{ "info": { "author": "Lukas Kubis", "author_email": "contact@lukaskubis.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.6", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Topic :: Home Automation", "Topic :: Scientific/Engineering :: Atmospheric Science" ], "description": "darkskylib\n==========\n\nThis library for the `Dark Sky\nAPI `__ provides access to detailed\nweather information from around the globe.\n\nQuick start\n-----------\n\nBefore you start using this library, you need to get your API key\n`here `__.\n\n\nAPI Calls\n~~~~~~~~~\n\nFunction ``forecast`` handles all request parameters and returns a\n``Forecast`` object.\n\n.. code:: python\n\n >>> from darksky import forecast\n >>> boston = forecast(key, 42.3601, -71.0589)\n >>>\n\nThe first 3 positional arguments are identical to the 3 required\nparameters for API call. The optional query parameters need to be\nprovided as keyword arguments.\n\nUsing ``time`` argument will get you a **time machine call**.\nUsing ``timeout`` argument will set default `request timeout `__ .\n\n.. code:: python\n\n >>> BOSTON = key, 42.3601, -71.0589\n >>> from datetime import datetime as dt\n >>> t = dt(2013, 5, 6, 12).isoformat()\n >>> boston = forecast(*BOSTON, time=t)\n >>> boston.time\n 1367866800\n\nData Points and Data Blocks\n~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nThe values as well as ``DataPoint`` and ``DataBlock`` objects are\naccessed using instance attributes or dictionary keys. You can access\ncurrent values directly, without going through ``currently`` data point.\n\n.. code:: python\n\n >>> boston['currently']['temperature']\n 60.72\n >>> boston.temperature\n 60.72\n\n**Data blocks** are indexable and iterable by their ``data`` values.\n\n.. code:: python\n\n >>> len(boston.hourly)\n 24\n >>>\n >>> boston.hourly[1].temperature\n 59.49\n >>>\n >>> # list temperatures for next 10 hours\n ... [hour.temperature for hour in boston.hourly[:10]]\n [60.83, 59.49, 58.93, 57.95, 56.01, 53.95, 51.21, 49.21, 47.95, 46.31]\n\nNonexistent attributes will raise ``AttributeError`` and dictionary keys\n``KeyError`` the way you'd expect.\n\nRaw data\n~~~~~~~~\n\nTo get the raw data dictionary, you can either access it through\ninstance attributes or navigate to it through dictionary keys, the same\nway you would navigate the actual dictionary.\n\n.. code:: python\n\n >>> boston.hourly[2]\n {'ozone': 290.06, 'temperature': 58.93, 'pressure': 1017.8, 'windBearing': 274, 'dewPoint': 52.58, 'cloudCover': 0.29, 'apparentTemperature': 58.93, 'windSpeed': 7.96, 'summary': 'Partly Cloudy', 'icon': 'partly-cloudy-night', 'humidity': 0.79, 'precipProbability': 0, 'precipIntensity': 0, 'visibility': 8.67, 'time': 1476410400}\n >>>\n >>> boston['hourly']['data'][2]\n {'ozone': 290.06, 'temperature': 58.93, 'pressure': 1017.8, 'windBearing': 274, 'dewPoint': 52.58, 'cloudCover': 0.29, 'apparentTemperature': 58.93, 'windSpeed': 7.96, 'summary': 'Partly Cloudy', 'icon': 'partly-cloudy-night', 'humidity': 0.79, 'precipProbability': 0, 'precipIntensity': 0, 'visibility': 8.67, 'time': 1476410400}\n\nFlags and Alerts\n~~~~~~~~~~~~~~~~\n\nAll dashes ``-`` in attribute names of **Flags** objects are replaced by\nunderscores ``_``. This doesn't affect the dictionary keys.\n\n.. code:: python\n\n >>> # instead of 'boston.flags.isd-stations'\n ... boston.flags.isd_stations\n ['383340-99999', '383390-99999', '383410-99999', '384620-99999', '384710-99999']\n >>>\n >>> boston.flags['isd-stations']\n ['383340-99999', '383390-99999', '383410-99999', '384620-99999', '384710-99999']\n\nEven though **Alerts** are represented by a list, the data accessibility\nthrough instance attributes is preserved for alerts in the list.\n\n.. code:: python\n\n >>> boston.alerts[0].title\n 'Freeze Watch for Norfolk, MA'\n\nUpdating data\n~~~~~~~~~~~~~\n\nUse ``refresh()`` method to update data of a ``Forecast`` object. The\n``refresh()`` method takes optional queries (including ``time``, making\nit a **Time machine** object) as keyword arguments. Calling\n``refresh()`` without any arguments will set all queries to default\nvalues. Use ``timeout`` argument to set the request timeout.\n\n.. code:: python\n\n >>> boston.refresh()\n >>> (boston.time, boston.temperature, len(boston.hourly))\n (1476403500, 60.72, 49)\n >>>\n >>> boston.refresh(units='si', extend='hourly')\n >>> (boston.time, boston.temperature, len(boston.hourly))\n (1476404205, 15.81, 169)\n >>>\n >>> boston.refresh(units='us')\n >>> (boston.time, boston.temperature, len(boston.hourly))\n (1476404489, 60.57, 49)\n\nFor Developers\n~~~~~~~~~~~~~~\n\nResponse headers are stored in a dictionary under ``response_headers``\nattribute.\n\n.. code:: python\n\n >>> boston.response_headers['X-response-Time']\n '146.035ms'\n\nExample script\n--------------\n\n.. code:: python\n\n from darksky import forecast\n from datetime import date, timedelta\n\n BOSTON = 42.3601, 71.0589\n\n weekday = date.today()\n with forecast('API_KEY', *BOSTON) as boston:\n print(boston.daily.summary, end='\\n---\\n')\n for day in boston.daily:\n day = dict(day = date.strftime(weekday, '%a'),\n sum = day.summary,\n tempMin = day.temperatureMin,\n tempMax = day.temperatureMax\n )\n print('{day}: {sum} Temp range: {tempMin} - {tempMax}'.format(**day))\n weekday += timedelta(days=1)\n\nOutput:\n\n::\n\n Light rain on Friday and Saturday, with temperatures bottoming out at 48\u00b0F on Tuesday.\n ---\n Sun: Partly cloudy in the morning. Temp range: 44.86 - 57.26\u00b0F\n Mon: Mostly cloudy in the morning. Temp range: 44.26 - 55.28\u00b0F\n Tue: Clear throughout the day. Temp range: 36.85 - 47.9\u00b0F\n Wed: Partly cloudy starting in the afternoon, continuing until evening. Temp range: 33.23 - 47.93\u00b0F\n Thu: Light rain overnight. Temp range: 35.75 - 49.71\u00b0F\n Fri: Light rain in the morning and afternoon. Temp range: 45.47 - 57.11\u00b0F\n Sat: Drizzle in the morning. Temp range: 43.3 - 62.08\u00b0F\n Sun: Clear throughout the day. Temp range: 39.81 - 60.84\u00b0F\n\nLicense\n-------\n\nThe code is available under terms of `MIT\nLicense `__\n\n\n", "description_content_type": null, "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/lukaskubis/darkskylib", "keywords": "darksky dark-sky dark sky forecast home weather home-weather weather-station", "license": "MIT", "maintainer": "", "maintainer_email": "", "name": "darkskylib", "package_url": "https://pypi.org/project/darkskylib/", "platform": "", "project_url": "https://pypi.org/project/darkskylib/", "project_urls": { "Homepage": "https://github.com/lukaskubis/darkskylib" }, "release_url": "https://pypi.org/project/darkskylib/0.3.91/", "requires_dist": [ "future", "requests" ], "requires_python": "", "summary": "The Dark Sky API wrapper", "version": "0.3.91" }, "last_serial": 3487716, "releases": { "0.2.2": [ { "comment_text": "", "digests": { "md5": 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