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cs.sqltags-20230217
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مشاهده بیشترتوضیحات
Simple SQL based tagging and the associated `sqltags` command line script, supporting both tagged named objects and tagged timestamped log entries.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | cs.sqltags-20230217 |
| نام | cs.sqltags |
| نسخه کتابخانه | 20230217 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Cameron Simpson |
| ایمیل نویسنده | Cameron Simpson <cs@cskk.id.au> |
| آدرس صفحه اصلی | https://bitbucket.org/cameron_simpson/css/commits/all |
| آدرس اینترنتی | https://pypi.org/project/cs.sqltags/ |
| مجوز | GNU General Public License v3 or later (GPLv3+) |
Simple SQL based tagging
and the associated `sqltags` command line script,
supporting both tagged named objects and tagged timestamped log entries.
*Latest release 20230217*:
SQLTagsORM.search: previous changes seem to have dropped SQTCriterion support.
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: {localtime} {headline}
help [-l] [subcommand-names...]
Print the full help for the named subcommands,
or for all subcommands if no names are specified.
-l Long help even if no subcommand-names provided.
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.
orm define_schema
Runs the ORM's `define_schema()` method, which creates missing tables
and entity 0 if missing.
shell
Run an interactive Python prompt with some predefined local names.
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.
## 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 `float`s and `int`s 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.
## 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`.
## 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, cs.deco.Promotable)`
A `cs.tagset.TagBasedTest` extended with a `.sql_parameters` method.
## 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'
## Class `SQLTags(cs.tagset.BaseTagSets, cs.resources.MultiOpenMixin, cs.context.ContextManagerMixin, collections.abc.MutableMapping, collections.abc.Mapping, collections.abc.Collection, collections.abc.Sized, collections.abc.Iterable, collections.abc.Container, cs.deco.Promotable)`
A class using an SQL database to store its `TagSet`s.
## 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: {localtime} {headline}
help [-l] [subcommand-names...]
Print the full help for the named subcommands,
or for all subcommands if no names are specified.
-l Long help even if no subcommand-names provided.
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.
orm define_schema
Runs the ORM's `define_schema()` method, which creates missing tables
and entity 0 if missing.
shell
Run an interactive Python prompt with some predefined local names.
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.
## 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`,
`int`s which round trip with `float`,
and `list`, `tuple` and `dict` whose contents transcribe to JSON.
`int`s 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),
....
)
## Class `SQLTagsORM(cs.sqlalchemy_utils.ORM, cs.resources.MultiOpenMixin, cs.context.ContextManagerMixin, 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 `str`s
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`.
## Class `SQTCriterion(cs.tagset.TagSetCriterion, cs.deco.Promotable)`
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.
## Class `SQTEntityIdTest(SQTCriterion, cs.tagset.TagSetCriterion, cs.deco.Promotable)`
A test on `entity.id`.
## Function `verbose(msg, *a)`
Emit message if in verbose mode.
# Release Log
*Release 20230217*:
SQLTagsORM.search: previous changes seem to have dropped SQTCriterion support.
*Release 20230212.1*:
Mark SQLTags as promotable.
*Release 20230212*:
* @promote support for SQLTags, promoting a filesystem path to a .sqlite db.
* Simpler SQLTagsORM.search comparison implementation.
* SQLTagSet: inherit format attributes from superclasses (TagSet).
* New BaseSQLTagsCommand.cmd_shell method.
* New BaseSQLTagsCommand.cmd_orm method with "define_schema" subcommand to update the db schema.
* SQLTagsORM.__init__: drop case_sensitive, no longer supported?
* SQLTagsORM.__init__: always call define_schema, it seems there are scenarios where this does some necessary sqlalchemy prep.
*Release 20221228*:
SQLTagsCommand: update implementation of BaseCommand.run_context to use super().run_context().
*Release 20220806*:
* Bugfix for SQLTagsORM.search(mode='entity').
* SQLTags.find: new _without_tags=False parameter to allow fast searches omitting the entity tags.
*Release 20220606*:
* New SQLTagsORM.Entities.add_new_tags method, use it in SQLTags.default_factory for bulk insert.
* SQTCriterion: new .from_equality(tag_name,tag_value) factory to make an equality criterion.
* SQLTags.find: accept criteria as positional parameters instead of a single iterable, accept new keyword parameters as equality criteria.
* SQLTags.__getitem__: accept a slice to index the .unixtime tag.
* SQLTagsORM: also turn on echo mode if "ECHO" in $SQLTAGS_MODES.
*Release 20220311*:
Assorted updates.
*Release 20211212*:
* Rename edit_many to edit_tagsets for clarity.
* Small bugfixes.
*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.
نیازمندی
| مقدار | نام |
|---|---|
| >=20210404 | cs.cmdutils |
| >=20230212 | cs.context |
| >=20230210 | cs.dateutils |
| >=20230212 | cs.deco |
| >=20221118 | cs.fileutils |
| >=20230217 | cs.lex |
| >=20230212 | cs.logutils |
| >=20220918 | cs.obj |
| >=20221118 | cs.pfx |
| >=20210420 | cs.sqlalchemy-utils |
| >=20211212 | cs.tagset |
| >=20201025 | cs.threads |
| >=20230217 | cs.upd |
| - | icontract |
| - | sqlalchemy |
| - | typeguard |
نحوه نصب
نصب پکیج whl cs.sqltags-20230217:
pip install cs.sqltags-20230217.whl
نصب پکیج tar.gz cs.sqltags-20230217:
pip install cs.sqltags-20230217.tar.gz