classrooms module#

class classrooms.Address(**kwargs: str)[source]#

Bases: object

Address object made from informations retrieved via ADE API.

Parameters: kwargs (str) – dict with minimal entries (can be None): - address1 - zipCode - city - country
Example

>>> informations = dict(address1='Rue Rose 42', zipCode='1300', city='Wavre', country='Belgique')
>>> address = Address(**informations)

class classrooms.Classroom(**kwargs: Union[str, classrooms.Address])[source]#

Bases: object

Classroom object containing the address (as string or Address object), the name of the classroom and its id.

Parameters: kwargs (Union[str, Address]) – dict with minimal entries: - address - name - id

Its main purpose is be used with location().

location() → str[source]#

Returns the location (address) of this classroom.

Returns: the location
Return type: str

classrooms.get_geo_locations() → Dict[source]#

Returns the dictionary mapping each address to its geo-location.

Returns: the geo-locations
Return type: Dict

classrooms.merge_classrooms(classrooms: Iterable[classrooms.Classroom]) → classrooms.Classroom[source]#

Merges multiple classrooms into one.

Parameters: classrooms (Iterable[Classroom]) – multiple classrooms
Returns: the new classroom
Return type: Classroom
Example

>>> c1 = Classroom(address1, 'classA', 1)
>>> c2 = Classroom(address2, 'classB', 2)
>>> c3 = merge_classrooms((c1, c2))

classrooms.prettify_classrooms(classrooms: pandas.core.frame.DataFrame, sleep: float = 0) → pandas.core.frame.DataFrame[source]#

Returns the classrooms dataframe in a pretty format, useful when need to display.

The function will request, for every different address, a geo-localisation, so it can take some times. If too many requests are done, Nominatim will not like it so prefer to put a time.sleep between each request.

Parameters

classrooms (pd.DataFrame) – the classrooms with fields defined in backend.resources.py
sleep (float) – the sleep duration between each address request

Returns

the classrooms in a prettier format and with geo-location information

Return type

pd.DataFrame

classrooms.save_geo_locations(geo_locations: Dict)[source]#

Saves the dictionary of geo-locations into a json file with pretty indent. This file can be manually edited without causing any problem.

Parameters: geo_locations (Dict) – the geo-locations