class AllDatatypesModel(Model):
id = columns.Integer(primary_key=True)
a = columns.Ascii()
b = columns.BigInt()
c = columns.Blob()
d = columns.Boolean()
e = columns.DateTime()
f = columns.Decimal()
g = columns.Double()
h = columns.Float()
i = columns.Inet()
j = columns.Integer()
k = columns.Text()
l = columns.TimeUUID()
m = columns.UUID()
n = columns.VarInt()
class CassandraIoT(Model):
example_id = columns.UUID(primary_key=True, default=uuid.uuid4)
name = columns.Text()
voltaj = columns.Float()
akim = columns.Float()
aktif = columns.Float()
reaktif = columns.Float()
faz_acisi = columns.Float()
sicaklik = columns.Float()
sinyal = columns.Text()
def __unicode__(self):
return self.example_id
class iot6(Model):
example_id = columns.UUID(primary_key=True, default=uuid.uuid4)
voltaj = columns.Float()
akim = columns.Float()
aktif= columns.Float()
reaktif = columns.Float()
faz_acisi = columns.Float()
sicaklik= columns.Float()
def __unicode__(self):
return self.example_id
class Customer(Model):
C_W_ID = columns.Integer(partition_key=True)
C_D_ID = columns.Integer(partition_key=True)
C_ID = columns.Integer(partition_key=True)
C_FIRST = columns.Text(max_length=16)
C_MIDDLE = columns.Text(max_length=2)
C_LAST = columns.Text(max_length=16)
C_STREET1 = columns.Text(max_length=20)
C_STREET2 = columns.Text(max_length=20)
C_CITY = columns.Text(max_length=20)
C_STATE = columns.Text(max_length=2)
C_ZIP = columns.Text(max_length=9)
C_PHONE = columns.Text(max_length=16)
C_SINCE = columns.DateTime()
C_CREDIT = columns.Text(max_length=2)
C_CREDIT_LIM = columns.Decimal()
C_DISCOUNT = columns.Decimal()
C_BALANCE = columns.Decimal()
C_YTD_PAYMENT = columns.Float()
C_PAYMENT_CNT = columns.Integer()
C_DELIVERY_CNT = columns.Integer()
C_DATA = columns.Text(max_length=500)
class EventsMentionsBySectorFirm(Base):
global_event_id = columns.Integer()
firm = columns.Text(partition_key=True)
sector = columns.Text(partition_key=True)
mention_source_name = columns.Text()
country = columns.Text()
confidence = columns.Integer()
mention_doc_tone = columns.Float()
event_date = columns.Date()
mention_date_time = columns.DateTime()
def get_date(self):
return {
"globalEventsId": self.global_event_id,
"firm": self.firm,
"sector": self.sector,
"mentionSourceName": self.mention_source_name,
"country": self.country,
"confidence": self.confidence,
"mentionDocTone": self.mention_doc_tone,
"eventDate": self.event_date,
"mentionDateTime": self.mention_date_time
}
class Item(Model):
__table_name__ = 'item'
id = columns.UUID(primary_key=True)
market_name = columns.Text(index=True)
avg_7_days = columns.Float()
avg_7_days_raw = columns.Float()
avg_30_days = columns.Float()
avg_30_days_raw = columns.Float()
current_price = columns.Float()
num_sales_24hrs = columns.Integer()
num_sales_7days = columns.Integer()
num_sales_30days = columns.Integer()
avg_daily_volume = columns.Float()
image_url = columns.Text()
description = columns.Text()
rarity = columns.Text()
game = columns.Integer(discriminator_column=True)
class Product(AioModel):
__table_name__ = 'product'
manager_id = columns.UUID(partition_key=True)
product_id = columns.UUID(primary_key=True)
name = columns.Text(index=True)
price = columns.Float()
description = columns.Text()
created_at = columns.DateTime(default=datetime.utcnow())
updated_at = columns.DateTime(default=datetime.utcnow())
@classmethod
async def new(cls, manager_id, name, price, description):
return await Product.async_create(manager_id=manager_id,
product_id=str(uuid.uuid4()),
name=name,
price=price,
description=description)
async def update_product(self, **new_product):
new_product['updated_at'] = datetime.utcnow()
return await self.async_update(**new_product)
class UserOrderModel(UserType):
__type_name__ = "user_order"
type = columns.Text(required=True)
code = columns.Text(required=True)
direction = columns.Text(required=True)
quantity = columns.Float(required=True)
place_time = columns.DateTime(required=True)
status = columns.Text(required=True)
filled_start_time = columns.DateTime()
filled_end_time = columns.DateTime()
filled_quantity = columns.Float()
filled_avg_price = columns.Float()
fee = columns.Float()
delay_time = columns.Text()
limit_price = columns.Float()
cross_price = columns.Float()
cross_direction = columns.Text()
execution_map = columns.Map(
key_type=columns.Text,
value_type=UserDefinedType(UserOrderExecutionModel),
default={})
class DailyRevenue(Model):
__key_space__ = 'bigdata'
__table_name__ = 'daily_revenue'
invoice_date = columns.Date(primary_key=True)
daily_revenue = columns.Float(primary_key=True)
class PriceChangeModel(UserType):
__type_name__ = "price_change2"
time = columns.DateTime()
pre_price = columns.Float()
after_price = columns.Float()
current_price = UserDefinedType(CurrentPriceModel)
class Observation(Model):
station_id = columns.Text(primary_key=True)
observation_date columns.Date(primary_key=True)
observation_time = columns.DateTime(primary_key=True, clustering_order="DESC")
latitude = columns.Float(static=True) # not in history
longitude = columns.Float(static=True) # not in history
elevation_ft = columns.Float(static=True) # not in history
weather_condition = columns.Text() # not in history
temp_f = columns.Float() # tempi
relative_humidity = columns.Float() # hum
wind_dir = columns.Text() #wdire
wind_degrees = columns.Float() #wdird
wind_mph = columns.Float() # wspdi
pressure_in = columns.Float() #pressurei
pressure_trend = columns.Text() # not in history
feelslike_f = columns.Float() # not in history
visibility_mi = columns.Float() # not in history
precip_1hr_in = columns.Float() #precip_ratei
precip_today_in = columns.Float() #precip_totali
class PetCategory(Model):
petCategoryId = columns.UUID(primary_key=True, default=uuid.uuid4)
name = columns.Text(required=True, index=True)
speed = columns.Float(required=False)
__keyspace__ = 'gpmr'
class TrainingBase(YrydayBaseModel):
hour = cCols.Integer(primary_key=True)
yryday = cCols.Integer(primary_key=True, clustering_order='DESC')
f_m7 = cCols.Float()
f_m718 = cCols.Float()
f_start2now = cCols.Float()
f_now2end = cCols.Float()
dow = cCols.Integer()
kWh_now = cCols.Float()
kWh_L = cCols.Float()
kWh_A = cCols.Float()
kWh_tot = cCols.Float()
target = cCols.Float()
HOURS_RANGE = range(0, 23)
__table_name_case_sensitive__ = True
# must specify this access name so client knows what to call it
access_name = 'training_base'
__table_name__ = models.resource_table_name(access_name, res_name)
_has_datetime_primary_key = False
def get(self, hour=None, yrydays=None):
if hour is None:
q = self.day_records_query(yrydays)
else:
q = self.objects.filter(hour=hour)
if yrydays is not None:
q = q.filter(yryday__in=yrydays)
q.limit(None)
return q
def get_df(self, *args, **kwargs):
q = self.get(*args, **kwargs)
return self.convert_to_df(q)
@classmethod
def format_df(cls, df, hour=None):
df.index.name = 'yryday'
df = df.reset_index()
if hour is not None:
df['hour'] = hour
return df
def rewind(self, hours=None, **kwargs):
hours = hours or self.HOURS_RANGE
self.rewind_multiple(iterable=hours, col_name='hour', **kwargs)
def day_records_query(self, yrydays):
q = self.objects.filter(hour__in=self.HOURS_RANGE)
try:
# accept a list of yrydays
q = q.filter(yryday__in=yrydays)
except QueryException:
# or a single yryday
q = q.filter(yryday=yrydays)
return q
def day_records(self, yrydays):
q = self.day_records_query(yrydays)
return self.convert_to_df(q, index='hour')
class FloatingPointModel(Model):
id = columns.Integer(primary_key=True)
a = columns.Float(double_precision=False)
b = columns.Float(double_precision=True)
c = columns.Float()
d = columns.Double()
class AssetStat(Model):
asset = columns.Text(primary_key=True)
reward = columns.Float()
risk = columns.Float()
latency = columns.Float()
time_evaluated = columns.Float()
class SourceUserEntity(Model):
user_id = columns.Integer(primary_key=True)
username = columns.Text(index=True)
full_name = columns.Text(index=True)
bio = columns.Text(index=True)
locations = columns.List(columns.Text(index=True))
website = columns.Text()
media_count = columns.Integer(index=True)
follows = columns.Integer(index=True)
followers = columns.Integer(index=True)
recent_media_ids = columns.List(columns.Text)
most_recent_engagement_rating = columns.Float(index=True)
averaged_engagement_rating = columns.Float(index=True)
trending = columns.Boolean(index=True)
trending_value = columns.Float(index=True)
created_time = columns.DateTime(index=True)
updated_time = columns.DateTime(index=True)
def __repr__(self):
return 'Id: %d - Username: %s - Followers: %d - RecentEngagementRating: %0.3f' \
' - AveragedRating: %0.3f - Trending: %r - Value: %0.2f' \
% (self.user_id, self.username, self.followers, self.most_recent_engagement_rating,
self.averaged_engagement_rating, self.trending, self.trending_value)
def tsv_repr(self):
return(str(self.user_id).encode('utf-8') + "\t" +
self.username.replace("\n","").replace("\t","").encode('utf-8') + "\t" +
self.full_name.replace("\n","").replace("\t","").encode('utf-8') + "\t" +
self.bio.replace("\n","").replace("\t","").encode('utf-8') + "\t" +
",".join(self.locations).replace("\n","").replace("\t","").encode('utf-8') + "\t" +
self.website.replace("\n","").replace("\t","").encode('utf-8') + "\t" +
str(self.media_count).encode('utf-8') + "\t" +
str(self.follows).encode('utf-8') + "\t" +
str(self.followers).encode('utf-8') + "\t" +
",".join(self.recent_media_ids).encode('utf-8') + "\t" +
str(self.most_recent_engagement_rating).encode('utf-8') + "\t" +
str(self.averaged_engagement_rating).encode('utf-8') + "\t" +
str(self.trending).encode('utf-8') + "\t" +
str(self.trending_value).encode('utf-8') + "\t" +
str(self.created_time).encode('utf-8') + "\t" +
str(self.updated_time).encode('utf-8') + "\n")
@staticmethod
def tsv_header():
return("USER_ID\t"
"USER_NAME\t"
"FULL_NAME\t"
"BIO\t"
"LOCATIONS\t"
"WEBSITE\t"
"MEDIA_COUNT\t"
"FOLLOWS\t"
"FOLLOWERS\t"
"RECENT_MEDIA_IDS\t"
"RECENT_ENGAGEMENT_RATING\t"
"AVG_ENGAGEMENT_RATING\t"
"TRENDING\t"
"TRENDING_VALUE\t"
"CREATED_TIME\t"
"UPDATED_TIME\n")
@staticmethod
def sync_table():
sync_table(SourceUserEntity)
class ping(DjangoCassandraModel):
numa = columns.Text(primary_key=True)
name = columns.Text()
lat = columns.Float()
lon = columns.Float()
hora = columns.Text()
class location(DjangoCassandraModel):
name = columns.Text(primary_key=True)
lat = columns.Float(index=True)
lon = columns.Float(index=True)
class Usage(models.Usage):
pv_production = cCols.Float()
access_name = 'usage'
__table_name__ = models.resource_table_name(access_name, res_name)
class ProductRevenue(Model):
__key_space__ = 'bigdata'
__table_name__ = 'product_revenue'
product_code = columns.Text(primary_key=True)
product_total_revenue = columns.Float(primary_key=True)
product_description = columns.Text()
class FloatingPointModel(Model):
id = columns.Integer(primary_key=True)
f = columns.Float()
d = columns.Double()
class Candidate(Model):
__abstract__ = True
candidate = columns.Text(required=True, primary_key=True)
created_at = columns.DateTime(required=True, primary_key=True)
sentiment = columns.Float(required=True, primary_key=True)
tid = columns.BigInt(required=True, primary_key=True)
text = columns.Text(required=True)
user = columns.Text(required=False)
anger = columns.Float(required=False)
disgust = columns.Float(required=False)
fear = columns.Float(required=False)
joy = columns.Float(required=False)
sadness = columns.Float(required=False)
openness = columns.Float(required=False)
conscientiousness = columns.Float(required=False)
extraversion = columns.Float(required=False)
agreeableness = columns.Float(required=False)
range = columns.Float(required=False)
class PredictTxInfoModel(Model):
tx_id = columns.UUID(primary_key=True, default=uuid.uuid4)
Time = columns.Integer(index=True)
V1 = columns.Float()
V2 = columns.Float()
V3 = columns.Float()
V4 = columns.Float()
V5 = columns.Float()
V6 = columns.Float()
V7 = columns.Float()
V8 = columns.Float()
V9 = columns.Float()
V10 = columns.Float()
V11 = columns.Float()
V12 = columns.Float()
V13 = columns.Float()
V14 = columns.Float()
V15 = columns.Float()
V16 = columns.Float()
V17 = columns.Float()
V18 = columns.Float()
V19 = columns.Float()
V20 = columns.Float()
V21 = columns.Float()
V22 = columns.Float()
V23 = columns.Float()
V24 = columns.Float()
V25 = columns.Float()
V26 = columns.Float()
V27 = columns.Float()
V28 = columns.Float()
Amount = columns.Float(required=False)
P = columns.Integer(index=True)
class UserProfile(Model):
__keyspace__ = 'wti_cache'
__table_name__ = 'user_profiles'
user_id = columns.Integer(required=True, primary_key=True)
genre_adventure = columns.Float(required=False, default=0.0)
genre_animation = columns.Float(required=False, default=0.0)
genre_children = columns.Float(required=False, default=0.0)
genre_comedy = columns.Float(required=False, default=0.0)
genre_fantasy = columns.Float(required=False, default=0.0)
genre_romance = columns.Float(required=False, default=0.0)
genre_drama = columns.Float(required=False, default=0.0)
genre_action = columns.Float(required=False, default=0.0)
genre_crime = columns.Float(required=False, default=0.0)
genre_thriller = columns.Float(required=False, default=0.0)
genre_horror = columns.Float(required=False, default=0.0)
genre_mystery = columns.Float(required=False, default=0.0)
genre_sci_fi = columns.Float(required=False, default=0.0)
genre_imax = columns.Float(required=False, default=0.0)
genre_documentary = columns.Float(required=False, default=0.0)
genre_war = columns.Float(required=False, default=0.0)
genre_musical = columns.Float(required=False, default=0.0)
genre_film_noir = columns.Float(required=False, default=0.0)
genre_western = columns.Float(required=False, default=0.0)
genre_short = columns.Float(required=False, default=0.0)
