semvec/pypi-packages huggingface dataset:
spatialiteintrospect 1.2
Python library for easily retrieving table names, geometry columns, geometry tables, etc from a Spatialite database

spatialite-introspect
=====================

Python library to do introspection in Sqlite/Spatialite databases.

Useful to get the table names, the column names of a specific table, the
available geometry columns, etc, without needing to dig in SQL.

Installation
------------

::

    pip install spatialiteintrospect

Dependences
-----------

spatialite-introspect uses
`sqlite3 <https://docs.python.org/2/library/sqlite3.html>`__, which
should be included in any Python distribution since version 2.5.

Usage
-----

Basic usage:

::

    import spatialiteintrospect as spintrospect

    # open db connection
    db = spintrospect.connect("mydb.sqlite")

    # get all the tables in the db
    db.get_tables()
    # The result is an array of table names, e.g.: ['tbl1', 'tbl2', 'tbl3']

    # finally, we need to close the database
    db.close()

Available methods:

::

    # get all the tables in the db
    db.get_tables()
    # The result is an array of table names, e.g.: ['tbl1', 'tbl2', 'tbl3']

    # get all the tables that contain at least one geometry field
    db.get_geometry_tables()
    # The result is an array of table names, e.g.: ['tbl1', 'tbl3']

    # get the geometry columns of a specific table
    db.get_geometry_columns("tbl1")
    # The result is an array of column names, e.g.: ['the_point_geom', 'the_line_geom']

    # get the geometry columns of a specific tables, plus some information about the table containing it
    db.get_geometry_columns_info("tbl1")
    # The result is an array of tuples such as
    #     [
    #         ('tbl1', 'the_point_geom', 2, 4326, 1, ['fid'], ['fid', 'title', 'the_point_geom', 'the_line_geom']),
    #         ('tbl1', 'the_line_geom', 2, 4326, 2, ['fid'], ['fid', 'title', 'the_point_geom', 'the_line_geom'])
    #     ]
    # The contents of each tuple is: (table_name, geom_column, coord_dimension, srid, geometry_type, key_columns, fields)

    # It also works with no table filter:
    db.get_geometry_columns_info()
    # Result:
    #     [
    #         ('tbl1', 'the_point_geom', 2, 4326, 1, ['fid'], ['fid', 'title', 'the_point_geom', 'the_line_geom']),
    #         ('tbl1', 'the_line_geom', 2, 4326, 2, ['fid'], ['fid', 'title', 'the_point_geom', 'the_line_geom']),
    #         ('tbl3', 'geom', 2, 4326, 1, ['fid'], ['fid', 'author', 'date', 'geom'])
    #     ]

    # get the primary column(s) of a table
    db.get_pk_columns("tbl2")
    # The result is an array of the fields that compose the PK: ['country_cd', 'region_cd']

    # get all the fields of a table
    db.get_fields("tbl1")
    # The result is an array of field names such as ['fid', 'title', 'the_point_geom', 'the_line_geom']

Note that the library expects Unicode strings on all the string params.
Non unicode strings are also accepted if using ASCII-only characters.

Authors
-------

Cesar Martinez Izquierdo - `Scolab <http://scolab.es>`__