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)