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+%global _empty_manifest_terminate_build 0
+Name: python-banner-storedot
+Version: 2.3.1
+Release: 1
+Summary: light dal package
+License: MIT License
+URL: https://https://github.com/storedot/banner
+Source0: https://mirrors.nju.edu.cn/pypi/web/packages/1e/d1/a1d53b6a74d2ebc3277fa5d5e708c01cc8d8f9020c99f60f66907e8e5895/banner-storedot-2.3.1.tar.gz
+BuildArch: noarch
+
+Requires: python3-wheel
+Requires: python3-mysqlclient
+Requires: python3-redis
+Requires: python3-pandas
+Requires: python3-joblib
+Requires: python3-psycopg2
+
+%description
+# banner.connection:
+ ## Connection(Object):
+ - ABS class
+
+ ## RelationalConnection(Connection):
+ - ABS class
+
+ ## Storage(Connection):
+ - ABS class
+
+ ## PrintableConnection(Connection):
+ - ABS class
+
+ ## MySqlConnection(RelationalConnection, PrintableConnection)(host, user, passwd, db, ssl_key, ssl_cert, name):
+ - Create Connection object compatible with banner.queries
+ - **raises MySQLError for bad connection**
+
+ ## PostgresSqlConnection(RelationalConnection, PrintableConnection)(host, user, port=5432, passwd=None, db=None, ssl_key=None, ssl_cert=None, charset='utf8', name=None):
+ - Create Connection object compatible with banner.queries
+ - **raises MySQLError for bad connection**
+
+ ## RedisConnection(Storage, PrintableConnection)(host, port, passwd, db, ssl_key, ssl_cert, name, ttl):
+ - Create CacheConnection object compatible with banner.queries
+
+# banner.queries.Queries:
+ ## CONNECTIONS(conns: Dict[str, Connection] = {}) -> :
+ - Getter/Setter for known(default) Connections dict
+
+ ## CACHE(con: CacheConnection = None):
+ - Getter/Setter for known(default) CacheConnection
+
+ ## simple_query(query: str, w2p_parse: bool = True, connection: Union[Connection, str] = None, cache: Storage = None, ttl: int = None) -> pd.DataFrame:
+ - run a simple string query for Connection
+ - connection=None try to get first known connection, **raise KeyError if None found**
+ - Cache the result if cache_connection or Queries.CACHE is set (ttl if provided otherwise use CACHE.ttl)
+ - Cache=False will not cache the result even if Queries.CACHE is set
+ - w2p_parse=True - should parse query according to w2p syntax
+
+ ## describe_table(table: str, connection: Union[RelationalConnection, str] = None) -> pd.DataFrame:
+ - Describes a table in connection
+ - Raises OperationalError and KeyError(Failed to find a connection for given key)
+
+ ## describe(connection: Union[RelationalConnection, str] = None) -> pd.DataFrame:
+ - Describe Table names in connection
+ - Raises OperationalError and KeyError(Failed to find a connection for given key)
+
+ ## table_query(table: str, columns: Union[list, str] = '*', condition: str = 'TRUE', connection=None, cache_connection=None, ttl=None, raw=False) -> pd.DataFrame:
+ - Queries a given connection for 'SELECT {columns} FROM {table} WHERE {condition}'
+ - Accepts both column values and labels
+ - raw=True - column names as in db
+ - Queries a given Connection(ip)/str of a known connection (or first known) return result as DataFrame
+ - Cache the result if cache_connection or Queries.CACHE is set (ttl if provided otherwise use CACHE.ttl)
+ - Cache=False will not cache the result even if Queries.CACHE is set
+ - Raises OperationalError and KeyError(Failed to find a connection for given key)
+
+ ## neware_cache_query(keys: Iterable, condition: str = 'TRUE', connection: Union[MySqlConnection, str] = None, cache: Storage = None, ttl: int = None) -> pd.DataFrame:
+ - simplified query to retrieve aggregate cache data by condition
+ - condition is a valid where clause for given connection type
+ - requires keys in the form Iterable(Tuple(ip, device, unit, channel, test)), ex: [(241, 240222, 6, 11, 2818575226)]
+ - Cache the result if cache_connection or Queries.CACHE is set (ttl if provided otherwise use CACHE.ttl)
+ - Cache=False will not cache the result even if Queries.CACHE is set
+
+ ## neware_query(device: int, unit: int, channel: int, test: int, connection: Union[Connection, str] = None, cache_connection=None, ttl=None, raw=False, dqdv=False, condition: str = '1', temperature: bool = True, cache_data: pd.DataFrame = pd.DataFrame()) -> pd.DataFrame:
+ - query Connection for device, unit, channel, test
+ - connection=None try to get first known connection, **raise KeyError if None found**
+ - temperature=True - fetch temperature data
+ - raw=False - compute temperature, voltage, current aswell as grouping by auxchl_id
+ - dqdv=True -> banner.neware.calc_dq_dv
+ - Cache the result if cache_connection or Queries.CACHE is set (ttl if provided otherwise use CACHE.ttl)
+ - Cache=False will not cache the result even if Queries.CACHE is set
+ - **raises Type err if no data exists**
+
+ ## neware_tests_query(table: str, experiments: Union[list, Number, str] = [], templates: Union[list, Number, str] = [], tests: Union[list, Number, str] = [], cells: Union[list,Number, str] = [], condition: str = 'cycle < 2', raw=False, dqdv=False, temperature: bool = True, connection: Union[Connection, str] = None, cache_connection=None, ttl=None):
+ - Multi Process Queries.neware_query (number of processes = number of distinct connections found for input)
+ - Queries all available tests for given table AND experiments AND templates AND tests AND cells
+ - Union[list, Number, str] - single/list of numbers or a valid query
+ - temperature=True - fetch temperature data
+ - raw=False - compute temperature, voltage, current aswell as grouping by auxchl_id
+ - dqdv=True -> banner.neware.calc_dq_dv
+ - Cache the result if cache_connection or Queries.CACHE is set (ttl if provided otherwise use CACHE.ttl)
+ - Cache=False will not cache the result even if Queries.CACHE is set
+ - **raises Type err if no data exists**
+
+# banner.neware:
+ ## NEWARE_STEPS:
+ - Step number : Step Name Dictionary
+
+ ## calculate_neware_columns(data: pd.DataFrame):
+ - calculate neware columns for a valid neware DataFrame
+
+ ## calculate_dq_dv(data: pd.DataFrame, raw=False):
+ - Calculate DQ/DV for a valid neware df
+ - raw=False: remove outliers
+
+ ## merge_cache(data: pd.DataFrame, cache_data: pd.DataFrame):
+ - Given data(neware df), cache_data(neware_cache df), tries to merge cache_data into data
+ - ** Raises TypeError and Index Error**
+
+# banner.utils.web2py:
+ ## JOINS:
+ - Default Joins dictionary
+ - Used when calling DataFrame.join_table without specifing how to join
+
+ ## COLUMN_TO_LABEL:
+ - Column : Label Dictionary
+
+ ## LABEL_TO_COLUMN:
+ - Label : Column Dictionary
+
+# banner.pandas_decorator:
+ ## Added functionality onto Pandas.DataFrame object
+
+ ## DataFrame.table_query
+ - banner.queries.Queries.table_query
+
+ ## DataFrame.calculate_neware_columns
+ - banner.neware.calculate_neware_columns
+
+ ## DataFrame.calculate_dq_dv
+ - banner.neware.calculate_dq_dv
+
+ ## join_table(table: str, columns: Union[list, str] = '*', condition: str = 'TRUE', left: Union[str, list, None] = None, right: Union[str, list, None] = None, how: Union[str, None] = None, connection: Union[RelationalConnection, str] = None, raw: bool = False, cache: Storage=None, ttl: Union[bool, None] = None) -> pd.DataFrame:
+ - Given a table, Join its relevant Data with the current table_query DataFrame!
+ - table: any table under the available Connection
+ - columns: select specific columns from the table, default=All
+ - condition: additional filtering condition on merged data
+ - left: columns used to merge left DataFrame, default is picked from banner.utils.web2py.JOINS
+ - right: columns used to merge right DataFrame, default is picked from banner.utils.web2py.JOINS
+ - how: how to merge left and right, default is picked from banner.utils.web2py.JOINS
+ - connection=None try to get first known connection, **raise KeyError if None found**
+ - **raise TypeError If failed to join**
+
+
+%package -n python3-banner-storedot
+Summary: light dal package
+Provides: python-banner-storedot
+BuildRequires: python3-devel
+BuildRequires: python3-setuptools
+BuildRequires: python3-pip
+%description -n python3-banner-storedot
+# banner.connection:
+ ## Connection(Object):
+ - ABS class
+
+ ## RelationalConnection(Connection):
+ - ABS class
+
+ ## Storage(Connection):
+ - ABS class
+
+ ## PrintableConnection(Connection):
+ - ABS class
+
+ ## MySqlConnection(RelationalConnection, PrintableConnection)(host, user, passwd, db, ssl_key, ssl_cert, name):
+ - Create Connection object compatible with banner.queries
+ - **raises MySQLError for bad connection**
+
+ ## PostgresSqlConnection(RelationalConnection, PrintableConnection)(host, user, port=5432, passwd=None, db=None, ssl_key=None, ssl_cert=None, charset='utf8', name=None):
+ - Create Connection object compatible with banner.queries
+ - **raises MySQLError for bad connection**
+
+ ## RedisConnection(Storage, PrintableConnection)(host, port, passwd, db, ssl_key, ssl_cert, name, ttl):
+ - Create CacheConnection object compatible with banner.queries
+
+# banner.queries.Queries:
+ ## CONNECTIONS(conns: Dict[str, Connection] = {}) -> :
+ - Getter/Setter for known(default) Connections dict
+
+ ## CACHE(con: CacheConnection = None):
+ - Getter/Setter for known(default) CacheConnection
+
+ ## simple_query(query: str, w2p_parse: bool = True, connection: Union[Connection, str] = None, cache: Storage = None, ttl: int = None) -> pd.DataFrame:
+ - run a simple string query for Connection
+ - connection=None try to get first known connection, **raise KeyError if None found**
+ - Cache the result if cache_connection or Queries.CACHE is set (ttl if provided otherwise use CACHE.ttl)
+ - Cache=False will not cache the result even if Queries.CACHE is set
+ - w2p_parse=True - should parse query according to w2p syntax
+
+ ## describe_table(table: str, connection: Union[RelationalConnection, str] = None) -> pd.DataFrame:
+ - Describes a table in connection
+ - Raises OperationalError and KeyError(Failed to find a connection for given key)
+
+ ## describe(connection: Union[RelationalConnection, str] = None) -> pd.DataFrame:
+ - Describe Table names in connection
+ - Raises OperationalError and KeyError(Failed to find a connection for given key)
+
+ ## table_query(table: str, columns: Union[list, str] = '*', condition: str = 'TRUE', connection=None, cache_connection=None, ttl=None, raw=False) -> pd.DataFrame:
+ - Queries a given connection for 'SELECT {columns} FROM {table} WHERE {condition}'
+ - Accepts both column values and labels
+ - raw=True - column names as in db
+ - Queries a given Connection(ip)/str of a known connection (or first known) return result as DataFrame
+ - Cache the result if cache_connection or Queries.CACHE is set (ttl if provided otherwise use CACHE.ttl)
+ - Cache=False will not cache the result even if Queries.CACHE is set
+ - Raises OperationalError and KeyError(Failed to find a connection for given key)
+
+ ## neware_cache_query(keys: Iterable, condition: str = 'TRUE', connection: Union[MySqlConnection, str] = None, cache: Storage = None, ttl: int = None) -> pd.DataFrame:
+ - simplified query to retrieve aggregate cache data by condition
+ - condition is a valid where clause for given connection type
+ - requires keys in the form Iterable(Tuple(ip, device, unit, channel, test)), ex: [(241, 240222, 6, 11, 2818575226)]
+ - Cache the result if cache_connection or Queries.CACHE is set (ttl if provided otherwise use CACHE.ttl)
+ - Cache=False will not cache the result even if Queries.CACHE is set
+
+ ## neware_query(device: int, unit: int, channel: int, test: int, connection: Union[Connection, str] = None, cache_connection=None, ttl=None, raw=False, dqdv=False, condition: str = '1', temperature: bool = True, cache_data: pd.DataFrame = pd.DataFrame()) -> pd.DataFrame:
+ - query Connection for device, unit, channel, test
+ - connection=None try to get first known connection, **raise KeyError if None found**
+ - temperature=True - fetch temperature data
+ - raw=False - compute temperature, voltage, current aswell as grouping by auxchl_id
+ - dqdv=True -> banner.neware.calc_dq_dv
+ - Cache the result if cache_connection or Queries.CACHE is set (ttl if provided otherwise use CACHE.ttl)
+ - Cache=False will not cache the result even if Queries.CACHE is set
+ - **raises Type err if no data exists**
+
+ ## neware_tests_query(table: str, experiments: Union[list, Number, str] = [], templates: Union[list, Number, str] = [], tests: Union[list, Number, str] = [], cells: Union[list,Number, str] = [], condition: str = 'cycle < 2', raw=False, dqdv=False, temperature: bool = True, connection: Union[Connection, str] = None, cache_connection=None, ttl=None):
+ - Multi Process Queries.neware_query (number of processes = number of distinct connections found for input)
+ - Queries all available tests for given table AND experiments AND templates AND tests AND cells
+ - Union[list, Number, str] - single/list of numbers or a valid query
+ - temperature=True - fetch temperature data
+ - raw=False - compute temperature, voltage, current aswell as grouping by auxchl_id
+ - dqdv=True -> banner.neware.calc_dq_dv
+ - Cache the result if cache_connection or Queries.CACHE is set (ttl if provided otherwise use CACHE.ttl)
+ - Cache=False will not cache the result even if Queries.CACHE is set
+ - **raises Type err if no data exists**
+
+# banner.neware:
+ ## NEWARE_STEPS:
+ - Step number : Step Name Dictionary
+
+ ## calculate_neware_columns(data: pd.DataFrame):
+ - calculate neware columns for a valid neware DataFrame
+
+ ## calculate_dq_dv(data: pd.DataFrame, raw=False):
+ - Calculate DQ/DV for a valid neware df
+ - raw=False: remove outliers
+
+ ## merge_cache(data: pd.DataFrame, cache_data: pd.DataFrame):
+ - Given data(neware df), cache_data(neware_cache df), tries to merge cache_data into data
+ - ** Raises TypeError and Index Error**
+
+# banner.utils.web2py:
+ ## JOINS:
+ - Default Joins dictionary
+ - Used when calling DataFrame.join_table without specifing how to join
+
+ ## COLUMN_TO_LABEL:
+ - Column : Label Dictionary
+
+ ## LABEL_TO_COLUMN:
+ - Label : Column Dictionary
+
+# banner.pandas_decorator:
+ ## Added functionality onto Pandas.DataFrame object
+
+ ## DataFrame.table_query
+ - banner.queries.Queries.table_query
+
+ ## DataFrame.calculate_neware_columns
+ - banner.neware.calculate_neware_columns
+
+ ## DataFrame.calculate_dq_dv
+ - banner.neware.calculate_dq_dv
+
+ ## join_table(table: str, columns: Union[list, str] = '*', condition: str = 'TRUE', left: Union[str, list, None] = None, right: Union[str, list, None] = None, how: Union[str, None] = None, connection: Union[RelationalConnection, str] = None, raw: bool = False, cache: Storage=None, ttl: Union[bool, None] = None) -> pd.DataFrame:
+ - Given a table, Join its relevant Data with the current table_query DataFrame!
+ - table: any table under the available Connection
+ - columns: select specific columns from the table, default=All
+ - condition: additional filtering condition on merged data
+ - left: columns used to merge left DataFrame, default is picked from banner.utils.web2py.JOINS
+ - right: columns used to merge right DataFrame, default is picked from banner.utils.web2py.JOINS
+ - how: how to merge left and right, default is picked from banner.utils.web2py.JOINS
+ - connection=None try to get first known connection, **raise KeyError if None found**
+ - **raise TypeError If failed to join**
+
+
+%package help
+Summary: Development documents and examples for banner-storedot
+Provides: python3-banner-storedot-doc
+%description help
+# banner.connection:
+ ## Connection(Object):
+ - ABS class
+
+ ## RelationalConnection(Connection):
+ - ABS class
+
+ ## Storage(Connection):
+ - ABS class
+
+ ## PrintableConnection(Connection):
+ - ABS class
+
+ ## MySqlConnection(RelationalConnection, PrintableConnection)(host, user, passwd, db, ssl_key, ssl_cert, name):
+ - Create Connection object compatible with banner.queries
+ - **raises MySQLError for bad connection**
+
+ ## PostgresSqlConnection(RelationalConnection, PrintableConnection)(host, user, port=5432, passwd=None, db=None, ssl_key=None, ssl_cert=None, charset='utf8', name=None):
+ - Create Connection object compatible with banner.queries
+ - **raises MySQLError for bad connection**
+
+ ## RedisConnection(Storage, PrintableConnection)(host, port, passwd, db, ssl_key, ssl_cert, name, ttl):
+ - Create CacheConnection object compatible with banner.queries
+
+# banner.queries.Queries:
+ ## CONNECTIONS(conns: Dict[str, Connection] = {}) -> :
+ - Getter/Setter for known(default) Connections dict
+
+ ## CACHE(con: CacheConnection = None):
+ - Getter/Setter for known(default) CacheConnection
+
+ ## simple_query(query: str, w2p_parse: bool = True, connection: Union[Connection, str] = None, cache: Storage = None, ttl: int = None) -> pd.DataFrame:
+ - run a simple string query for Connection
+ - connection=None try to get first known connection, **raise KeyError if None found**
+ - Cache the result if cache_connection or Queries.CACHE is set (ttl if provided otherwise use CACHE.ttl)
+ - Cache=False will not cache the result even if Queries.CACHE is set
+ - w2p_parse=True - should parse query according to w2p syntax
+
+ ## describe_table(table: str, connection: Union[RelationalConnection, str] = None) -> pd.DataFrame:
+ - Describes a table in connection
+ - Raises OperationalError and KeyError(Failed to find a connection for given key)
+
+ ## describe(connection: Union[RelationalConnection, str] = None) -> pd.DataFrame:
+ - Describe Table names in connection
+ - Raises OperationalError and KeyError(Failed to find a connection for given key)
+
+ ## table_query(table: str, columns: Union[list, str] = '*', condition: str = 'TRUE', connection=None, cache_connection=None, ttl=None, raw=False) -> pd.DataFrame:
+ - Queries a given connection for 'SELECT {columns} FROM {table} WHERE {condition}'
+ - Accepts both column values and labels
+ - raw=True - column names as in db
+ - Queries a given Connection(ip)/str of a known connection (or first known) return result as DataFrame
+ - Cache the result if cache_connection or Queries.CACHE is set (ttl if provided otherwise use CACHE.ttl)
+ - Cache=False will not cache the result even if Queries.CACHE is set
+ - Raises OperationalError and KeyError(Failed to find a connection for given key)
+
+ ## neware_cache_query(keys: Iterable, condition: str = 'TRUE', connection: Union[MySqlConnection, str] = None, cache: Storage = None, ttl: int = None) -> pd.DataFrame:
+ - simplified query to retrieve aggregate cache data by condition
+ - condition is a valid where clause for given connection type
+ - requires keys in the form Iterable(Tuple(ip, device, unit, channel, test)), ex: [(241, 240222, 6, 11, 2818575226)]
+ - Cache the result if cache_connection or Queries.CACHE is set (ttl if provided otherwise use CACHE.ttl)
+ - Cache=False will not cache the result even if Queries.CACHE is set
+
+ ## neware_query(device: int, unit: int, channel: int, test: int, connection: Union[Connection, str] = None, cache_connection=None, ttl=None, raw=False, dqdv=False, condition: str = '1', temperature: bool = True, cache_data: pd.DataFrame = pd.DataFrame()) -> pd.DataFrame:
+ - query Connection for device, unit, channel, test
+ - connection=None try to get first known connection, **raise KeyError if None found**
+ - temperature=True - fetch temperature data
+ - raw=False - compute temperature, voltage, current aswell as grouping by auxchl_id
+ - dqdv=True -> banner.neware.calc_dq_dv
+ - Cache the result if cache_connection or Queries.CACHE is set (ttl if provided otherwise use CACHE.ttl)
+ - Cache=False will not cache the result even if Queries.CACHE is set
+ - **raises Type err if no data exists**
+
+ ## neware_tests_query(table: str, experiments: Union[list, Number, str] = [], templates: Union[list, Number, str] = [], tests: Union[list, Number, str] = [], cells: Union[list,Number, str] = [], condition: str = 'cycle < 2', raw=False, dqdv=False, temperature: bool = True, connection: Union[Connection, str] = None, cache_connection=None, ttl=None):
+ - Multi Process Queries.neware_query (number of processes = number of distinct connections found for input)
+ - Queries all available tests for given table AND experiments AND templates AND tests AND cells
+ - Union[list, Number, str] - single/list of numbers or a valid query
+ - temperature=True - fetch temperature data
+ - raw=False - compute temperature, voltage, current aswell as grouping by auxchl_id
+ - dqdv=True -> banner.neware.calc_dq_dv
+ - Cache the result if cache_connection or Queries.CACHE is set (ttl if provided otherwise use CACHE.ttl)
+ - Cache=False will not cache the result even if Queries.CACHE is set
+ - **raises Type err if no data exists**
+
+# banner.neware:
+ ## NEWARE_STEPS:
+ - Step number : Step Name Dictionary
+
+ ## calculate_neware_columns(data: pd.DataFrame):
+ - calculate neware columns for a valid neware DataFrame
+
+ ## calculate_dq_dv(data: pd.DataFrame, raw=False):
+ - Calculate DQ/DV for a valid neware df
+ - raw=False: remove outliers
+
+ ## merge_cache(data: pd.DataFrame, cache_data: pd.DataFrame):
+ - Given data(neware df), cache_data(neware_cache df), tries to merge cache_data into data
+ - ** Raises TypeError and Index Error**
+
+# banner.utils.web2py:
+ ## JOINS:
+ - Default Joins dictionary
+ - Used when calling DataFrame.join_table without specifing how to join
+
+ ## COLUMN_TO_LABEL:
+ - Column : Label Dictionary
+
+ ## LABEL_TO_COLUMN:
+ - Label : Column Dictionary
+
+# banner.pandas_decorator:
+ ## Added functionality onto Pandas.DataFrame object
+
+ ## DataFrame.table_query
+ - banner.queries.Queries.table_query
+
+ ## DataFrame.calculate_neware_columns
+ - banner.neware.calculate_neware_columns
+
+ ## DataFrame.calculate_dq_dv
+ - banner.neware.calculate_dq_dv
+
+ ## join_table(table: str, columns: Union[list, str] = '*', condition: str = 'TRUE', left: Union[str, list, None] = None, right: Union[str, list, None] = None, how: Union[str, None] = None, connection: Union[RelationalConnection, str] = None, raw: bool = False, cache: Storage=None, ttl: Union[bool, None] = None) -> pd.DataFrame:
+ - Given a table, Join its relevant Data with the current table_query DataFrame!
+ - table: any table under the available Connection
+ - columns: select specific columns from the table, default=All
+ - condition: additional filtering condition on merged data
+ - left: columns used to merge left DataFrame, default is picked from banner.utils.web2py.JOINS
+ - right: columns used to merge right DataFrame, default is picked from banner.utils.web2py.JOINS
+ - how: how to merge left and right, default is picked from banner.utils.web2py.JOINS
+ - connection=None try to get first known connection, **raise KeyError if None found**
+ - **raise TypeError If failed to join**
+
+
+%prep
+%autosetup -n banner-storedot-2.3.1
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+ find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+ find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+ find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+ find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+ find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-banner-storedot -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 29 2023 Python_Bot <Python_Bot@openeuler.org> - 2.3.1-1
+- Package Spec generated
generated by cgit v1.2.3 (git 2.25.1) at 2025-07-12 19:45:10 +0000