cs.sqltags 20210913

Simple SQL based tagging and the associated `sqltags` command line script, supporting both tagged named objects and tagged timestamped log entries.

Simple SQL based tagging and the associated sqltags command line script, supporting both tagged named objects and tagged timestamped log entries.

Latest release 20210913:

• SQLTagsCommand: rename cmd_ns to cmd_list,cmd_ls.
• SQLTagsCommand.cmd_export: accept "-F export_format" for csv or fstags export, accept no criteria to mean all tagsets.
• Encoding schema for nonJSONable types.
• Rename the TagSets abstract base class to BaseTagSets.
• BaseSQLTagsCommand.cmd_edit: implement rename.
• Many other internal small changes.

Compared to cs.fstags and its associated fstags command, this is oriented towards large numbers of items not naturally associated with filesystem objects.

My initial use case is an activity log (unnamed timestamped tag sets) but I'm also using it for ontologies (named tag sets containing metadata).

Many basic tasks can be performed with the sqltags command line utility, documented under the SQLTagsCommand class below.

See the SQLTagsORM documentation for details about how data are stored in the database. See the SQLTagSet documentation for details of how various tag value types are supported.

Class BaseSQLTagsCommand(cs.cmdutils.BaseCommand,cs.tagset.TagsCommandMixin)

Common features for commands oriented around an SQLTags database.

Command line usage:

Usage: basesqltags [-f db_url] subcommand [...]
  -f db_url SQLAlchemy database URL or filename.
            Default from $SQLTAGS_DBURL (default '~/var/sqltags.sqlite').
  Subcommands:
    dbshell
      Start an interactive database shell.
    edit criteria...
      Edit the entities specified by criteria.
    export [-F format] [{tag[=value]|-tag}...]
      Export entities matching all the constraints.
      -F format Specify the export format, either CSV or FSTAGS.
    find [-o output_format] {tag[=value]|-tag}...
      List entities matching all the constraints.
      -o output_format
                  Use output_format as a Python format string to lay out
                  the listing.
                  Default: {datetime} {headline}
    help [subcommand-names...]
      Print the help for the named subcommands,
      or for all subcommands if no names are specified.
    import [{-u|--update}] {-|srcpath}...
      Import CSV data in the format emitted by "export".
      Each argument is a file path or "-", indicating standard input.
      -u, --update  If a named entity already exists then update its tags.
                    Otherwise this will be seen as a conflict
                    and the import aborted.
    init
      Initialise the database.
      This includes defining the schema and making the root metanode.
    log [-c category,...] [-d when] [-D strptime] {-|headline} [tags...]
      Record entries into the database.
      If headline is '-', read headlines from standard input.
      -c categories
        Specify the categories for this log entry.
        The default is to recognise a leading CAT,CAT,...: prefix.
      -d when
        Use when, an ISO8601 date, as the log entry timestamp.
      -D strptime
        Read the time from the start of the headline
        according to the provided strptime specification.
    tag {-|entity-name} {tag[=value]|-tag}...
      Tag an entity with multiple tags.
      With the form "-tag", remove that tag from the direct tags.
      A entity-name named "-" indicates that entity-names should
      be read from the standard input.

BaseSQLTagsCommand.TAGSETS_CLASS

BaseSQLTagsCommand.TAGSET_CRITERION_CLASS

BaseSQLTagsCommand.TAG_BASED_TEST_CLASS

Method BaseSQLTagsCommand.apply_defaults(self)

Set up the default values in options.

Method BaseSQLTagsCommand.apply_opt(self, opt, val)

Apply a command line option.

Method BaseSQLTagsCommand.cmd_dbshell(self, argv)

Usage: {cmd} Start an interactive database shell.

Method BaseSQLTagsCommand.cmd_edit(self, argv)

Usage: edit criteria... Edit the entities specified by criteria.

Method BaseSQLTagsCommand.cmd_export(self, argv)

Usage: {cmd} [-F format] [{{tag[=value]|-tag}}...] Export entities matching all the constraints. -F format Specify the export format, either CSV or FSTAGS.

The CSV export format is CSV data with the following columns:

• unixtime: the entity unixtime, a float
• id: the entity database row id, an integer
• name: the entity name
• tags: a column per Tag

Method BaseSQLTagsCommand.cmd_find(self, argv)

Usage: {cmd} [-o output_format] {{tag[=value]|-tag}}... List entities matching all the constraints. -o output_format Use output_format as a Python format string to lay out the listing. Default: {FIND_OUTPUT_FORMAT_DEFAULT}

Method BaseSQLTagsCommand.cmd_import(self, argv)

Usage: {cmd} [{{-u|--update}}] {{-|srcpath}}... Import CSV data in the format emitted by "export". Each argument is a file path or "-", indicating standard input. -u, --update If a named entity already exists then update its tags. Otherwise this will be seen as a conflict and the import aborted.

TODO: should this be a transaction so that an import is all or nothing?

Method BaseSQLTagsCommand.cmd_init(self, argv)

Usage: {cmd} Initialise the database. This includes defining the schema and making the root metanode.

Method BaseSQLTagsCommand.cmd_log(self, argv)

Record a log entry.

Usage: {cmd} [-c category,...] [-d when] [-D strptime] {{-|headline}} [tags...] Record entries into the database. If headline is '-', read headlines from standard input. -c categories Specify the categories for this log entry. The default is to recognise a leading CAT,CAT,...: prefix. -d when Use when, an ISO8601 date, as the log entry timestamp. -D strptime Read the time from the start of the headline according to the provided strptime specification.

Method BaseSQLTagsCommand.cmd_tag(self, argv)

Usage: {cmd} {{-|entity-name}} {{tag[=value]|-tag}}... Tag an entity with multiple tags. With the form "-tag", remove that tag from the direct tags. A entity-name named "-" indicates that entity-names should be read from the standard input.

Method BaseSQLTagsCommand.parse_categories(categories)

Extract "category" words from the str categories, return a list of category names.

Splits on commas, strips leading and trailing whitespace, downcases.

Method BaseSQLTagsCommand.parse_tagset_criterion(arg, tag_based_test_class=None)

Parse tag criteria from argv.

The criteria may be either:

• an integer specifying a Tag id
• a sequence of tag criteria

Method BaseSQLTagsCommand.run_context(self)

Prepare the SQLTags around each command invocation.

Function glob2like(glob: str) -> str

Convert a filename glob to an SQL LIKE pattern.

Function main(argv=None)

Command line mode.

Class PolyValue(PolyValue,builtins.tuple)

A namedtuple for the polyvalues used in an SQLTagsORM.

We express various types in SQL as one of 3 columns:

• float_value: for floats and ints which round trip with float
• string_value: for str
• structured_value: a JSON transcription of any other type

This allows SQL indexing of basic types.

Note that because str gets stored in string_value this leaves us free to use "bare string" JSON to serialise various nonJSONable types.

The SQLTagSets class has a to_polyvalue factory which produces a PolyValue suitable for the SQL rows. NonJSONable types such as datetime are converted to a str but stored in the structured_value column. This should be overridden by subclasses as necessary.

On retrieval from the database the tag rows are converted to Python values by the SQLTagSets.from_polyvalue method, reversing the process above.

Method PolyValue.is_valid(self)

Test that at most one attribute is non-None.

Class PolyValueColumnMixin

A mixin for classes with (float_value,string_value,structured_value) columns. This is used by the Tags and TagMultiValues relations inside SQLTagsORM.

Method PolyValueColumnMixin.as_polyvalue(self)

Return this row's value as a PolyValue.

Method PolyValueColumnMixin.set_polyvalue(self, pv: cs.sqltags.PolyValue)

Set all the value fields.

Method PolyValueColumnMixin.value_test(other_value)

Return (column,test_value) for constructing tests against other_value where column if the appropriate SQLAlchemy column and test_value is the comparison value for testing.

For most other_values the test_value will just be other_value, but for certain types the test_value will be:

• NoneType: None, and the column will also be None
• datetime: datetime2unixtime(other_value)

Function prefix2like(prefix: str, esc='\\') -> str

Convert a prefix string to an SQL LIKE pattern.

Class SQLParameters(SQLParameters,builtins.tuple)

The parameters required for constructing queries or extending queries with JOINs.

Attributes:

• criterion: the source criterion, usually an SQTCriterion subinstance
• alias: an alias of the source table for use in queries
• entity_id_column: the entities id column, alias.id if the alias is of entities, alias.entity_id if the alias is of tags
• constraint: a filter query based on alias

Class SQLTagBasedTest(cs.tagset.TagBasedTest,cs.tagset.TagBasedTest,builtins.tuple,SQTCriterion,cs.tagset.TagSetCriterion)

A cs.tagset.TagBasedTest extended with a .sql_parameters method.

Method SQLTagBasedTest.match_tagged_entity(self, te: cs.tagset.TagSet) -> bool

Match this criterion against te.

Class SQLTagProxies

A proxy for the tags supporting Python comparison => SQLParameters.

Example:

sqltags.tags.dotted.name.here == 'foo'

Class SQLTagProxy

An object based on a Tag name which produces an SQLParameters when compared with some value.

Example:

>>> sqltags = SQLTags('sqlite://')
>>> sqltags.init()
>>> # make a SQLParameters for testing the tag 'name.thing'==5
>>> sqlp = sqltags.tags.name.thing == 5
>>> str(sqlp.constraint)
'tags_1.name = :name_1 AND tags_1.float_value = :float_value_1'
>>> sqlp = sqltags.tags.name.thing == 'foo'
>>> str(sqlp.constraint)
'tags_1.name = :name_1 AND tags_1.string_value = :string_value_1'

Method SQLTagProxy.__eq__(self, other, alias=None) -> cs.sqltags.SQLParameters

Return an SQL = test SQLParameters.

Example:

>>> sqlp = SQLTags('sqlite://').tags.name.thing == 'foo'
>>> str(sqlp.constraint)
'tags_1.name = :name_1 AND tags_1.string_value = :string_value_1'

Method SQLTagProxy.__ge__(self, other)

Return an SQL >= test SQLParameters.

Example:

>>> sqlp = SQLTags('sqlite://').tags.name.thing >= 'foo'
>>> str(sqlp.constraint)
'tags_1.name = :name_1 AND tags_1.string_value >= :string_value_1'

Method SQLTagProxy.__getattr__(self, sub_tag_name)

Magic access to dotted tag names: produce a new SQLTagProxy from ourself.

Method SQLTagProxy.__gt__(self, other)

Return an SQL > test SQLParameters.

Example:

>>> sqlp = SQLTags('sqlite://').tags.name.thing > 'foo'
>>> str(sqlp.constraint)
'tags_1.name = :name_1 AND tags_1.string_value > :string_value_1'

Method SQLTagProxy.__le__(self, other)

Return an SQL <= test SQLParameters.

Example:

>>> sqlp = SQLTags('sqlite://').tags.name.thing <= 'foo'
>>> str(sqlp.constraint)
'tags_1.name = :name_1 AND tags_1.string_value <= :string_value_1'

Method SQLTagProxy.__lt__(self, other)

Return an SQL < test SQLParameters.

Example:

>>> sqlp = SQLTags('sqlite://').tags.name.thing < 'foo'
>>> str(sqlp.constraint)
'tags_1.name = :name_1 AND tags_1.string_value < :string_value_1'

Method SQLTagProxy.__ne__(self, other, alias=None) -> cs.sqltags.SQLParameters

Return an SQL <> test SQLParameters.

Example:

>>> sqlp = SQLTags('sqlite://').tags.name.thing != 'foo'
>>> str(sqlp.constraint)
'tags_1.name = :name_1 AND tags_1.string_value != :string_value_1'

Method SQLTagProxy.by_op_text(self, op_text, other, alias=None)

Return an SQLParameters based on the comparison's text representation.

Parameters:

• op_text: the comparsion operation text, one of: '=', '<=', '<', '>=', '>', '~'.
• other: the other value for the comparison, used to infer the SQL column name and kept to provide the SQL value parameter
• alias: optional SQLAlchemy table alias

Method SQLTagProxy.likeglob(self, globptn: str) -> cs.sqltags.SQLParameters

Return an SQL LIKE test approximating a glob as an SQLParameters.

Example:

>>> sqlp = SQLTags('sqlite://').tags.name.thing.likeglob('foo*')
>>> str(sqlp.constraint)
"tags_1.name = :name_1 AND tags_1.string_value LIKE :string_value_1 ESCAPE '\\'"

Method SQLTagProxy.startswith(self, prefix: str) -> cs.sqltags.SQLParameters

Return an SQL LIKE prefix test SQLParameters.

Example:

>>> sqlp = SQLTags('sqlite://').tags.name.thing.startswith('foo')
>>> str(sqlp.constraint)
"tags_1.name = :name_1 AND tags_1.string_value LIKE :string_value_1 ESCAPE '\\'"

Class SQLTags(cs.tagset.BaseTagSets,cs.resources.MultiOpenMixin,collections.abc.MutableMapping,collections.abc.Mapping,collections.abc.Collection,collections.abc.Sized,collections.abc.Iterable,collections.abc.Container)

A class using an SQL database to store its TagSets.

Method SQLTags.TagSetClass(self, *a, **kw)

Local implementation of TagSetClass so that we can annotate it with a .singleton_also_by attribute.

Method SQLTags.__getitem__(self, *a, **kw)

Return an SQLTagSet for index (an int or str).

Method SQLTags.__setitem__(self, *a, **kw)

Dummy __setitem__ which checks te against the db by type because the factory inserts it into the database.

Method SQLTags.db_entity(self, index)

Return the Entities instance for index or None.

Method SQLTags.db_session(self, *, new=False)

Context manager to obtain a db session if required, just a shim for self.orm.session().

Property SQLTags.default_db_session

The current per-Thread SQLAlchemy Session.

Method SQLTags.default_factory(self, name: [<class 'str'>, None], *, unixtime=None, tags=None)

Fetch or create an SQLTagSet for name.

Note that name may be None to create a new "log" entry.

Method SQLTags.find(self, criteria)

Generate and run a query derived from criteria yielding SQLTagSet instances.

Parameters:

• criteria: an iterable of search criteria which should be SQTCriterions or a str suitable for SQTCriterion.from_str.

Method SQLTags.flush(self)

Flush the current session state to the database.

Method SQLTags.get(self, index, default=None)

Return an SQLTagSet matching index, or None if there is no such entity.

Method SQLTags.import_csv_file(self, f, *, update_mode=False)

Import CSV data from the file f.

If update_mode is true named records which already exist will update from the data, otherwise the conflict will raise a ValueError.

Method SQLTags.import_tagged_entity(self, te, *, update_mode=False) -> None

Import the TagSet te.

This updates the database with the contents of the supplied TagSet, which has no inherent relationship to the database.

If update_mode is true named records which already exist will update from te, otherwise the conflict will raise a ValueError.

Method SQLTags.infer_db_url(envvar=None, default_path=None)

Infer the database URL.

Parameters:

• envvar: environment variable to specify a default, default from DBURL_ENVVAR (SQLTAGS_DBURL).

Method SQLTags.init(self)

Initialise the database.

Method SQLTags.items(self, *, prefix=None)

Return an iterable of (tagset_name,TagSet). Excludes unnamed TagSets.

Constrain the names to those starting with prefix if not None.

Method SQLTags.keys(self, *, prefix=None)

Yield all the nonNULL names.

Constrain the names to those starting with prefix if not None.

Property SQLTags.metanode

The metadata node.

Method SQLTags.values(self, *, prefix=None)

Return an iterable of the named TagSets. Excludes unnamed TagSets.

Constrain the names to those starting with prefix if not None.

Class SQLTagsCommand(BaseSQLTagsCommand,cs.cmdutils.BaseCommand,cs.tagset.TagsCommandMixin)

sqltags main command line utility.

Command line usage:

Usage: sqltags [-f db_url] subcommand [...]
  -f db_url SQLAlchemy database URL or filename.
            Default from $SQLTAGS_DBURL (default '~/var/sqltags.sqlite').
  Subcommands:
    dbshell
      Start an interactive database shell.
    edit criteria...
      Edit the entities specified by criteria.
    export [-F format] [{tag[=value]|-tag}...]
      Export entities matching all the constraints.
      -F format Specify the export format, either CSV or FSTAGS.
    find [-o output_format] {tag[=value]|-tag}...
      List entities matching all the constraints.
      -o output_format
                  Use output_format as a Python format string to lay out
                  the listing.
                  Default: {datetime} {headline}
    help [subcommand-names...]
      Print the help for the named subcommands,
      or for all subcommands if no names are specified.
    import [{-u|--update}] {-|srcpath}...
      Import CSV data in the format emitted by "export".
      Each argument is a file path or "-", indicating standard input.
      -u, --update  If a named entity already exists then update its tags.
                    Otherwise this will be seen as a conflict
                    and the import aborted.
    init
      Initialise the database.
      This includes defining the schema and making the root metanode.
    list [entity-names...]
      List entities and their tags.
    log [-c category,...] [-d when] [-D strptime] {-|headline} [tags...]
      Record entries into the database.
      If headline is '-', read headlines from standard input.
      -c categories
        Specify the categories for this log entry.
        The default is to recognise a leading CAT,CAT,...: prefix.
      -d when
        Use when, an ISO8601 date, as the log entry timestamp.
      -D strptime
        Read the time from the start of the headline
        according to the provided strptime specification.
    ls [entity-names...]
      List entities and their tags.
    tag {-|entity-name} {tag[=value]|-tag}...
      Tag an entity with multiple tags.
      With the form "-tag", remove that tag from the direct tags.
      A entity-name named "-" indicates that entity-names should
      be read from the standard input.

Method SQLTagsCommand.cmd_list(self, argv)

Usage: {cmd} [entity-names...] List entities and their tags.

Method SQLTagsCommand.cmd_ls(self, argv)

Usage: {cmd} [entity-names...] List entities and their tags.

Class SQLTagSet(cs.obj.SingletonMixin,cs.tagset.TagSet,builtins.dict,cs.dateutils.UNIXTimeMixin,cs.lex.FormatableMixin,cs.lex.FormatableFormatter,string.Formatter,cs.mappings.AttrableMappingMixin)

A singleton TagSet attached to an SQLTags instance.

As with the TagSet superclass, tag values can be any Python type. However, because we are storing these values in an SQL database it is necessary to provide a conversion facility to prepare those values for storage.

The database schema is described in the SQLTagsORM class; in short we directly support None, float and str, ints which round trip with float, and list, tuple and dict whose contents transcribe to JSON.

ints which are too large to round trip with float are treated as an extended "bigint" type using the scheme described below.

Because the ORM has distinct float and str columns to support indexing, there will be no plain strings in the remaining JSON blob column. Therefore we support other types by providing functions to convert each type to a str and back, and an associated "type label" which will be prefixed to the string; the resulting string is stored in the JSON blob.

The default mechanism is based on the following class attributes and methods:

• TYPE_JS_MAPPING: a mapping of a type label string to a 3 tuple of (type,to_str,from_str) being the extended type, a function to convert an instance to str and a function to convert a str to an instance of this type
• to_js_str: a method accepting (tag_name,tag_value) and returning tag_value as a str; the default implementation looks up the type of tag_value in TYPE_JS_MAPPING to locate the corresponding to_str function
• from_js_str: a method accepting (tag_name,js) which uses the leading type label prefix from the js to look up the corresponding from_str function from TYPE_JS_MAPPING and use it on the tail of js

The default TYPE_JS_MAPPING has mappings for:

• "bigint": conversions for int
• "date": conversions for datetime.date
• "datetime": conversions for datetime.datetime

Subclasses wanting to augument the TYPE_JS_MAPPING should prepare their own with code such as:

class SubSQLTagSet(SQLTagSet,....):
    ....
    TYPE_JS_MAPPING=dict(SQLTagSet.TYPE_JS_MAPPING)
    TYPE_JS_MAPPING.update(
      typelabel=(type, to_str, from_str),
      ....
    )

Method SQLTagSet.add_db_tag(self, *a, **kw)

Add a tag to the database.

Method SQLTagSet.child_tagsets(self, tag_name='parent')

Return the child TagSets as defined by their parent Tag, by default the Tag named 'parent'.

Method SQLTagSet.db_session(self, new=False)

Context manager to obtain a new session if required, just a shim for self.sqltags.db_session.

Method SQLTagSet.discard_db_tag(self, tag_name: str, pv: Optional[cs.sqltags.PolyValue] = None)

Discard a tag from the database.

Method SQLTagSet.from_js_str(tag_name: str, js: str)

Convert the str js to a Tag value. This is the reverse of as_js_str.

Subclasses wanting extra type support should either: (usual approach) provide their own TYPE_JS_MAPPING class attribute as described at the top of this class or (for unusual requirements) override this method and also to_js_str.

Method SQLTagSet.from_polyvalue(tag_name: str, pv: cs.sqltags.PolyValue)

Convert an SQL PolyValue to a tag value.

This can be overridden by subclasses along with to_polyvalue. The tag_name is provided for context in case it should influence the normalisation.

Property SQLTagSet.name

Return the .name.

Method SQLTagSet.parent_tagset(self, tag_name='parent')

Return the parent TagSet as defined by a Tag, by default the Tag named 'parent'.

Method SQLTagSet.to_js_str(tag_name: str, tag_value) -> str

Convert tag_value to a str suitable for storage in structure_value. This can be reversed by from_js_str.

Subclasses wanting extra type support should either: (usual approach) provide their own TYPE_JS_MAPPING class attribute as described at the top of this class or (for unusual requirements) override this method and also from_js_str.

Method SQLTagSet.to_polyvalue(tag_name: str, tag_value) -> cs.sqltags.PolyValue

Normalise Tag values for storage via SQL. Preserve things directly expressable in JSON. Convert other values via to_js_str. Return PolyValue for use with the SQL rows.

Class SQLTagsORM(cs.sqlalchemy_utils.ORM,cs.resources.MultiOpenMixin,cs.dateutils.UNIXTimeMixin)

The ORM for an SQLTags.

The current implementation uses 3 tables:

• entities: this has a NULLable name and unixtime UNIX timestamp; this is unique per name if the name is not NULL
• tags: this has an entity_id, name and a value stored in one of three columns: float_value, string_value and structured_value which is a JSON blob; this is unique per (entity_id,name)
• tag_subvalues: this is a broken out version of tags when structured_value is a sequence or mapping, breaking out the values one per row; this exists to support "tag contains value" lookups

Tag values are stored as follows:

• None: all 3 columns are set to NULL
• float: stored in float_value
• int: if the int round trips to float then it is stored in float_value, otherwise it is stored in structured_value with the type label "bigint"
• str: stored in string_value
• list, tuple, dict: stored in structured_value; if these containers contain unJSONable content there will be trouble
• other types, such as datetime: these are converted to strings with identifying type label prefixes and stored in structured_value

The float_value and string_value columns allow us to provide indices for these kinds of tag values.

The type label scheme takes advantage of the fact that actual strs are stored in the string_value column. Because of this, there will be no actual strings in structured_value. Therefore, we can convert nonJSONable types to str and store them here.

The scheme used is to provide conversion functions to convert types to str and back, and an associated "type label" prefix. For example, we store a datetime as the ISO format of the datetime with "datetime:" prefixed to it.

The actual conversions are kept with the SQLTagSet class (or any subclass). This ORM receives the 3-tuples of SQL ready values from that class as the PolyValue namedtuple and does not perform any conversion itself. The conversion process is described in SQLTagSet.

Method SQLTagsORM.declare_schema(self)

Define the database schema / ORM mapping.

Method SQLTagsORM.define_schema(self)

Instantiate the schema and define the root metanode.

Method SQLTagsORM.prepare_metanode(self, *, session)

Ensure row id 0, the metanode, exists.

Method SQLTagsORM.search(self, *a, **kw)

Construct a query to match Entity rows matching the supplied criteria iterable. Return an SQLAlchemy Query.

The mode parameter has the following values:

• 'id': the query only yields entity ids
• 'entity': (default) the query yields entities without tags
• 'tagged': (default) the query yields entities left outer joined with their matching tags

Note that the 'tagged' result produces multiple rows for any entity with multiple tags, and that this requires the caller to fold entities with multiple tags together.

Note: due to implementation limitations the SQL query itself may not apply all the criteria, so every criterion must still be applied to the results using its .match_entity method.

If name is omitted or None the query will match log entities otherwise the entity with the specified name.

The criteria should be an iterable of SQTCriterion instances used to construct the query.

Class SQTCriterion(cs.tagset.TagSetCriterion)

Subclass of TagSetCriterion requiring an .sql_parameters method which returns an SQLParameters providing the information required to construct an sqlalchemy query. It also resets .CRITERION_PARSE_CLASSES, which will pick up the SQL capable criterion classes below.

SQTCriterion.TAG_BASED_TEST_CLASS

Method SQTCriterion.match_tagged_entity(self, te: cs.tagset.TagSet) -> bool

Perform the criterion test on the Python object directly. This is used at the end of a query to implement tests which cannot be sufficiently implemented in SQL. If self.SQL_COMPLETE it is not necessary to call this method.

Method SQTCriterion.sql_parameters(self, orm) -> cs.sqltags.SQLParameters

Subclasses must return am SQLParameters instance parameterising the SQL queries that follow.

Class SQTEntityIdTest(SQTCriterion,cs.tagset.TagSetCriterion)

A test on entity.id.

Method SQTEntityIdTest.match_tagged_entity(self, te: cs.tagset.TagSet) -> bool

Test the TagSet te against self.entity_ids.

Method SQTEntityIdTest.parse(s, offset=0, delim=None)

Parse a decimal entity id from s.

Function verbose(msg, *a)

Emit message if in verbose mode.

Release Log

Release 20210913:

• SQLTagsCommand: rename cmd_ns to cmd_list,cmd_ls.
• SQLTagsCommand.cmd_export: accept "-F export_format" for csv or fstags export, accept no criteria to mean all tagsets.
• Encoding schema for nonJSONable types.
• Rename the TagSets abstract base class to BaseTagSets.
• BaseSQLTagsCommand.cmd_edit: implement rename.
• Many other internal small changes.

Release 20210420:

• New PolyValueMixin pulled out of Tags for common support of the (float_value,string_value,structured_value).
• SQLTagsORM: new TagSubValues relation containing broken out values for values which are sequences, to support efficient lookup if sequence values such as log entry categories.
• New BaseSQLTagsCommand.parse_categories static method to parse FOO,BAH into ['foo','bah'].
• sqltags find: change default format to "{datetime} {headline}".
• Assorted small changes.

Release 20210404:

• SQLTags.getitem: when autocreating an entity, do it in a new session so that the entity is commited to the database before any further use.
• SQLTagsCommand: new cmd_dbshell to drop you into the database.

Release 20210321: Drop logic now merged with cs.sqlalchemy_utils, use the new default session stuff.

Release 20210306.1: Docstring updates.

Release 20210306: Initial release.