How to use the graphene.Float function in graphene

return dt

	@staticmethod
	def parse_literal(node):
		if isinstance(node, graphql.language.ast.StringValue):
			return datetime.datetime.strptime(node.value, '%Y-%m-%dT%H:%M:%S.%f')

	@staticmethod
	def parse_value(value):
		return datetime.datetime.strptime(value, '%Y-%m-%dT%H:%M:%S.%f')

# custom compound types
class GeoLocation(graphene.ObjectType):
	city = graphene.Field(graphene.String)
	continent = graphene.Field(graphene.String)
	coordinates = graphene.List(graphene.Float)
	country = graphene.Field(graphene.String)
	postal_code = graphene.Field(graphene.String)
	time_zone = graphene.Field(graphene.String)
	@classmethod
	def from_ip_address(cls, ip_address):
		ip_address = ipaddress.ip_address(ip_address)
		if ip_address.is_private:
			return
		try:
			result = geoip.lookup(ip_address)
		except geoip2.errors.AddressNotFoundError:
			result = None
		if result is None:
			return
		return cls(**result)

def convert_column_to_float(type, column, registry=None):
    return Float(description=column.doc, required=not(column.nullable))

from .models import Book, HasRead


class UserType(graphene_django.DjangoObjectType):
    is_admin = graphene.Boolean()

    def resolve_is_admin(self, info):
        return self.is_staff

    class Meta(object):
        model = UserModel
        only_fields = ('id', 'username', 'books_read')


class BookType(graphene_django.DjangoObjectType):
    average_rating = graphene.Float()

    def resolve_average_rating(self, info):
        query = self.read_by.all().aggregate(Avg('rating'))
        return query['rating__avg']

    class Meta(object):
        model = Book


class HasReadType(graphene_django.DjangoObjectType):
    class Meta(object):
        model = HasRead


class Query(graphene.ObjectType):
    users = graphene.List(UserType)

title = String(description="title for the chart")
    x_label = String(description="label for the x axis")
    y_label = String(description="label for the y axis")
    x_low = String(description="lower range for the x axis")
    x_high = String(description="higher range for x axis")
    y_low = String(description="lower range for y axis")
    y_high = String(description="higher range for y axis")


class ParameterDomain(ObjectType):
    class Meta:
        interfaces = relay.Node,

    name = String()
    domain_low = Float()
    domain_high = Float()


class ParallelCoordinates(ObjectType):
    class Meta:
        interfaces = relay.Node,

    # todo: {key, value}
    data = List(ObjectType)
    domains = List(ParameterDomain)


class Chart(Union):
    """this is also a file type."""

    class Meta:

    @classmethod
    def mutate_and_get_payload(cls, input, context, info):
        temp = Region.objects.get(pk=from_global_id(input.get('id'))[1])
        temp.delete()
        return DeleteRegion(region=temp)

# Site
class NewSite(ClientIDMutation):
    site = Field(SiteNode)
    class Input:
        name = String()
        slug = String()
        region = String(default_value=None)
        tenant = String(default_value=None)
        facility = String(default_value=None)
        asn = Float(default_value=None)
        physical_address = String(default_value=None)
        shipping_address = String(default_value=None)
        contact_name = String(default_value=None)
        contact_phone = String(default_value=None)
        contact_email = String(default_value=None)
        comments = String(default_value=None)

    @classmethod
    def mutate_and_get_payload(cls, input, context, info):
        region = input.get('region')
        tenant = input.get('tenant')

        temp = Site()

        if not_none(region):
            temp.region = Region.objects.get(pk=from_global_id(region)[1])

import graphene

from .geometry import Geometry

__all__ = ['Distance']


DistanceUnitEnum = graphene.Enum('DistanceUnitEnum', [
    (value, value) for value in D.UNITS.keys()
])


class Distance(graphene.InputObjectType):
    unit = DistanceUnitEnum(required=True)
    value = graphene.Float(required=True)
    geometry = Geometry(required=True)

    class Meta:
        description = """
Distance object type comprising:

\n- checkins: The number of the event checkins in a room
                \n- cancellations: The number of the even cacellations in a room
                \n- bookings: The number of the room bookings
                \n- checkins_percentage: The percentage of room checkins
                \n- cancellations_percentage: The percentage of room
                cancellations \n- app_bookings: The number of the room bookings
                    via app \n- app_bookings_percentage: The field with the
                        percentage of room bookings via app
    """
    room_id = graphene.Int()
    room_name = graphene.String()
    checkins = graphene.Int()
    cancellations = graphene.Int()
    bookings = graphene.Int()
    checkins_percentage = graphene.Float()
    cancellations_percentage = graphene.Float()
    app_bookings = graphene.Int()
    app_bookings_percentage = graphene.Float()


class Calendar(graphene.ObjectType):
    """
        Querry for the calendar events and accepts the arguments
        \n- events: The calendar events in a room
        \n- occupants: The number of occupants of a room
    """
    events = graphene.String()
    occupants = graphene.String()


class RoomFilter(graphene.ObjectType):
    """

model = MLModel


class CumulativeMetricsByRoundType(graphene.ObjectType):
    """Cumulative performance metrics for the given model through the given round."""

    ml_model__name = graphene.String(name="modelName")
    cumulative_correct_count = graphene.Int(
        description=(
            "Cumulative sum of correct tips made by the given model "
            "for the given season"
        ),
        default_value=0,
    )
    cumulative_accuracy = graphene.Float(
        description=(
            "Cumulative mean of correct tips (i.e. accuracy) made by the given model "
            "for the given season."
        ),
        default_value=0,
    )
    cumulative_mean_absolute_error = graphene.Float(
        description="Cumulative mean absolute error for the given season",
        default_value=0,
    )
    cumulative_margin_difference = graphene.Int(
        description=(
            "Cumulative difference between predicted margin and actual margin "
            "for the given season."
        ),
        default_value=0,

permissions = get_permissions(user_id, discussion_id)
                vote = vote.handle_duplication(
                    permissions=permissions, user_id=user_id)
                vote.db.add(vote)

        proposal.db.flush()
        return AddTokenVote(vote_specification=vote_spec)


class AddGaugeVote(graphene.Mutation):
    __doc__ = docs.AddGaugeVote.__doc__

    class Input:
        proposal_id = graphene.ID(required=True)
        vote_spec_id = graphene.ID(required=True)
        vote_value = graphene.Float(required=False)

    vote_specification = graphene.Field(lambda: VoteSpecificationUnion)  # need to match GaugeVoteSpecification / NumberGaugeVoteSpecification

    @staticmethod
    @abort_transaction_on_exception
    def mutate(root, args, context, info):
        require_cls_permission(CrudPermissions.CREATE, models.TokenIdeaVote, context)
        discussion_id = context.matchdict['discussion_id']
        discussion = models.Discussion.get(discussion_id)
        user_id = context.authenticated_userid
        vote_value = args.get('vote_value')

        proposal_id = args.get('proposal_id')
        proposal_id = int(Node.from_global_id(proposal_id)[1])
        proposal = models.Idea.get(proposal_id)

import asyncio
import random

import graphene as G


class RandomType(G.ObjectType):
    seconds = G.Int()
    random_int = G.Int()


class Subscription(G.ObjectType):
    count_seconds = G.Float(up_to=G.Int())
    random_int = G.Field(RandomType)

    async def resolve_count_seconds(root, info, up_to=5):
        for i in range(up_to):
            yield i
            await asyncio.sleep(1.0)
        yield up_to

    async def resolve_random_int(root, info):
        i = 0
        while True:
            yield RandomType(seconds=i, random_int=random.randint(0, 500))
            await asyncio.sleep(1.0)
            i += 1