://files.pythonhosted.org/packages/46/6d/50127d58a09b5f9be457256c58824d0e2f2b271b22ae33ddc2580797754a/pydataweaver-1.0.0.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "73f0019b94170ef08eb8914396d96533", "sha256": "ee5c3d5667e5f6f4951a1ca68434c70e22cc17a32d8c5a058a1c21bb5cdd576b" }, "downloads": -1, "filename": "pydataweaver-1.0.0-py3-none-any.whl", "has_sig": false, "md5_digest": "73f0019b94170ef08eb8914396d96533", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 38848, "upload_time": "2019-07-09T14:30:10", "url": "https://files.pythonhosted.org/packages/65/af/3eae5488a41923e7dcf8bd70717a9f5f9144f1e60121e58b77e91e14230d/pydataweaver-1.0.0-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "7e05d79f3397458d6cc6f5d99b3c8cf2", "sha256": "c57c371adf2f7fdd5443d21979e1c0617a226440230961e683119013ddd0f6a4" }, "downloads": -1, "filename": "pydataweaver-1.0.0.tar.gz", "has_sig": false, "md5_digest": "7e05d79f3397458d6cc6f5d99b3c8cf2", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 37452, "upload_time": "2019-07-09T14:30:12", "url": "https://files.pythonhosted.org/packages/46/6d/50127d58a09b5f9be457256c58824d0e2f2b271b22ae33ddc2580797754a/pydataweaver-1.0.0.tar.gz" } ] }