class User(BaseModel):
user_id = BigAutoField(primary_key=True)
username = CharField(33)
password = CharField(60)
first_login_sub = BooleanField(default=True)
free_to_play = BooleanField(default=False)
front_character = SmallIntegerField(default=0)
class ComponentSummary(DataBaseModel):
_mapper = {}
@classmethod
def model(cls, table_index=None, date=None):
if not table_index:
table_index = date.strftime(
'%Y%m%d') if date else datetime.datetime.now().strftime(
'%Y%m%d')
class_name = 'ComponentSummary_%s' % table_index
ModelClass = TrackingMetric._mapper.get(class_name, None)
if ModelClass is None:
class Meta:
db_table = '%s_%s' % ('t_component_summary', table_index)
attrs = {'__module__': cls.__module__, 'Meta': Meta}
ModelClass = type("%s_%s" % (cls.__name__, table_index), (cls, ),
attrs)
ComponentSummary._mapper[class_name] = ModelClass
return ModelClass()
f_id = BigAutoField(primary_key=True)
f_job_id = CharField(max_length=25, index=True)
f_role = CharField(max_length=25, index=True)
f_party_id = CharField(max_length=10, index=True)
f_component_name = TextField()
f_task_id = CharField(max_length=50, null=True, index=True)
f_task_version = CharField(max_length=50, null=True, index=True)
f_summary = LongTextField()
class ModelTag(DataBaseModel):
f_id = BigAutoField(primary_key=True)
f_m_id = CharField(max_length=25, null=False)
f_t_id = BigIntegerField(null=False)
class Meta:
db_table = "t_model_tag"
class TrackingMetric(DataBaseModel):
_mapper = {}
@classmethod
def model(cls, table_index=None, date=None):
if not table_index:
table_index = date.strftime(
'%Y%m%d') if date else datetime.datetime.now().strftime(
'%Y%m%d')
class_name = 'TrackingMetric_%s' % table_index
ModelClass = TrackingMetric._mapper.get(class_name, None)
if ModelClass is None:
class Meta:
db_table = '%s_%s' % ('t_tracking_metric', table_index)
attrs = {'__module__': cls.__module__, 'Meta': Meta}
ModelClass = type("%s_%s" % (cls.__name__, table_index), (cls,),
attrs)
TrackingMetric._mapper[class_name] = ModelClass
return ModelClass()
f_id = BigAutoField(primary_key=True)
f_job_id = CharField(max_length=25, index=True)
f_component_name = TextField()
f_task_id = CharField(max_length=100, null=True, index=True)
f_task_version = BigIntegerField(null=True, index=True)
f_role = CharField(max_length=50, index=True)
f_party_id = CharField(max_length=10, index=True)
f_metric_namespace = CharField(max_length=180, index=True)
f_metric_name = CharField(max_length=180, index=True)
f_key = CharField(max_length=200)
f_value = TextField()
f_type = IntegerField(index=True) # 0 is data, 1 is meta
class Tag(DataBaseModel):
f_id = BigAutoField(primary_key=True)
f_name = CharField(max_length=100, index=True, unique=True)
f_desc = TextField(null=True)
class Meta:
db_table = "t_tags"
class Article(BaseModel):
article_id = BigAutoField(primary_key=True)
status = SmallIntegerField(null=False, index=True)
name = TextField(null=False)
body = TextField(null=False)
created_date = DateTimeField(index=True, default=datetime.utcnow)
modified_date = DateTimeField(null=True, index=True)
deleted_date = DateTimeField(null=True, index=True)
class Tag(DataBaseModel):
f_id = BigAutoField(primary_key=True)
f_name = CharField(max_length=100, index=True, unique=True)
f_desc = TextField(null=True)
f_create_time = BigIntegerField(default=current_timestamp())
f_update_time = BigIntegerField(default=current_timestamp())
class Meta:
db_table = "t_tags"
class UserDO(BaseDO):
class Meta:
table_name = 'user'
id = BigAutoField()
user = CharField()
source = CharField()
likes = FloatField()
reviews = IntegerField()
gmt_create = DateTimeField()
gmt_modified = DateTimeField()
class MenuDO(BaseDO):
class Meta:
table_name = 'menu'
id = BigAutoField()
outlet_id = ForeignKeyField(OutletDO)
brand = CharField()
price = DoubleField()
volume = IntegerField()
name = CharField()
gmt_create = DateTimeField()
gmt_modified = DateTimeField()
class ReviewDO(BaseDO):
class Meta:
table_name = 'review'
id = BigAutoField()
user = ForeignKeyField(UserDO)
outlet = ForeignKeyField(OutletDO)
date = DateField()
review = CharField()
rating = DoubleField()
gmt_create = DateTimeField()
gmt_modified = DateTimeField()
class VariableTable(BaseModel):
id = BigAutoField(primary_key=True)
is_top_level = BooleanField(null=True)
encoding = SmallIntegerField(default=0)
# primitive values
boolean_value = BooleanField(null=True)
number_value = DoubleField(null=True)
string_value = TextField(null=True)
# list_elements
# map_elements
# linked value
variable_value = DeferredForeignKey("VariableTable", null=True)
# allow different interpretations (such as interpreting a string as regex, or as a datetime)
interpretation = ForeignKeyField(Interpretation, null=True)
@property
def type(self):
if self.encoding == Encoding.null:
return type(None)
elif self.encoding == Encoding.boolean:
return bool
elif self.encoding == Encoding.number:
return float
elif self.encoding == Encoding.string:
return str
elif self.encoding == Encoding.list:
return list
elif self.encoding == Encoding.map:
return dict
elif self.encoding == Encoding.variable:
return VariableTable
@property
def value(self):
if self.encoding == Encoding.null:
return None
elif self.encoding == Encoding.boolean:
return self.boolean_value
elif self.encoding == Encoding.number:
return self.number_value
elif self.encoding == Encoding.string:
return self.string_value
elif self.encoding == Encoding.list:
return self.list_elements
elif self.encoding == Encoding.map:
return self.map_elements
elif self.encoding == Encoding.variable:
return self.variable_value
class DataTableTracking(DataBaseModel):
f_table_id = BigAutoField(primary_key=True)
f_table_name = CharField(max_length=300, null=True)
f_table_namespace = CharField(max_length=300, null=True)
f_job_id = CharField(max_length=25, index=True, null=True)
f_have_parent = BooleanField(default=False)
f_parent_number = IntegerField(default=0)
f_parent_table_name = CharField(max_length=500, null=True)
f_parent_table_namespace = CharField(max_length=500, null=True)
f_source_table_name = CharField(max_length=500, null=True)
f_source_table_namespace = CharField(max_length=500, null=True)
class Meta:
db_table = "t_data_table_tracking"
class ClassificationModel(Model):
id = BigAutoField()
item = CharField()
city = CharField()
classification = IntegerField()
frequency = SmallIntegerField()
extra_detail = CharField()
image_hash = CharField()
is_deleted = BooleanField()
created_at = DateTimeField()
updated_at = DateTimeField()
class Meta:
database = db
table_name = 'tb_classification'
class OutletDO(BaseDO):
class Meta:
table_name = 'outlet'
id = BigAutoField()
id_outlet = CharField(index=True, unique=True)
name = CharField()
source = CharField()
address = CharField()
country = CharField(max_length=2)
phone = CharField()
rating = FloatField()
reviews_nr = IntegerField()
gmt_create = DateTimeField()
gmt_modified = DateTimeField()
class Character(BaseModel):
character_id = BigAutoField(primary_key=True)
user = ForeignKeyField(User, backref='characters')
name = CharField(33)
unapproved_name = CharField(33, default="")
name_rejected = BooleanField(default=False)
free_to_play = BooleanField(default=False)
shirt_color = BigIntegerField()
shirt_style = BigIntegerField()
pants_color = BigIntegerField()
hair_style = BigIntegerField()
hair_color = BigIntegerField()
lh = BigIntegerField()
rh = BigIntegerField()
eyebrow_style = BigIntegerField()
eye_style = BigIntegerField()
mouth_style = BigIntegerField()
last_zone = IntegerField(default=0)
last_instance = IntegerField(default=0)
last_clone = BigIntegerField(default=0)
last_login = DateTimeField(default=datetime.now)
class MachineLearningModelInfo(DataBaseModel):
f_id = BigAutoField(primary_key=True)
f_role = CharField(max_length=50, index=True)
f_party_id = CharField(max_length=10, index=True)
f_roles = JSONField()
f_job_id = CharField(max_length=25)
f_model_id = CharField(max_length=100, index=True)
f_model_version = CharField(max_length=100, index=True)
f_loaded_times = IntegerField(default=0)
f_size = BigIntegerField(default=0)
f_create_time = BigIntegerField(default=0)
f_update_time = BigIntegerField(default=0)
f_description = TextField(null=True, default='')
f_initiator_role = CharField(max_length=50, index=True)
f_initiator_party_id = CharField(max_length=50, index=True, default=-1)
f_runtime_conf = JSONField()
f_work_mode = IntegerField()
f_dsl = JSONField()
f_train_runtime_conf = JSONField(default={})
f_imported = IntegerField(default=0)
f_job_status = CharField(max_length=50)
class Meta:
db_table = "t_machine_learning_model_info"
class BaseModel(Model):
id = BigAutoField(primary_key=True)
class Meta:
database = db
class ListElementTable(BaseModel):
id = BigAutoField(primary_key=True)
parent = ForeignKeyField(VariableTable, backref="list_elements")
key = IntegerField(default=0)
variable = ForeignKeyField(VariableTable)
class BHM_Spiders_Generic_Superset(CatalogdbModel):
# Not using reflection here to preserve Tom's notes.
pk = BigAutoField()
# Parameters derived from eROSITA eSASS catalogue
# Chosen to match X-ray columns defined in eROSITA/SDSS-V MoU (v2.0, April 2019)
ero_version = TextField(index=True, null=True) # string identifying this eROSITA data
# reduction version
ero_souuid = TextField(index=True, null=True) # string identifying this X-ray source
ero_flux = FloatField(null=True) # X-ray flux, 0.5-8keV band, erg/cm2/s
ero_flux_err = FloatField(null=True) # X-ray flux uncertainty, 0.5-8keV band,
# erg/cm2/s
ero_ext = FloatField(null=True) # X-ray extent parameter - arcsec
ero_ext_err = FloatField(null=True) # X-ray extent parameter uncertainty - arcsec
ero_ext_like = FloatField(null=True) # X-ray extent likelihood
ero_det_like = FloatField(null=True) # X-ray detection likelihood
ero_ra = DoubleField(index=True, null=True) # X-ray position, RA, ICRS, degrees
ero_dec = DoubleField(index=True, null=True) # X-ray position, Dec, ICRS, degrees
ero_radec_err = FloatField(null=True) # X-ray position uncertainty, arcsec
# Parameters describing the cross-matching of X-ray to optical/IR catalogue(s)
# 'ML+NWAY', 'LR' , 'SDSS_REDMAPPER', 'LS_REDMAPPER', 'HSC_REDMAPPER', 'MCMF' etc
xmatch_method = TextField(null=True)
# version identifier for cross-matching algorithm
xmatch_version = TextField(null=True)
# separation between X-ray position and opt positions - arcsec
xmatch_dist = FloatField(null=True)
# measure of quality of xmatch (e.g. p_any for Nway, LR)
xmatch_metric = FloatField(null=True)
# flavour of match, quality flags, e.g. NWAY match_flag - treat as bitmask
xmatch_flags = BigIntegerField(null=True)
# Parameters that describe the major class of the object
target_class = TextField(null=True) # TBD, but e.g. 'unknown', 'AGN', 'Star', 'Galaxy'
target_priority = IntegerField(null=True) # allows priority ranking based on
# info not available in catalogdb
target_has_spec = IntegerField(null=True) # (bitmask) allows flagging of targets
# that have a redshift from a catalogue
# that might not be listed in catalogdb
# follow bit pattern in spec compilation
# values < 0 means 'unknown'
# Parameters derived from the cross-matched opt/IR catalogue
# which optical catalogue(and version) provided this counterpart,
# e.g. 'ls_dr8', 'ps1_dr2' ... will also be the origin of the photometry columns below
best_opt = TextField(null=True)
# arithmetically derived from ls_release, ls_brickid and ls_objid
# ls_id = ls_objid + ls_brickid * 2**16 + ls_release * 2**40
# - make sure that we have a common definition within CatalogDB
# must be used when ls was the main source of counterparts to
# erosita source, otherwise is optional
ls_id = BigIntegerField(index=True, null=True)
# Pan-STARRS1-DR2 object id (= ObjectThin.ObjID = StackObjectThin.ObjID)
# Must be used when ps1-dr2(+unWISE) was the main source of counterparts
# to an erosita source, otherwise is optional
ps1_dr2_objid = BigIntegerField(index=True, null=True)
# derived from legacysurvey sweeps OPT_REF_ID when OPT_REF_CAT='G2'
# must be used when ls was the main source of counterparts to erosita source,
# otherwise is optional
# - SPIDERS team should also pre-match to gaia dr2 when using counterparts
# from non-LS catalogues
gaia_dr2_source_id = BigIntegerField(index=True, null=True)
# Corresponds to the unWISE catalog band-merged 'unwise_objid'
# - should be used when ps1-dr2+unWISE was the main source of
# counterparts to erosita sources, otherwise is optional
unwise_dr1_objid = CharField(index=True, null=True, max_length=16)
# provisional:
# Corresponds to the DES dr1 coadd_object_id
# - must be used when DES-dr1 was the primary source of counterpart to an
# erosita source, otherwise is optional
des_dr1_coadd_object_id = BigIntegerField(index=True, null=True)
# Corresponds to the SDSS DR16 photoObj https://www.sdss.org/dr13/help/glossary/#ObjID
# - must be used when SDSS photoObj was the primary source of counterpart
# to an erosita source, otherwise is optional
sdss_dr16_objid = BigIntegerField(index=True, null=True)
# included for convenience, but are copied from columns in other tables
opt_ra = DoubleField(index=True, null=True)
opt_dec = DoubleField(index=True, null=True)
opt_pmra = FloatField(null=True)
opt_pmdec = FloatField(null=True)
opt_epoch = FloatField(null=True)
# For convenience we send a subset of magnitude columns over to the database
# - the full set of columns is available via a database JOIN to e.g. main ls_dr8 catalogue
# Note to self: Be careful with use of modelflux, fiberflux, fiber2flux etc!
opt_modelflux_g = FloatField(null=True)
opt_modelflux_ivar_g = FloatField(null=True)
opt_modelflux_r = FloatField(null=True)
opt_modelflux_ivar_r = FloatField(null=True)
opt_modelflux_r = FloatField(null=True)
opt_modelflux_ivar_r = FloatField(null=True)
opt_modelflux_i = FloatField(null=True)
opt_modelflux_ivar_i = FloatField(null=True)
opt_modelflux_z = FloatField(null=True)
opt_modelflux_ivar_z = FloatField(null=True)
ls = ForeignKeyField(Legacy_Survey_DR8, field='ls_id', backref='+')
gaia = ForeignKeyField(Gaia_DR2, object_id_name='gaia_dr2_source_id', backref='+')
tic = ForeignKeyField(TIC_v8,
field='gaia_int',
column_name='gaia_dr2_source_id',
object_id_name='gaia_dr2_source_id',
backref='+')
class Meta:
use_reflection = False
class MapElementTable(BaseModel):
id = BigAutoField(primary_key=True)
parent = ForeignKeyField(VariableTable, backref="map_elements")
key = TextField()
variable = ForeignKeyField(VariableTable)
class TweetModel(ModelBase):
id = BigAutoField(primary_key=True)
user = ForeignKeyField(UserModel, backref="tweets")
content = TextField()
datetime = DateTimeField(default=datetime.now)
class TableBase(BaseModel):
"""Base Table with Hard Delete"""
def inttime():
return int(time.time())
id = BigAutoField()
created_at = TimestampField(default=inttime)
updated_at = TimestampField(default=0)
@classmethod
def do_create(cls):
return cls.create()
@classmethod
def do_update(cls, __data=None, **update):
if isinstance(__data, dict):
__data["updated_at"] = time
return cls.update(__data=__data, **update)
else:
return cls.update(__data=__data,
updated_at=int(time.time()),
**update)
@classmethod
def do_delete(cls):
return cls.delete()
@classmethod
def do_select(cls, *fields):
return cls.select(*fields)
def save(self, force_insert=False, only=None):
self.updated_at = int(time.time())
return super().save(force_insert, only)
@classmethod
def migrations(cls):
"""No Migrations"""
return []
@classmethod
def table_setup(cls) -> bool:
"""Magic to create the table returns true if a table is created"""
tv = TableVersion.get_or_none(name=cls._meta.table_name)
if not cls.table_exists():
cls.create_table()
tv = TableVersion()
tv.name = cls._meta.table_name
tv.version = 0
tv.save()
return True
else:
migrations = cls.migrations()
if migrations == []:
tv.version = 0
else:
current_version = tv.version - 1
with Database.db.atomic():
for migration in migrations[current_version:]:
migrate(*migration)
tv.version = len(migrations) if isinstance(migrations, list) else 0
tv.save()
return False