{ "info": { "author": "Severin Langberg", "author_email": "langberg91@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Environment :: Console", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Natural Language :: English", "Programming Language :: Python :: 3" ], "description": "Installation_ | Usage_ | License_\n\n\n##################\npydavis\n##################\n\nA package intended the logging of weather data parameters monitored by\nDavis weather stations. The parameters are obtained through the reports\ngenerated at Davis WeatherLink websites, and can be streamed to a *MySQL*\ndatabase or a specified file.\n\n\n************\nInstallation\n************\n\nThe package can be installed with `pip `_\n\n.. code-block:: bash\n\n pip install pydavis\n\n\n*****\nUsage\n*****\n\nThrough the ``data_logging.py`` module, the weather parameters are\nstreamed from `WeatherLink `__ websites::\n\n >>> from data_logging import DataLogger\n\nBy instantiating the ``DataLogger`` with an URL, the logging sequence can then\nbe initiated and data stored according to specified format. Any logging\nsequence is aborted with ``CTRL + C``.\n\n**Storing data in a MySQL database**\n\n.. code-block:: python\n\n >>> logger = DataLogger(url)\n >>> logger.initiate_logging(to_table=True,\n user='user',\n password='password',\n database='pydavis',\n table='weather_data')\n\nThe necessary arguments are *MySQL* login credentials, the name of the database\nand the table. The ``logger`` will create the database and the table if\nnecessary.\n\n**Storing data in a file**\n\n.. code-block:: python\n\n >>> logger = DataLogger(url)\n >>> logger.initiate_logging(to_file=True,\n path_to_file='./weather_data.csv')\n\nThe location including the name of the file must be passed as argument.\nThe ``logger`` will create a new file if necessary.\n\n*******\nLicense\n*******\n\nMIT, see `MIT license `_.\n\n\n", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/GSEL9/pydavis", "keywords": "data science,data analytics,web scraping,database,weather data,data collection,davis", "license": "MIT", "maintainer": "", "maintainer_email": "", "name": "pydavis", "package_url": "https://pypi.org/project/pydavis/", "platform": "", "project_url": "https://pypi.org/project/pydavis/", "project_urls": { "Homepage": "https://github.com/GSEL9/pydavis" }, "release_url": "https://pypi.org/project/pydavis/0.1.1/", "requires_dist": [ "sphinx", "pymysql", "beautifulsoup4", "python-dateutil" ], "requires_python": "", "summary": "Tools to stream weather data from Davis weather stations.", "version": "0.1.1" }, "last_serial": 4034483, "releases": { "0.1.1": [ { "comment_text": "", "digests": { "md5": "43c68b16876ce725fc8d05d6a67cc25d", "sha256": "6b4fe48610dec0b22c21eb29630f58f88b8b6863a785dce1e8088918eb566fef" }, "downloads": -1, "filename": "pydavis-0.1.1-py3-none-any.whl", "has_sig": false, "md5_digest": "43c68b16876ce725fc8d05d6a67cc25d", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 11203, "upload_time": "2018-07-05T20:56:59", "url": "https://files.pythonhosted.org/packages/57/2b/9ee7d2a22dedaca8fad1f5ae79e3ba8fea8f9862cfbab362d658f87196b1/pydavis-0.1.1-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "8b81be1b19debc4b073edf01de0688a5", "sha256": "c54611db7d88b7cfc1033b70731fda13173f39f110ac7767dee293e73e6d866e" }, "downloads": -1, "filename": "pydavis-0.1.1.tar.gz", "has_sig": false, "md5_digest": "8b81be1b19debc4b073edf01de0688a5", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 12855, "upload_time": "2018-07-05T20:57:01", "url": "https://files.pythonhosted.org/packages/d6/4a/ff0c961427c438af0beb5874cea0c42a092943aede5bddf82b62a9b7c46e/pydavis-0.1.1.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "43c68b16876ce725fc8d05d6a67cc25d", "sha256": "6b4fe48610dec0b22c21eb29630f58f88b8b6863a785dce1e8088918eb566fef" }, "downloads": -1, "filename": "pydavis-0.1.1-py3-none-any.whl", "has_sig": false, "md5_digest": "43c68b16876ce725fc8d05d6a67cc25d", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 11203, "upload_time": "2018-07-05T20:56:59", "url": "https://files.pythonhosted.org/packages/57/2b/9ee7d2a22dedaca8fad1f5ae79e3ba8fea8f9862cfbab362d658f87196b1/pydavis-0.1.1-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "8b81be1b19debc4b073edf01de0688a5", "sha256": "c54611db7d88b7cfc1033b70731fda13173f39f110ac7767dee293e73e6d866e" }, "downloads": -1, "filename": "pydavis-0.1.1.tar.gz", "has_sig": false, "md5_digest": "8b81be1b19debc4b073edf01de0688a5", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 12855, "upload_time": "2018-07-05T20:57:01", "url": "https://files.pythonhosted.org/packages/d6/4a/ff0c961427c438af0beb5874cea0c42a092943aede5bddf82b62a9b7c46e/pydavis-0.1.1.tar.gz" } ] }