class WorkDay(Base): __tablename__ = 'workday' id = Column(Integer, primary_key=True) day = Column(types.Date()) am_enter = Column(types.DateTime()) am_leave = Column(types.DateTime()) pm_enter = Column(types.DateTime()) pm_leave = Column(types.DateTime())
class ActionPlan(BaseObject): """Action plans for a known risk.""" __tablename__ = "action_plan" id = schema.Column(types.Integer(), primary_key=True, autoincrement=True) risk_id = schema.Column( types.Integer(), schema.ForeignKey(Risk.id, onupdate="CASCADE", ondelete="CASCADE"), nullable=False, index=True, ) action_plan = schema.Column(types.UnicodeText()) prevention_plan = schema.Column(types.UnicodeText()) # The column "action" is the synthesis of "action_plan" and "prevention_plan" action = schema.Column(types.UnicodeText()) requirements = schema.Column(types.UnicodeText()) responsible = schema.Column(types.Unicode(256)) budget = schema.Column(types.Integer()) planning_start = schema.Column(types.Date()) planning_end = schema.Column(types.Date()) reference = schema.Column(types.Text()) plan_type = schema.Column( Enum([ "measure_custom", "measure_standard", "in_place_standard", "in_place_custom", ]), nullable=False, index=True, default="measure_custom", ) solution_id = schema.Column(types.Unicode(20)) used_in_training = schema.Column( types.Boolean(), default=True, index=True, ) risk = orm.relation( Risk, backref=orm.backref("action_plans", order_by=id, cascade="all, delete, delete-orphan"), )
def load_dialect_impl(self, dialect): if dialect.name == "sqlite": return sqlite.DATE( storage_format="%(year)04d%(month)02d%(day)02d", regexp=r"(\d{4})(\d{2})(\d{2})" ) else: return types.Date()
def __init__(self, connectstring=None): ''' Create the engine and connection. Define the jobreport table ''' if connectstring is None: connectstring = '%s://%s:%s@%s' % (GOALCHEMY_DRIVER, GOALCHEMY_USER, GOALCHEMY_PASSWORD, GOALCHEMY_HOST) # configure Session class with desired options self.engine = create_engine(connectstring) Session = sessionmaker(bind=self.engine) self.session = Session() self.metadata = MetaData() self.tables = {} self.tables['goa'] = Table( 'goa', self.metadata, Column('id', types.Integer, primary_key=True, autoincrement='auto'), Column('db', types.String(50)), Column('db_object_id', types.String(20)), Column('db_object_symbol', types.String(50)), Column('qualifier', types.String(20)), Column('go_id', types.String(20)), Column('db_reference', types.String(50)), Column('evidence_code', types.String(10)), Column('with_or_from', types.String(100)), Column('aspect', types.String(1)), Column('db_object_name', types.String(50)), Column('db_object_synonym', types.String(500)), Column('db_object_type', types.String(20)), Column('taxon', types.String(20)), Column('organism', types.String(50)), Column('date', types.Date()), Column('assigned_by', types.String(20)), UniqueConstraint('db', 'db_object_id', 'go_id', 'db_reference', name='uix_1'), ) self.tables['go_term'] = Table( 'go_term', self.metadata, Column('go_id', types.String(20), primary_key=True), Column('term', types.String(200)), ) self.tables['alias'] = Table( 'alias', self.metadata, Column('id', types.Integer, primary_key=True, autoincrement='auto'), Column('authority', types.String(50)), Column('accession', types.String(100)), Column('alias', types.String(100)), Column('source', types.String(100)), UniqueConstraint('alias', 'source', name='uix_1'), ) self.metadata.bind = self.engine self.connection = self.engine.connect()
def write_asic_details(driver, engine, linked_id, company_name): try: df = extract_asic_details(driver, linked_id, company_name) inspector = inspect(engine) types = {'linked_id': st.Integer(), 'company_name': st.Text()} table_exists = 'asx' in inspector.get_table_names(schema="asic") current_cols_sql = """SELECT column_name FROM information_schema.columns WHERE table_schema = 'asic' AND table_name = 'asx' """ current_cols = pd.read_sql(current_cols_sql, engine)['column_name'].tolist() for col in df.columns: if(re.search('(^date_|_date$|_date_)', col)): types[col] = st.Date() if(col not in current_cols and table_exists): new_col_sql = "ALTER TABLE asic.asx ADD COLUMN " + col + " DATE" engine.execute(new_col_sql) elif(col == 'former_names'): types[col] = st.ARRAY(st.Text(), dimensions = 1) if(col not in current_cols and table_exists): new_col_sql = "ALTER TABLE asic.asx ADD COLUMN " + col + " TEXT[]" engine.execute(new_col_sql) else: types[col] = st.Text() if(col not in current_cols and table_exists): new_col_sql = "ALTER TABLE asic.asx ADD COLUMN " + col + " TEXT" engine.execute(new_col_sql) df.to_sql('asx', engine, schema="asic", if_exists="append", index=False, dtype = types) return(True) except: return(False)
class DutchCompany(BaseObject): """Information about a Dutch company.""" __tablename__ = "dutch_company" id = schema.Column(types.Integer(), primary_key=True, autoincrement=True) session_id = schema.Column( types.Integer(), schema.ForeignKey("session.id", onupdate="CASCADE", ondelete="CASCADE"), nullable=False, index=True, ) session = orm.relation( "SurveySession", cascade="all,delete-orphan", single_parent=True, backref=orm.backref("dutch_company", uselist=False, cascade="all"), ) title = schema.Column(types.Unicode(128)) address_visit_address = schema.Column(types.UnicodeText()) address_visit_postal = schema.Column(types.Unicode(16)) address_visit_city = schema.Column(types.Unicode(64)) address_postal_address = schema.Column(types.UnicodeText()) address_postal_postal = schema.Column(types.Unicode(16)) address_postal_city = schema.Column(types.Unicode(64)) email = schema.Column(types.String(128)) phone = schema.Column(types.String(32)) activity = schema.Column(types.Unicode(64)) submitter_name = schema.Column(types.Unicode(64)) submitter_function = schema.Column(types.Unicode(64)) department = schema.Column(types.Unicode(64)) location = schema.Column(types.Unicode(64)) submit_date = schema.Column(types.Date(), default=functions.now()) employees = schema.Column(Enum([None, "40h", "max25", "over25"])) absentee_percentage = schema.Column(types.Numeric(precision=5, scale=2)) accidents = schema.Column(types.Integer()) incapacitated_workers = schema.Column(types.Integer()) arbo_expert = schema.Column(types.Unicode(128)) works_council_approval = schema.Column(types.Date())
class Student(Model): __tablename__ = "student" id = Column(sqla_types.Integer, primary_key=True) full_name = Column(sqla_types.String(255), nullable=False, unique=True) dob = Column(sqla_types.Date(), nullable=True) current_school_id = Column(sqla_types.Integer, ForeignKey(School.id), nullable=False) current_school = relationship(School, backref=backref('students')) courses = relationship( "Course", secondary=student_course, backref=backref("students", lazy='dynamic') )
class Invoice(Entity, type_and_status.StatusMixin): book_date = schema.Column(types.Date(), nullable=False) status = type_and_status.Status(enumeration=[(1, 'DRAFT'), (2, 'READY')]) class Admin(EntityAdmin): list_display = ['book_date', 'current_status'] list_actions = [ type_and_status.ChangeStatus('DRAFT'), type_and_status.ChangeStatus('READY') ] form_actions = list_actions
class Ranking(Base): __tablename__ = 'ranking' id = Column(types.Integer(), primary_key=True) team_id = Column(types.Integer(), ForeignKey('teams.team_id')) league_id = Column(types.Integer()) season_id = Column(types.Integer()) standingsdate = Column(types.Date()) conference = Column(types.Text()) team = Column(types.Text()) g_i = Column(types.SmallInteger()) w = Column(types.SmallInteger()) l = Column(types.SmallInteger()) w_pct = Column(types.Numeric()) home_record = Column(types.Text()) road_record = Column(types.Text())
def init(): """ initialize graphics interface_period define table period and mapping""" # Graphics initialisation global interface_period interface_period = PeriodInterface() # Database definition from sqlalchemy import types, orm from sqlalchemy.schema import Column, Table, Sequence, ForeignKey from sqlalchemy.orm import relationship, backref, relation, mapper # dependencies from Planning import Planning from Cursus import Cursus t_period = Table( 'period', db.metadata, Column('id', types.Integer, Sequence('period_seq_id', optional=True), nullable=False, primary_key=True), Column('name', types.VARCHAR(255), nullable=False), Column('end', types.Date(), nullable=False), Column('id_planning', types.Integer, ForeignKey('planning.id'), nullable=False), Column('id_cursus', types.Integer, ForeignKey('cursus.id'), nullable=False), ) mapper(Period, t_period, properties={ 'planning': relationship(Planning, backref=backref('type_period', uselist=False)), 'cursus': relationship(Cursus, backref=backref('periods', cascade="all, delete-orphan", order_by=t_period.c.end.asc())), })
class Currency(BaseObject): """A currency Currencies are identified by their ISO 4217 three letter currency code. """ __tablename__ = "currency" id = schema.Column(types.Integer(), schema.Sequence("currency_id_seq", optional=True), primary_key=True, autoincrement=True) code = schema.Column(types.String(3), nullable=False) rate = schema.Column(types.Numeric(precision=6, scale=2), nullable=False) until = schema.Column(types.Date()) def __repr__(self): return "<Currency id=%s, code=%s rate=%.2f>" % (self.id, self.code, self.rate)
def output_to_test_sqlite(df, table_name, engine_url): df["date"] = pd.to_datetime(df["date"]) engine = create_engine(engine_url, echo=False) type_dict = {key: types.Integer() for key in df.columns[4:]} type_dict["district_name"] = types.VARCHAR(length=200) type_dict["facility_id"] = types.VARCHAR(length=200) type_dict["facility_name"] = types.VARCHAR(length=500) type_dict["date"] = types.Date() df.to_sql( table_name, con=engine, chunksize=10000, dtype=type_dict, if_exists="replace", index=False, )
def init(): """define table cursus and mapping""" # Database definition from sqlalchemy import types, orm from sqlalchemy.schema import Column, Table, Sequence, ForeignKey from sqlalchemy.orm import relationship, backref, relation, mapper # Dependencies from Period import Period t_cursus = Table( 'cursus', db.metadata, Column('id', types.Integer, Sequence('cursus_seq_id', optional=True), nullable=False, primary_key=True), Column('name', types.VARCHAR(255), nullable=False, unique=True), Column('start', types.Date(), nullable=False), ) mapper(Cursus, t_cursus)
class Games(Base): __tablename__ = 'games' game_date_est = Column(types.Date()) game_id = Column(types.Integer(), unique=True, primary_key=True) game_status_text = Column(types.Text()) home_team_id = Column(types.Integer()) visitor_team_id = Column(types.Integer()) season = Column(types.SmallInteger()) team_id_home = Column(types.Integer()) pts_home = Column(types.Numeric()) fg_pct_home = Column(types.Numeric()) ft_pct_home = Column(types.Numeric()) fg3_pct_home = Column(types.Numeric()) ast_home = Column(types.Numeric()) reb_homee = Column(types.Numeric()) team_id_away = Column(types.Numeric()) pts_away = Column(types.Numeric()) fg_pct_away = Column(types.Numeric()) ft_pct_away = Column(types.Numeric()) fg3_pct_away = Column(types.Numeric()) ast_away = Column(types.Numeric()) reb_away = Column(types.Numeric()) home_team_wins = Column(types.SmallInteger())
class BaseEngineSpec: # pylint: disable=too-many-public-methods """Abstract class for database engine specific configurations""" engine = "base" # str as defined in sqlalchemy.engine.engine engine_aliases: Optional[Tuple[str]] = None engine_name: Optional[ str ] = None # used for user messages, overridden in child classes _date_trunc_functions: Dict[str, str] = {} _time_grain_expressions: Dict[Optional[str], str] = {} column_type_mappings: Tuple[ Tuple[ Pattern[str], Union[TypeEngine, Callable[[Match[str]], TypeEngine]], GenericDataType, ], ..., ] = ( ( re.compile(r"^smallint", re.IGNORECASE), types.SmallInteger(), GenericDataType.NUMERIC, ), ( re.compile(r"^int.*", re.IGNORECASE), types.Integer(), GenericDataType.NUMERIC, ), ( re.compile(r"^bigint", re.IGNORECASE), types.BigInteger(), GenericDataType.NUMERIC, ), ( re.compile(r"^decimal", re.IGNORECASE), types.Numeric(), GenericDataType.NUMERIC, ), ( re.compile(r"^numeric", re.IGNORECASE), types.Numeric(), GenericDataType.NUMERIC, ), (re.compile(r"^real", re.IGNORECASE), types.REAL, GenericDataType.NUMERIC,), ( re.compile(r"^smallserial", re.IGNORECASE), types.SmallInteger(), GenericDataType.NUMERIC, ), ( re.compile(r"^serial", re.IGNORECASE), types.Integer(), GenericDataType.NUMERIC, ), ( re.compile(r"^bigserial", re.IGNORECASE), types.BigInteger(), GenericDataType.NUMERIC, ), ( re.compile(r"^string", re.IGNORECASE), types.String(), utils.GenericDataType.STRING, ), ( re.compile(r"^N((VAR)?CHAR|TEXT)", re.IGNORECASE), UnicodeText(), utils.GenericDataType.STRING, ), ( re.compile(r"^((VAR)?CHAR|TEXT|STRING)", re.IGNORECASE), String(), utils.GenericDataType.STRING, ), ( re.compile(r"^datetime", re.IGNORECASE), types.DateTime(), GenericDataType.TEMPORAL, ), (re.compile(r"^date", re.IGNORECASE), types.Date(), GenericDataType.TEMPORAL,), ( re.compile(r"^timestamp", re.IGNORECASE), types.TIMESTAMP(), GenericDataType.TEMPORAL, ), ( re.compile(r"^interval", re.IGNORECASE), types.Interval(), GenericDataType.TEMPORAL, ), (re.compile(r"^time", re.IGNORECASE), types.Time(), GenericDataType.TEMPORAL,), ( re.compile(r"^bool.*", re.IGNORECASE), types.Boolean(), GenericDataType.BOOLEAN, ), ) time_groupby_inline = False limit_method = LimitMethod.FORCE_LIMIT time_secondary_columns = False allows_joins = True allows_subqueries = True allows_alias_in_select = True allows_alias_in_orderby = True allows_sql_comments = True force_column_alias_quotes = False arraysize = 0 max_column_name_length = 0 try_remove_schema_from_table_name = True # pylint: disable=invalid-name run_multiple_statements_as_one = False @classmethod def get_dbapi_exception_mapping(cls) -> Dict[Type[Exception], Type[Exception]]: """ Each engine can implement and converge its own specific exceptions into Superset DBAPI exceptions Note: On python 3.9 this method can be changed to a classmethod property without the need of implementing a metaclass type :return: A map of driver specific exception to superset custom exceptions """ return {} @classmethod def get_dbapi_mapped_exception(cls, exception: Exception) -> Exception: """ Get a superset custom DBAPI exception from the driver specific exception. Override if the engine needs to perform extra changes to the exception, for example change the exception message or implement custom more complex logic :param exception: The driver specific exception :return: Superset custom DBAPI exception """ new_exception = cls.get_dbapi_exception_mapping().get(type(exception)) if not new_exception: return exception return new_exception(str(exception)) @classmethod def get_allow_cost_estimate(cls, extra: Dict[str, Any]) -> bool: return False @classmethod def get_engine( cls, database: "Database", schema: Optional[str] = None, source: Optional[str] = None, ) -> Engine: user_name = utils.get_username() return database.get_sqla_engine( schema=schema, nullpool=True, user_name=user_name, source=source ) @classmethod def get_timestamp_expr( cls, col: ColumnClause, pdf: Optional[str], time_grain: Optional[str], type_: Optional[str] = None, ) -> TimestampExpression: """ Construct a TimestampExpression to be used in a SQLAlchemy query. :param col: Target column for the TimestampExpression :param pdf: date format (seconds or milliseconds) :param time_grain: time grain, e.g. P1Y for 1 year :param type_: the source column type :return: TimestampExpression object """ if time_grain: time_expr = cls.get_time_grain_expressions().get(time_grain) if not time_expr: raise NotImplementedError( f"No grain spec for {time_grain} for database {cls.engine}" ) if type_ and "{func}" in time_expr: date_trunc_function = cls._date_trunc_functions.get(type_) if date_trunc_function: time_expr = time_expr.replace("{func}", date_trunc_function) if type_ and "{type}" in time_expr: date_trunc_function = cls._date_trunc_functions.get(type_) if date_trunc_function: time_expr = time_expr.replace("{type}", type_) else: time_expr = "{col}" # if epoch, translate to DATE using db specific conf if pdf == "epoch_s": time_expr = time_expr.replace("{col}", cls.epoch_to_dttm()) elif pdf == "epoch_ms": time_expr = time_expr.replace("{col}", cls.epoch_ms_to_dttm()) return TimestampExpression(time_expr, col, type_=DateTime) @classmethod def get_time_grains(cls) -> Tuple[TimeGrain, ...]: """ Generate a tuple of supported time grains. :return: All time grains supported by the engine """ ret_list = [] time_grains = builtin_time_grains.copy() time_grains.update(config["TIME_GRAIN_ADDONS"]) for duration, func in cls.get_time_grain_expressions().items(): if duration in time_grains: name = time_grains[duration] ret_list.append(TimeGrain(name, _(name), func, duration)) return tuple(ret_list) @classmethod def _sort_time_grains( cls, val: Tuple[Optional[str], str], index: int ) -> Union[float, int, str]: """ Return an ordered time-based value of a portion of a time grain for sorting Values are expected to be either None or start with P or PT Have a numerical value in the middle and end with a value for the time interval It can also start or end with epoch start time denoting a range i.e, week beginning or ending with a day """ pos = { "FIRST": 0, "SECOND": 1, "THIRD": 2, "LAST": 3, } if val[0] is None: return pos["FIRST"] prog = re.compile(r"(.*\/)?(P|PT)([0-9\.]+)(S|M|H|D|W|M|Y)(\/.*)?") result = prog.match(val[0]) # for any time grains that don't match the format, put them at the end if result is None: return pos["LAST"] second_minute_hour = ["S", "M", "H"] day_week_month_year = ["D", "W", "M", "Y"] is_less_than_day = result.group(2) == "PT" interval = result.group(4) epoch_time_start_string = result.group(1) or result.group(5) has_starting_or_ending = bool(len(epoch_time_start_string or "")) def sort_day_week() -> int: if has_starting_or_ending: return pos["LAST"] if is_less_than_day: return pos["SECOND"] return pos["THIRD"] def sort_interval() -> float: if is_less_than_day: return second_minute_hour.index(interval) return day_week_month_year.index(interval) # 0: all "PT" values should come before "P" values (i.e, PT10M) # 1: order values within the above arrays ("D" before "W") # 2: sort by numeric value (PT10M before PT15M) # 3: sort by any week starting/ending values plist = { 0: sort_day_week(), 1: pos["SECOND"] if is_less_than_day else pos["THIRD"], 2: sort_interval(), 3: float(result.group(3)), } return plist.get(index, 0) @classmethod def get_time_grain_expressions(cls) -> Dict[Optional[str], str]: """ Return a dict of all supported time grains including any potential added grains but excluding any potentially disabled grains in the config file. :return: All time grain expressions supported by the engine """ # TODO: use @memoize decorator or similar to avoid recomputation on every call time_grain_expressions = cls._time_grain_expressions.copy() grain_addon_expressions = config["TIME_GRAIN_ADDON_EXPRESSIONS"] time_grain_expressions.update(grain_addon_expressions.get(cls.engine, {})) denylist: List[str] = config["TIME_GRAIN_DENYLIST"] for key in denylist: time_grain_expressions.pop(key) return dict( sorted( time_grain_expressions.items(), key=lambda x: ( cls._sort_time_grains(x, 0), cls._sort_time_grains(x, 1), cls._sort_time_grains(x, 2), cls._sort_time_grains(x, 3), ), ) ) @classmethod def make_select_compatible( cls, groupby_exprs: Dict[str, ColumnElement], select_exprs: List[ColumnElement] ) -> List[ColumnElement]: """ Some databases will just return the group-by field into the select, but don't allow the group-by field to be put into the select list. :param groupby_exprs: mapping between column name and column object :param select_exprs: all columns in the select clause :return: columns to be included in the final select clause """ return select_exprs @classmethod def fetch_data( cls, cursor: Any, limit: Optional[int] = None ) -> List[Tuple[Any, ...]]: """ :param cursor: Cursor instance :param limit: Maximum number of rows to be returned by the cursor :return: Result of query """ if cls.arraysize: cursor.arraysize = cls.arraysize try: if cls.limit_method == LimitMethod.FETCH_MANY and limit: return cursor.fetchmany(limit) return cursor.fetchall() except Exception as ex: raise cls.get_dbapi_mapped_exception(ex) @classmethod def expand_data( cls, columns: List[Dict[Any, Any]], data: List[Dict[Any, Any]] ) -> Tuple[List[Dict[Any, Any]], List[Dict[Any, Any]], List[Dict[Any, Any]]]: """ Some engines support expanding nested fields. See implementation in Presto spec for details. :param columns: columns selected in the query :param data: original data set :return: list of all columns(selected columns and their nested fields), expanded data set, listed of nested fields """ return columns, data, [] @classmethod def alter_new_orm_column(cls, orm_col: "TableColumn") -> None: """Allow altering default column attributes when first detected/added For instance special column like `__time` for Druid can be set to is_dttm=True. Note that this only gets called when new columns are detected/created""" # TODO: Fix circular import caused by importing TableColumn @classmethod def epoch_to_dttm(cls) -> str: """ SQL expression that converts epoch (seconds) to datetime that can be used in a query. The reference column should be denoted as `{col}` in the return expression, e.g. "FROM_UNIXTIME({col})" :return: SQL Expression """ raise NotImplementedError() @classmethod def epoch_ms_to_dttm(cls) -> str: """ SQL expression that converts epoch (milliseconds) to datetime that can be used in a query. :return: SQL Expression """ return cls.epoch_to_dttm().replace("{col}", "({col}/1000)") @classmethod def get_datatype(cls, type_code: Any) -> Optional[str]: """ Change column type code from cursor description to string representation. :param type_code: Type code from cursor description :return: String representation of type code """ if isinstance(type_code, str) and type_code != "": return type_code.upper() return None @classmethod def normalize_indexes(cls, indexes: List[Dict[str, Any]]) -> List[Dict[str, Any]]: """ Normalizes indexes for more consistency across db engines noop by default :param indexes: Raw indexes as returned by SQLAlchemy :return: cleaner, more aligned index definition """ return indexes @classmethod def extra_table_metadata( cls, database: "Database", table_name: str, schema_name: str ) -> Dict[str, Any]: """ Returns engine-specific table metadata :param database: Database instance :param table_name: Table name :param schema_name: Schema name :return: Engine-specific table metadata """ # TODO: Fix circular import caused by importing Database return {} @classmethod def apply_limit_to_sql(cls, sql: str, limit: int, database: "Database") -> str: """ Alters the SQL statement to apply a LIMIT clause :param sql: SQL query :param limit: Maximum number of rows to be returned by the query :param database: Database instance :return: SQL query with limit clause """ # TODO: Fix circular import caused by importing Database if cls.limit_method == LimitMethod.WRAP_SQL: sql = sql.strip("\t\n ;") qry = ( select("*") .select_from(TextAsFrom(text(sql), ["*"]).alias("inner_qry")) .limit(limit) ) return database.compile_sqla_query(qry) if cls.limit_method == LimitMethod.FORCE_LIMIT: parsed_query = sql_parse.ParsedQuery(sql) sql = parsed_query.set_or_update_query_limit(limit) return sql @classmethod def get_limit_from_sql(cls, sql: str) -> Optional[int]: """ Extract limit from SQL query :param sql: SQL query :return: Value of limit clause in query """ parsed_query = sql_parse.ParsedQuery(sql) return parsed_query.limit @classmethod def set_or_update_query_limit(cls, sql: str, limit: int) -> str: """ Create a query based on original query but with new limit clause :param sql: SQL query :param limit: New limit to insert/replace into query :return: Query with new limit """ parsed_query = sql_parse.ParsedQuery(sql) return parsed_query.set_or_update_query_limit(limit) @staticmethod def csv_to_df(**kwargs: Any) -> pd.DataFrame: """Read csv into Pandas DataFrame :param kwargs: params to be passed to DataFrame.read_csv :return: Pandas DataFrame containing data from csv """ kwargs["encoding"] = "utf-8" kwargs["iterator"] = True chunks = pd.read_csv(**kwargs) df = pd.concat(chunk for chunk in chunks) return df @classmethod def df_to_sql(cls, df: pd.DataFrame, **kwargs: Any) -> None: """Upload data from a Pandas DataFrame to a database. For regular engines this calls the DataFrame.to_sql() method. Can be overridden for engines that don't work well with to_sql(), e.g. BigQuery. :param df: Dataframe with data to be uploaded :param kwargs: kwargs to be passed to to_sql() method """ df.to_sql(**kwargs) @classmethod def create_table_from_csv( # pylint: disable=too-many-arguments cls, filename: str, table: Table, database: "Database", csv_to_df_kwargs: Dict[str, Any], df_to_sql_kwargs: Dict[str, Any], ) -> None: """ Create table from contents of a csv. Note: this method does not create metadata for the table. """ df = cls.csv_to_df(filepath_or_buffer=filename, **csv_to_df_kwargs) engine = cls.get_engine(database) if table.schema: # only add schema when it is preset and non empty df_to_sql_kwargs["schema"] = table.schema if engine.dialect.supports_multivalues_insert: df_to_sql_kwargs["method"] = "multi" cls.df_to_sql(df=df, con=engine, **df_to_sql_kwargs) @classmethod def convert_dttm(cls, target_type: str, dttm: datetime) -> Optional[str]: """ Convert Python datetime object to a SQL expression :param target_type: The target type of expression :param dttm: The datetime object :return: The SQL expression """ return None @classmethod def create_table_from_excel( # pylint: disable=too-many-arguments cls, filename: str, table: Table, database: "Database", excel_to_df_kwargs: Dict[str, Any], df_to_sql_kwargs: Dict[str, Any], ) -> None: """ Create table from contents of a excel. Note: this method does not create metadata for the table. """ df = pd.read_excel(io=filename, **excel_to_df_kwargs) engine = cls.get_engine(database) if table.schema: # only add schema when it is preset and non empty df_to_sql_kwargs["schema"] = table.schema if engine.dialect.supports_multivalues_insert: df_to_sql_kwargs["method"] = "multi" cls.df_to_sql(df=df, con=engine, **df_to_sql_kwargs) @classmethod def get_all_datasource_names( cls, database: "Database", datasource_type: str ) -> List[utils.DatasourceName]: """Returns a list of all tables or views in database. :param database: Database instance :param datasource_type: Datasource_type can be 'table' or 'view' :return: List of all datasources in database or schema """ # TODO: Fix circular import caused by importing Database schemas = database.get_all_schema_names( cache=database.schema_cache_enabled, cache_timeout=database.schema_cache_timeout, force=True, ) all_datasources: List[utils.DatasourceName] = [] for schema in schemas: if datasource_type == "table": all_datasources += database.get_all_table_names_in_schema( schema=schema, force=True, cache=database.table_cache_enabled, cache_timeout=database.table_cache_timeout, ) elif datasource_type == "view": all_datasources += database.get_all_view_names_in_schema( schema=schema, force=True, cache=database.table_cache_enabled, cache_timeout=database.table_cache_timeout, ) else: raise Exception(f"Unsupported datasource_type: {datasource_type}") return all_datasources @classmethod def handle_cursor(cls, cursor: Any, query: Query, session: Session) -> None: """Handle a live cursor between the execute and fetchall calls The flow works without this method doing anything, but it allows for handling the cursor and updating progress information in the query object""" # TODO: Fix circular import error caused by importing sql_lab.Query @classmethod def extract_error_message(cls, ex: Exception) -> str: return f"{cls.engine} error: {cls._extract_error_message(ex)}" @classmethod def _extract_error_message(cls, ex: Exception) -> str: """Extract error message for queries""" return utils.error_msg_from_exception(ex) @classmethod def extract_errors(cls, ex: Exception) -> List[Dict[str, Any]]: return [ dataclasses.asdict( SupersetError( error_type=SupersetErrorType.GENERIC_DB_ENGINE_ERROR, message=cls._extract_error_message(ex), level=ErrorLevel.ERROR, extra={"engine_name": cls.engine_name}, ) ) ] @classmethod def adjust_database_uri(cls, uri: URL, selected_schema: Optional[str]) -> None: """ Mutate the database component of the SQLAlchemy URI. The URI here represents the URI as entered when saving the database, ``selected_schema`` is the schema currently active presumably in the SQL Lab dropdown. Based on that, for some database engine, we can return a new altered URI that connects straight to the active schema, meaning the users won't have to prefix the object names by the schema name. Some databases engines have 2 level of namespacing: database and schema (postgres, oracle, mssql, ...) For those it's probably better to not alter the database component of the URI with the schema name, it won't work. Some database drivers like presto accept '{catalog}/{schema}' in the database component of the URL, that can be handled here. """ @classmethod def patch(cls) -> None: """ TODO: Improve docstring and refactor implementation in Hive """ @classmethod def get_schema_names(cls, inspector: Inspector) -> List[str]: """ Get all schemas from database :param inspector: SqlAlchemy inspector :return: All schemas in the database """ return sorted(inspector.get_schema_names()) @classmethod def get_table_names( cls, database: "Database", inspector: Inspector, schema: Optional[str] ) -> List[str]: """ Get all tables from schema :param inspector: SqlAlchemy inspector :param schema: Schema to inspect. If omitted, uses default schema for database :return: All tables in schema """ tables = inspector.get_table_names(schema) if schema and cls.try_remove_schema_from_table_name: tables = [re.sub(f"^{schema}\\.", "", table) for table in tables] return sorted(tables) @classmethod def get_view_names( cls, database: "Database", inspector: Inspector, schema: Optional[str] ) -> List[str]: """ Get all views from schema :param inspector: SqlAlchemy inspector :param schema: Schema name. If omitted, uses default schema for database :return: All views in schema """ views = inspector.get_view_names(schema) if schema and cls.try_remove_schema_from_table_name: views = [re.sub(f"^{schema}\\.", "", view) for view in views] return sorted(views) @classmethod def get_table_comment( cls, inspector: Inspector, table_name: str, schema: Optional[str] ) -> Optional[str]: """ Get comment of table from a given schema and table :param inspector: SqlAlchemy Inspector instance :param table_name: Table name :param schema: Schema name. If omitted, uses default schema for database :return: comment of table """ comment = None try: comment = inspector.get_table_comment(table_name, schema) comment = comment.get("text") if isinstance(comment, dict) else None except NotImplementedError: # It's expected that some dialects don't implement the comment method pass except Exception as ex: # pylint: disable=broad-except logger.error("Unexpected error while fetching table comment") logger.exception(ex) return comment @classmethod def get_columns( cls, inspector: Inspector, table_name: str, schema: Optional[str] ) -> List[Dict[str, Any]]: """ Get all columns from a given schema and table :param inspector: SqlAlchemy Inspector instance :param table_name: Table name :param schema: Schema name. If omitted, uses default schema for database :return: All columns in table """ return inspector.get_columns(table_name, schema) @classmethod def where_latest_partition( # pylint: disable=too-many-arguments cls, table_name: str, schema: Optional[str], database: "Database", query: Select, columns: Optional[List[Dict[str, str]]] = None, ) -> Optional[Select]: """ Add a where clause to a query to reference only the most recent partition :param table_name: Table name :param schema: Schema name :param database: Database instance :param query: SqlAlchemy query :param columns: List of TableColumns :return: SqlAlchemy query with additional where clause referencing latest partition """ # TODO: Fix circular import caused by importing Database, TableColumn return None @classmethod def _get_fields(cls, cols: List[Dict[str, Any]]) -> List[Any]: return [column(c["name"]) for c in cols] @classmethod def select_star( # pylint: disable=too-many-arguments,too-many-locals cls, database: "Database", table_name: str, engine: Engine, schema: Optional[str] = None, limit: int = 100, show_cols: bool = False, indent: bool = True, latest_partition: bool = True, cols: Optional[List[Dict[str, Any]]] = None, ) -> str: """ Generate a "SELECT * from [schema.]table_name" query with appropriate limit. WARNING: expects only unquoted table and schema names. :param database: Database instance :param table_name: Table name, unquoted :param engine: SqlALchemy Engine instance :param schema: Schema, unquoted :param limit: limit to impose on query :param show_cols: Show columns in query; otherwise use "*" :param indent: Add indentation to query :param latest_partition: Only query latest partition :param cols: Columns to include in query :return: SQL query """ fields: Union[str, List[Any]] = "*" cols = cols or [] if (show_cols or latest_partition) and not cols: cols = database.get_columns(table_name, schema) if show_cols: fields = cls._get_fields(cols) quote = engine.dialect.identifier_preparer.quote if schema: full_table_name = quote(schema) + "." + quote(table_name) else: full_table_name = quote(table_name) qry = select(fields).select_from(text(full_table_name)) if limit: qry = qry.limit(limit) if latest_partition: partition_query = cls.where_latest_partition( table_name, schema, database, qry, columns=cols ) if partition_query is not None: qry = partition_query sql = database.compile_sqla_query(qry) if indent: sql = sqlparse.format(sql, reindent=True) return sql @classmethod def estimate_statement_cost(cls, statement: str, cursor: Any,) -> Dict[str, Any]: """ Generate a SQL query that estimates the cost of a given statement. :param statement: A single SQL statement :param cursor: Cursor instance :return: Dictionary with different costs """ raise Exception("Database does not support cost estimation") @classmethod def query_cost_formatter( cls, raw_cost: List[Dict[str, Any]] ) -> List[Dict[str, str]]: """ Format cost estimate. :param raw_cost: Raw estimate from `estimate_query_cost` :return: Human readable cost estimate """ raise Exception("Database does not support cost estimation") @classmethod def process_statement( cls, statement: str, database: "Database", user_name: str ) -> str: """ Process a SQL statement by stripping and mutating it. :param statement: A single SQL statement :param database: Database instance :param username: Effective username :return: Dictionary with different costs """ parsed_query = ParsedQuery(statement) sql = parsed_query.stripped() sql_query_mutator = config["SQL_QUERY_MUTATOR"] if sql_query_mutator: sql = sql_query_mutator(sql, user_name, security_manager, database) return sql @classmethod def estimate_query_cost( cls, database: "Database", schema: str, sql: str, source: Optional[str] = None ) -> List[Dict[str, Any]]: """ Estimate the cost of a multiple statement SQL query. :param database: Database instance :param schema: Database schema :param sql: SQL query with possibly multiple statements :param source: Source of the query (eg, "sql_lab") """ extra = database.get_extra() or {} if not cls.get_allow_cost_estimate(extra): raise Exception("Database does not support cost estimation") user_name = g.user.username if g.user else None parsed_query = sql_parse.ParsedQuery(sql) statements = parsed_query.get_statements() engine = cls.get_engine(database, schema=schema, source=source) costs = [] with closing(engine.raw_connection()) as conn: cursor = conn.cursor() for statement in statements: processed_statement = cls.process_statement( statement, database, user_name ) costs.append(cls.estimate_statement_cost(processed_statement, cursor)) return costs @classmethod def modify_url_for_impersonation( cls, url: URL, impersonate_user: bool, username: Optional[str] ) -> None: """ Modify the SQL Alchemy URL object with the user to impersonate if applicable. :param url: SQLAlchemy URL object :param impersonate_user: Flag indicating if impersonation is enabled :param username: Effective username """ if impersonate_user and username is not None: url.username = username @classmethod def update_impersonation_config( cls, connect_args: Dict[str, Any], uri: str, username: Optional[str], ) -> None: """ Update a configuration dictionary that can set the correct properties for impersonating users :param connect_args: config to be updated :param uri: URI :param impersonate_user: Flag indicating if impersonation is enabled :param username: Effective username :return: None """ @classmethod def execute(cls, cursor: Any, query: str, **kwargs: Any) -> None: """ Execute a SQL query :param cursor: Cursor instance :param query: Query to execute :param kwargs: kwargs to be passed to cursor.execute() :return: """ if not cls.allows_sql_comments: query = sql_parse.strip_comments_from_sql(query) if cls.arraysize: cursor.arraysize = cls.arraysize try: cursor.execute(query) except Exception as ex: raise cls.get_dbapi_mapped_exception(ex) @classmethod def make_label_compatible(cls, label: str) -> Union[str, quoted_name]: """ Conditionally mutate and/or quote a sqlalchemy expression label. If force_column_alias_quotes is set to True, return the label as a sqlalchemy.sql.elements.quoted_name object to ensure that the select query and query results have same case. Otherwise return the mutated label as a regular string. If maxmimum supported column name length is exceeded, generate a truncated label by calling truncate_label(). :param label: expected expression label/alias :return: conditionally mutated label supported by the db engine """ label_mutated = cls._mutate_label(label) if ( cls.max_column_name_length and len(label_mutated) > cls.max_column_name_length ): label_mutated = cls._truncate_label(label) if cls.force_column_alias_quotes: label_mutated = quoted_name(label_mutated, True) return label_mutated @classmethod def get_sqla_column_type( cls, column_type: Optional[str], column_type_mappings: Tuple[ Tuple[ Pattern[str], Union[TypeEngine, Callable[[Match[str]], TypeEngine]], GenericDataType, ], ..., ] = column_type_mappings, ) -> Union[Tuple[TypeEngine, GenericDataType], None]: """ Return a sqlalchemy native column type that corresponds to the column type defined in the data source (return None to use default type inferred by SQLAlchemy). Override `column_type_mappings` for specific needs (see MSSQL for example of NCHAR/NVARCHAR handling). :param column_type: Column type returned by inspector :return: SqlAlchemy column type """ if not column_type: return None for regex, sqla_type, generic_type in column_type_mappings: match = regex.match(column_type) if match: if callable(sqla_type): return sqla_type(match), generic_type return sqla_type, generic_type return None @staticmethod def _mutate_label(label: str) -> str: """ Most engines support mixed case aliases that can include numbers and special characters, like commas, parentheses etc. For engines that have restrictions on what types of aliases are supported, this method can be overridden to ensure that labels conform to the engine's limitations. Mutated labels should be deterministic (input label A always yields output label X) and unique (input labels A and B don't yield the same output label X). :param label: Preferred expression label :return: Conditionally mutated label """ return label @classmethod def _truncate_label(cls, label: str) -> str: """ In the case that a label exceeds the max length supported by the engine, this method is used to construct a deterministic and unique label based on the original label. By default this returns an md5 hash of the original label, conditionally truncated if the length of the hash exceeds the max column length of the engine. :param label: Expected expression label :return: Truncated label """ label = hashlib.md5(label.encode("utf-8")).hexdigest() # truncate hash if it exceeds max length if cls.max_column_name_length and len(label) > cls.max_column_name_length: label = label[: cls.max_column_name_length] return label @classmethod def column_datatype_to_string( cls, sqla_column_type: TypeEngine, dialect: Dialect ) -> str: """ Convert sqlalchemy column type to string representation. By default removes collation and character encoding info to avoid unnecessarily long datatypes. :param sqla_column_type: SqlAlchemy column type :param dialect: Sqlalchemy dialect :return: Compiled column type """ sqla_column_type = sqla_column_type.copy() if hasattr(sqla_column_type, "collation"): sqla_column_type.collation = None if hasattr(sqla_column_type, "charset"): sqla_column_type.charset = None return sqla_column_type.compile(dialect=dialect).upper() @classmethod def get_function_names(cls, database: "Database") -> List[str]: """ Get a list of function names that are able to be called on the database. Used for SQL Lab autocomplete. :param database: The database to get functions for :return: A list of function names useable in the database """ return [] @staticmethod def pyodbc_rows_to_tuples(data: List[Any]) -> List[Tuple[Any, ...]]: """ Convert pyodbc.Row objects from `fetch_data` to tuples. :param data: List of tuples or pyodbc.Row objects :return: List of tuples """ if data and type(data[0]).__name__ == "Row": data = [tuple(row) for row in data] return data @staticmethod def mutate_db_for_connection_test(database: "Database") -> None: """ Some databases require passing additional parameters for validating database connections. This method makes it possible to mutate the database instance prior to testing if a connection is ok. :param database: instance to be mutated """ return None @staticmethod def get_extra_params(database: "Database") -> Dict[str, Any]: """ Some databases require adding elements to connection parameters, like passing certificates to `extra`. This can be done here. :param database: database instance from which to extract extras :raises CertificateException: If certificate is not valid/unparseable """ extra: Dict[str, Any] = {} if database.extra: try: extra = json.loads(database.extra) except json.JSONDecodeError as ex: logger.error(ex) raise ex return extra @classmethod def is_readonly_query(cls, parsed_query: ParsedQuery) -> bool: """Pessimistic readonly, 100% sure statement won't mutate anything""" return ( parsed_query.is_select() or parsed_query.is_explain() or parsed_query.is_show() ) @classmethod def get_column_spec( cls, native_type: Optional[str], source: utils.ColumnTypeSource = utils.ColumnTypeSource.GET_TABLE, column_type_mappings: Tuple[ Tuple[ Pattern[str], Union[TypeEngine, Callable[[Match[str]], TypeEngine]], GenericDataType, ], ..., ] = column_type_mappings, ) -> Union[ColumnSpec, None]: """ Converts native database type to sqlalchemy column type. :param native_type: Native database typee :param source: Type coming from the database table or cursor description :return: ColumnSpec object """ col_types = cls.get_sqla_column_type( native_type, column_type_mappings=column_type_mappings ) if col_types: column_type, generic_type = col_types # wrap temporal types in custom type that supports literal binding # using datetimes if generic_type == GenericDataType.TEMPORAL: column_type = literal_dttm_type_factory( type(column_type), cls, native_type or "" ) is_dttm = generic_type == GenericDataType.TEMPORAL return ColumnSpec( sqla_type=column_type, generic_type=generic_type, is_dttm=is_dttm ) return None
def reflecttable(self, connection, table, include_columns): #TODO: map these better column_func = { 14 : lambda r: sqltypes.String(r['FLEN']), # TEXT 7 : lambda r: sqltypes.Integer(), # SHORT 8 : lambda r: r['FPREC']==0 and sqltypes.Integer() or sqltypes.Numeric(precision=r['FPREC'], length=r['FSCALE'] * -1), #INT or NUMERIC 9 : lambda r: sqltypes.Float(), # QUAD 10 : lambda r: sqltypes.Float(), # FLOAT 27 : lambda r: sqltypes.Float(), # DOUBLE 35 : lambda r: sqltypes.DateTime(), # TIMESTAMP 37 : lambda r: sqltypes.String(r['FLEN']), # VARYING 261: lambda r: sqltypes.TEXT(), # BLOB 40 : lambda r: sqltypes.Char(r['FLEN']), # CSTRING 12 : lambda r: sqltypes.Date(), # DATE 13 : lambda r: sqltypes.Time(), # TIME 16 : lambda r: sqltypes.Numeric(precision=r['FPREC'], length=r['FSCALE'] * -1) #INT64 } tblqry = """ SELECT DISTINCT R.RDB$FIELD_NAME AS FNAME, R.RDB$NULL_FLAG AS NULL_FLAG, R.RDB$FIELD_POSITION, F.RDB$FIELD_TYPE AS FTYPE, F.RDB$FIELD_SUB_TYPE AS STYPE, F.RDB$FIELD_LENGTH AS FLEN, F.RDB$FIELD_PRECISION AS FPREC, F.RDB$FIELD_SCALE AS FSCALE FROM RDB$RELATION_FIELDS R JOIN RDB$FIELDS F ON R.RDB$FIELD_SOURCE=F.RDB$FIELD_NAME WHERE F.RDB$SYSTEM_FLAG=0 and R.RDB$RELATION_NAME=? ORDER BY R.RDB$FIELD_POSITION""" keyqry = """ SELECT SE.RDB$FIELD_NAME SENAME FROM RDB$RELATION_CONSTRAINTS RC JOIN RDB$INDEX_SEGMENTS SE ON RC.RDB$INDEX_NAME=SE.RDB$INDEX_NAME WHERE RC.RDB$CONSTRAINT_TYPE=? AND RC.RDB$RELATION_NAME=?""" fkqry = """ SELECT RC.RDB$CONSTRAINT_NAME CNAME, CSE.RDB$FIELD_NAME FNAME, IX2.RDB$RELATION_NAME RNAME, SE.RDB$FIELD_NAME SENAME FROM RDB$RELATION_CONSTRAINTS RC JOIN RDB$INDICES IX1 ON IX1.RDB$INDEX_NAME=RC.RDB$INDEX_NAME JOIN RDB$INDICES IX2 ON IX2.RDB$INDEX_NAME=IX1.RDB$FOREIGN_KEY JOIN RDB$INDEX_SEGMENTS CSE ON CSE.RDB$INDEX_NAME=IX1.RDB$INDEX_NAME JOIN RDB$INDEX_SEGMENTS SE ON SE.RDB$INDEX_NAME=IX2.RDB$INDEX_NAME AND SE.RDB$FIELD_POSITION=CSE.RDB$FIELD_POSITION WHERE RC.RDB$CONSTRAINT_TYPE=? AND RC.RDB$RELATION_NAME=? ORDER BY SE.RDB$INDEX_NAME, SE.RDB$FIELD_POSITION""" # get primary key fields c = connection.execute(keyqry, ["PRIMARY KEY", self._denormalize_name(table.name)]) pkfields =[self._normalize_name(r['SENAME']) for r in c.fetchall()] # get all of the fields for this table c = connection.execute(tblqry, [self._denormalize_name(table.name)]) found_table = False while True: row = c.fetchone() if row is None: break found_table = True name = self._normalize_name(row['FNAME']) if include_columns and name not in include_columns: continue args = [name] kw = {} # get the data types and lengths coltype = column_func.get(row['FTYPE'], None) if coltype is None: warnings.warn(RuntimeWarning("Did not recognize type '%s' of column '%s'" % (str(row['FTYPE']), name))) coltype = sqltypes.NULLTYPE else: coltype = coltype(row) args.append(coltype) # is it a primary key? kw['primary_key'] = name in pkfields # is it nullable ? kw['nullable'] = not bool(row['NULL_FLAG']) table.append_column(schema.Column(*args, **kw)) if not found_table: raise exceptions.NoSuchTableError(table.name) # get the foreign keys c = connection.execute(fkqry, ["FOREIGN KEY", self._denormalize_name(table.name)]) fks = {} while True: row = c.fetchone() if not row: break cname = self._normalize_name(row['CNAME']) try: fk = fks[cname] except KeyError: fks[cname] = fk = ([], []) rname = self._normalize_name(row['RNAME']) schema.Table(rname, table.metadata, autoload=True, autoload_with=connection) fname = self._normalize_name(row['FNAME']) refspec = rname + '.' + self._normalize_name(row['SENAME']) fk[0].append(fname) fk[1].append(refspec) for name,value in fks.iteritems(): table.append_constraint(schema.ForeignKeyConstraint(value[0], value[1], name=name))
types = {'linked_id': st.Integer(), 'company_name': st.Text(), 'company_name_asic': st.Text(), 'acn': st.Text(), 'abn': st.Text(), 'previous_state_number': st.Text(), 'previous_state_of_registration': st.Text(), 'registration_date': st.Date(), 'next_review_date': st.Date(), 'status': st.Text(), 'type': st.Text(), 'locality_of_registered_office': st.Text(), 'regulator': st.Text(), 'former_names': st.ARRAY(st.Text(), dimensions = 1), 'date_deregistered': st.Date(), 'arbn': st.Text() } asic_information.to_sql('asx', engine, schema="asic", if_exists="replace", index=False, dtype = types)
def test_should_date_convert_string(): assert get_field(types.Date()).type == graphene.String
schema.ForeignKey('node.id'), primary_key=True), schema.Column('settings', types.Binary(), nullable=False), schema.Column('type', types.String(20)), schema.Column('created', types.DateTime(), default=datetime.now()), ) event = schema.Table( 'event', meta.metadata, schema.Column('id', types.Integer, schema.ForeignKey('node.id'), primary_key=True), schema.Column('title', types.Unicode(250), nullable=False), schema.Column('summary', types.Unicode(1000)), schema.Column('start', types.Date(), nullable=False), schema.Column('finish', types.Date(), nullable=False), schema.Column('published', types.DateTime), schema.Column('created', types.DateTime(), default=datetime.now()), schema.Column('updated', types.DateTime(), onupdate=datetime.now())) report = schema.Table( 'report', meta.metadata, schema.Column('id', types.Integer, schema.ForeignKey('node.id'), primary_key=True), schema.Column('event_id', types.Integer, schema.ForeignKey('event.id'), nullable=False), schema.Column('title', types.Unicode()),
class AuthenticationMechanism( Entity ): __tablename__ = 'authentication_mechanism' authentication_type = Column( camelot.types.Enumeration(authentication_types), nullable = False, index = True , default = authentication_types[0][1] ) username = Column( types.Unicode( 40 ), nullable = False, index = True, unique = True ) password = Column( types.Unicode( 200 ), nullable = True, index = False, default = None ) from_date = Column( types.Date(), default = datetime.date.today, nullable = False, index = True ) thru_date = Column( types.Date(), default = end_of_times, nullable = False, index = True ) last_login = Column( types.DateTime() ) representation = Column( types.Text(), nullable=True ) @classmethod def get_or_create( cls, username ): session = Session() authentication = session.query( cls ).filter_by( username = username ).first() if not authentication: authentication = cls( username = username ) session.add( authentication ) session.flush() return authentication def get_representation(self): """ :return: a :class:`QtGui.QImage` object with the avatar of the user, or `None`. """ if self.representation is None: return self.representation return QtGui.QImage.fromData(base64.b64decode(self.representation)) def set_representation(self, image): """ :param image: a :class:`QtGui.QImage` object with the avatar of the user, or `None`. """ if image is None: self.representation=None qbyte_array = QtCore.QByteArray() qbuffer = QtCore.QBuffer( qbyte_array ) image.save( qbuffer, 'PNG' ) self.representation=base64.b64encode(qbyte_array.data()) def has_role( self, role_name ): """ :param role_name: a string with the name of the role :return; `True` if the user is associated to this role, otherwise `False`. """ for group in self.groups: if getattr( group, role_name ) == True: return True return False def __unicode__( self ): return self.username class Admin( EntityAdmin ): verbose_name = _('Authentication mechanism') list_display = ['authentication_type', 'username', 'from_date', 'thru_date', 'last_login']
def reflecttable(self, connection, table): #TODO: map these better column_func = { 14: lambda r: sqltypes.String(r['FLEN']), # TEXT 7: lambda r: sqltypes.Integer(), # SHORT 8: lambda r: sqltypes.Integer(), # LONG 9: lambda r: sqltypes.Float(), # QUAD 10: lambda r: sqltypes.Float(), # FLOAT 27: lambda r: sqltypes.Double(), # DOUBLE 35: lambda r: sqltypes.DateTime(), # TIMESTAMP 37: lambda r: sqltypes.String(r['FLEN']), # VARYING 261: lambda r: sqltypes.TEXT(), # BLOB 40: lambda r: sqltypes.Char(r['FLEN']), # CSTRING 12: lambda r: sqltypes.Date(), # DATE 13: lambda r: sqltypes.Time(), # TIME 16: lambda r: sqltypes.Numeric(precision=r['FPREC'], length=r['FSCALE'] * -1) #INT64 } tblqry = """\ SELECT DISTINCT R.RDB$FIELD_NAME AS FNAME, R.RDB$NULL_FLAG AS NULL_FLAG, R.RDB$FIELD_POSITION, F.RDB$FIELD_TYPE AS FTYPE, F.RDB$FIELD_SUB_TYPE AS STYPE, F.RDB$FIELD_LENGTH AS FLEN, F.RDB$FIELD_PRECISION AS FPREC, F.RDB$FIELD_SCALE AS FSCALE FROM RDB$RELATION_FIELDS R JOIN RDB$FIELDS F ON R.RDB$FIELD_SOURCE=F.RDB$FIELD_NAME WHERE F.RDB$SYSTEM_FLAG=0 and R.RDB$RELATION_NAME=? ORDER BY R.RDB$FIELD_POSITION;""" keyqry = """ SELECT RC.RDB$CONSTRAINT_TYPE KEYTYPE, RC.RDB$CONSTRAINT_NAME CNAME, RC.RDB$INDEX_NAME INAME, SE.RDB$FIELD_NAME SENAME, FROM RDB$RELATION_CONSTRAINTS RC LEFT JOIN RDB$INDEX_SEGMENTS SE ON RC.RDB$INDEX_NAME=SE.RDB$INDEX_NAME WHERE RC.RDB$RELATION_NAME=? AND SE.RDB$FIELD_NAME=? """ #import pdb;pdb.set_trace() # get all of the fields for this table c = connection.execute(tblqry, [table.name.upper()]) while True: row = c.fetchone() if not row: break args = [row['FNAME']] kw = {} # get the data types and lengths args.append(column_func[row['FTYPE']](row)) # is it a foreign key (and what is it linked to) # is it a primary key? table.append_item(schema.Column(*args, **kw))
def test_should_date_convert_string(): assert_column_conversion(types.Date(), graphene.String)
# phonetic transcription -- broad, optional schema.Column('phoneticTranscription', types.Unicode(255)), # narrow phonetic transcription -- optional schema.Column('narrowPhoneticTranscription', types.Unicode(255)), schema.Column('morphemeBreak', types.Unicode(255)), schema.Column('morphemeGloss', types.Unicode(255)), schema.Column('comments', types.UnicodeText()), schema.Column('speakerComments', types.UnicodeText()), schema.Column('context', types.UnicodeText()), # describing context of utterance # Forced choice textual values schema.Column('grammaticality', types.Unicode(255)), # Temporal values: only dateElicited is consciously enterable by the user schema.Column('dateElicited', types.Date()), schema.Column('datetimeEntered', types.DateTime()), schema.Column('datetimeModified', types.DateTime(), default=now), # syntacticCategoryString: OLD-generated value schema.Column('syntacticCategoryString', types.Unicode(255)), # morphemeBreakIDs and morphemeGlossIDs: OLD-generated values schema.Column('morphemeBreakIDs', types.Unicode(1023)), schema.Column('morphemeGlossIDs', types.Unicode(1023)), # breakGlossCategory: OLD-generated value, e.g., 'chien|dog|N-s|PL|NUM' schema.Column('breakGlossCategory', types.Unicode(1023)), # A Form can have only one each of elicitor, enterer and verifier, but each # of these can have more than one form
def reflecttable(self, connection, table): #TODO: map these better column_func = { 14 : lambda r: sqltypes.String(r['FLEN']), # TEXT 7 : lambda r: sqltypes.Integer(), # SHORT 8 : lambda r: sqltypes.Integer(), # LONG 9 : lambda r: sqltypes.Float(), # QUAD 10 : lambda r: sqltypes.Float(), # FLOAT 27 : lambda r: sqltypes.Float(), # DOUBLE 35 : lambda r: sqltypes.DateTime(), # TIMESTAMP 37 : lambda r: sqltypes.String(r['FLEN']), # VARYING 261: lambda r: sqltypes.TEXT(), # BLOB 40 : lambda r: sqltypes.Char(r['FLEN']), # CSTRING 12 : lambda r: sqltypes.Date(), # DATE 13 : lambda r: sqltypes.Time(), # TIME 16 : lambda r: sqltypes.Numeric(precision=r['FPREC'], length=r['FSCALE'] * -1) #INT64 } tblqry = """ SELECT DISTINCT R.RDB$FIELD_NAME AS FNAME, R.RDB$NULL_FLAG AS NULL_FLAG, R.RDB$FIELD_POSITION, F.RDB$FIELD_TYPE AS FTYPE, F.RDB$FIELD_SUB_TYPE AS STYPE, F.RDB$FIELD_LENGTH AS FLEN, F.RDB$FIELD_PRECISION AS FPREC, F.RDB$FIELD_SCALE AS FSCALE FROM RDB$RELATION_FIELDS R JOIN RDB$FIELDS F ON R.RDB$FIELD_SOURCE=F.RDB$FIELD_NAME WHERE F.RDB$SYSTEM_FLAG=0 and R.RDB$RELATION_NAME=? ORDER BY R.RDB$FIELD_POSITION""" keyqry = """ SELECT SE.RDB$FIELD_NAME SENAME FROM RDB$RELATION_CONSTRAINTS RC JOIN RDB$INDEX_SEGMENTS SE ON RC.RDB$INDEX_NAME=SE.RDB$INDEX_NAME WHERE RC.RDB$CONSTRAINT_TYPE=? AND RC.RDB$RELATION_NAME=?""" fkqry = """ SELECT RC.RDB$CONSTRAINT_NAME CNAME, CSE.RDB$FIELD_NAME FNAME, IX2.RDB$RELATION_NAME RNAME, SE.RDB$FIELD_NAME SENAME FROM RDB$RELATION_CONSTRAINTS RC JOIN RDB$INDICES IX1 ON IX1.RDB$INDEX_NAME=RC.RDB$INDEX_NAME JOIN RDB$INDICES IX2 ON IX2.RDB$INDEX_NAME=IX1.RDB$FOREIGN_KEY JOIN RDB$INDEX_SEGMENTS CSE ON CSE.RDB$INDEX_NAME=IX1.RDB$INDEX_NAME JOIN RDB$INDEX_SEGMENTS SE ON SE.RDB$INDEX_NAME=IX2.RDB$INDEX_NAME AND SE.RDB$FIELD_POSITION=CSE.RDB$FIELD_POSITION WHERE RC.RDB$CONSTRAINT_TYPE=? AND RC.RDB$RELATION_NAME=? ORDER BY SE.RDB$INDEX_NAME, SE.RDB$FIELD_POSITION""" # get primary key fields c = connection.execute(keyqry, ["PRIMARY KEY", table.name.upper()]) pkfields =[r['SENAME'] for r in c.fetchall()] # get all of the fields for this table def lower_if_possible(name): # Remove trailing spaces: FB uses a CHAR() type, # that is padded with spaces name = name.rstrip() # If its composed only by upper case chars, use # the lowered version, otherwise keep the original # (even if stripped...) lname = name.lower() if lname.upper() == name and not ' ' in name: return lname return name c = connection.execute(tblqry, [table.name.upper()]) row = c.fetchone() if not row: raise exceptions.NoSuchTableError(table.name) while row: name = row['FNAME'] args = [lower_if_possible(name)] kw = {} # get the data types and lengths args.append(column_func[row['FTYPE']](row)) # is it a primary key? kw['primary_key'] = name in pkfields table.append_column(schema.Column(*args, **kw)) row = c.fetchone() # get the foreign keys c = connection.execute(fkqry, ["FOREIGN KEY", table.name.upper()]) fks = {} while True: row = c.fetchone() if not row: break cname = lower_if_possible(row['CNAME']) try: fk = fks[cname] except KeyError: fks[cname] = fk = ([], []) rname = lower_if_possible(row['RNAME']) schema.Table(rname, table.metadata, autoload=True, autoload_with=connection) fname = lower_if_possible(row['FNAME']) refspec = rname + '.' + lower_if_possible(row['SENAME']) fk[0].append(fname) fk[1].append(refspec) for name,value in fks.iteritems(): table.append_constraint(schema.ForeignKeyConstraint(value[0], value[1], name=name))
class Invoice(Entity, type_and_status.StatusMixin): book_date = schema.Column(types.Date(), nullable=False) status = type_and_status.Status()
def test_encode_date(): today = datetime.date.today() e = encode(types.Date()) d = decode(types.Date()) assert today == d(e(today))
class Invoice(meta.BaseObject): """An invoice.""" __tablename__ = "invoice" id = schema.Column(types.Integer(), schema.Sequence("invoice_id_seq", optional=True), primary_key=True, autoincrement=True) _number = schema.Column("number", types.Integer()) customer_id = schema.Column(types.Integer(), schema.ForeignKey(Customer.id, onupdate="CASCADE", ondelete="CASCADE"), nullable=False) customer = orm.relationship(Customer, backref="invoices") sent = schema.Column(types.Date()) payment_term = schema.Column(types.Integer(), nullable=False, default=30) paid = schema.Column(types.Date()) note = schema.Column(types.UnicodeText()) @orm.reconstructor def _add_acls(self): account_id = self.customer.account_id self.__acl__ = [(security.Allow, account_id, ("comment", "view"))] if not self.sent: self.__acl__.append( (security.Allow, account_id, ("delete", "edit"))) if len(self.entries): self.__acl__.append((security.Allow, account_id, "send")) if self.sent and not self.paid: self.__acl__.append((security.Allow, account_id, "mark-paid")) @property def due(self): if self.sent: return self.sent + datetime.timedelta(days=self.payment_term) return None def total(self, type="gross"): assert type in ["gross", "net", "vat"] gross = sum([entry.total for entry in self.entries]) if type == "gross": return gross vat = sum([v[1] for v in self.VAT()]) if type == "vat": return vat return gross + vat def VAT(self): totals = {} for entry in self.entries: if not entry.vat: continue current = entry.total totals[entry.vat] = totals.get(entry.vat, 0) + current for (vat, total) in totals.items(): totals[vat] = (totals[vat] * vat) / 100 return sorted(totals.items()) @synonym_for("_number") @property def number(self): if not self._number: return None return "%s.%04d" % (self.customer.invoice_code, self._number) def state(self): if not self.sent: return "unsend" elif self.paid: return "paid" today = datetime.date.today() due = self.sent + datetime.timedelta(days=self.payment_term) if due < today: return "overdue" else: return "pending" def overdue(self): if self.paid or not self.sent: return None today = datetime.date.today() due = self.sent + datetime.timedelta(days=self.payment_term) if due >= today: return None return (today - due).days def send(self): assert self.sent is None self.sent = datetime.datetime.now() self._number = self.customer.account.newInvoiceNumber()