Update docs

Author: Perseudonymous

Pipfile

@@ -4,13 +4,19 @@ verify_ssl = true
 name = "pypi"
 
 [packages]
-requests = "==2.31.0"
-appdirs = "==1.4.4"
-requests-mock = "==1.11.0"
-geojson = "==3.1.0"
+requests = "*"
+appdirs = "*"
+requests-mock = "*"
+geojson = "*"
 datapoint = {file = ".", editable = true}
 
 [dev-packages]
+black = "*"
+isort = "*"
+flake8 = "*"
+flake8-bugbear = "*"
+pytest = "*"
+flake8-pytest-style = "*"
 
 [documentation]
 sphinx = "*"

Pipfile.lock

@@ -7,73 +7,57 @@ simple script which prints out data in just 6 lines of Python.
 API Key
 -------
 
-To access DataPoint you need to
-`register <http://www.metoffice.gov.uk/datapoint/API>`__ with the Met
-Office and get yourself an API key. The process is simple and just
-ensures that you don’t abuse the service.
+To access DataPoint you need to `register <https://datahub.metoffice.gov.uk/>`__
+with the Met Office and get yourself an API key. The process is simple and just
+ensures that you don’t abuse the service. You will need access to the
+Site-Specific forecast API.
 
-Connecting to DataPoint
+Connecting to DataHub
 -----------------------
 
-Now that we have an API key we can import the module:
+Now that you have an API key you can import the module:
 
 ::
 
    import datapoint
 
-And create a connection to DataPoint:
+And create a connection to DataHub:
 
 ::
 
-   conn = datapoint.connection(api_key="aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee")
+   manager = datapoint.Manager(api_key="aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee")
 
-This creates a :ref:`manager` object which manages our connection and interacts
-with DataPoint for us, we’ll discuss Manager Objects in depth later but for now
-you just need to know that it looks after your API key and has a load of methods
-to return data from DataPoint.
+This creates a `manager` object which manages the connection and interacts
+with DataHub.
 
-Getting data from DataPoint
+Getting data from DataHub
 ---------------------------
 
-So now that we have our Manager Object with a connection to DataPoint we can
-request some data. Our goal is to request some forecast data but first we need
-to know the site ID for the location we want data for. Luckily the Manager
-Object has a method to return a :ref:`site` object, which contains the ID among
-other things, from a specified latitude and longitude.
-
-We can simply request a Site Object like so:
-
-::
-
-   site = conn.get_nearest_forecast_site(51.500728, -0.124626)
-
-For now we’re just going to use this object to get us our forecast but
-you’ll find more information about what the Site Object contains later.
-
-Let’s call another of the Manager Object’s methods to give us a
-:ref:`forecast` object for our site:
+So now that you have a Manager object with a connection to DataHub you can
+request some data. To do this, use the `manager` object:
 
 ::
 
-   forecast = conn.get_forecast_for_site(site.location_id, "3hourly")
+   forecast = manager.get_forecast(51, 0, "hourly")
 
-We’ve given this method two parameters, the site ID for the forecast we want and
-also a forecast type of “3hourly”. We’ll discuss the forecast types later on.
+This takes three parameters: the latitude and longitude of the location you want
+a forecast for and also a forecast type of “hourly”. We’ll discuss the forecast
+types later on.
 
 This Forecast Object which has been returned to us contains lots of information
 which we will cover in a later section, right now we’re just going to get the
-:ref:`timestep` object which represents right this minute:
+data for the current time:
 
 ::
 
-   current_timestep = forecast.now()
+   current_weather = forecast.now()
 
-This Timestep Object contains many different details about the weather
-but for now we’ll just print out the weather text.
+This is a dict which contains many different details about the weather
+but for now we’ll just print out one field.
 
 ::
 
-   print current_timestep.weather.text
+   print(current_weather["feelsLikeTemperature"])
 
 And there you have it. If you followed all the steps you should have
 printed out the current weather for your chosen location.

docs/source/forecast_sites_map.png

@@ -12,5 +12,4 @@ datapoint-python documentation
 
    install
    getting-started
-   locations
-   objects
+   migration