sqlite-utils/docs/table.rst

=======
 Table
=======

Tables are accessed using the indexing operator, like so:

.. code-block:: python

    from sqlite_utils import Database
    import sqlite3

    db = Database(sqlite3.connect("my_database.db"))
    table = db["my_table"]

If the table does not yet exist, it will be created the first time you attempt to insert or upsert data into it.

Creating tables
===============

The easiest way to create a new table is to insert a record into it:

.. code-block:: python

    from sqlite_utils import Database
    import sqlite3

    db = Database(sqlite3.connect("/tmp/dogs.db"))
    dogs = db["dogs"]
    dogs.insert({
        "name": "Cleo",
        "twitter": "cleopaws",
        "age": 3,
        "is_good_dog": True,
    })

This will automatically create a new table called "dogs" with the following schema::

    CREATE TABLE dogs (
        name TEXT,
        twitter TEXT,
        age INTEGER,
        is_good_dog INTEGER
    )

The column types are automatically derived from the types of the incoming data.

You can also specify a primary key by passing the ``pk=`` parameter to the ``.insert()`` call. This will only be obeyed if the record being inserted causes the table to be created:

.. code-block:: python

    dogs.insert({
        "id": 1,
        "name": "Cleo",
        "twitter": "cleopaws",
        "age": 3,
        "is_good_dog": True,
    }, pk="id")

Introspection
=============

If you have loaded an existing table, you can use introspection to find out more about it::

    >>> db["PlantType"]
    <sqlite_utils.db.Table at 0x10f5960b8>

The ``.count`` property shows the current number of rows (``select count(*) from table``)::

    >>> db["PlantType"].count
    3
    >>> db["Street_Tree_List"].count
    189144

The ``.columns`` property shows the columns in the table::

    >>> db["PlantType"].columns
    [Column(cid=0, name='id', type='INTEGER', notnull=0, default_value=None, is_pk=1),
     Column(cid=1, name='value', type='TEXT', notnull=0, default_value=None, is_pk=0)]

The ``.foreign_keys`` property shows if the table has any foreign key relationships::

    >>> db["Street_Tree_List"].foreign_keys
    [ForeignKey(table='Street_Tree_List', column='qLegalStatus', other_table='qLegalStatus', other_column='id'),
     ForeignKey(table='Street_Tree_List', column='qCareAssistant', other_table='qCareAssistant', other_column='id'),
     ForeignKey(table='Street_Tree_List', column='qSiteInfo', other_table='qSiteInfo', other_column='id'),
     ForeignKey(table='Street_Tree_List', column='qSpecies', other_table='qSpecies', other_column='id'),
     ForeignKey(table='Street_Tree_List', column='qCaretaker', other_table='qCaretaker', other_column='id'),
     ForeignKey(table='Street_Tree_List', column='PlantType', other_table='PlantType', other_column='id')]

The ``.schema`` property outputs the table's schema as a SQL string::

    >>> print(db["Street_Tree_List"].schema)
    CREATE TABLE "Street_Tree_List" (
    "TreeID" INTEGER,
      "qLegalStatus" INTEGER,
      "qSpecies" INTEGER,
      "qAddress" TEXT,
      "SiteOrder" INTEGER,
      "qSiteInfo" INTEGER,
      "PlantType" INTEGER,
      "qCaretaker" INTEGER,
      "qCareAssistant" INTEGER,
      "PlantDate" TEXT,
      "DBH" INTEGER,
      "PlotSize" TEXT,
      "PermitNotes" TEXT,
      "XCoord" REAL,
      "YCoord" REAL,
      "Latitude" REAL,
      "Longitude" REAL,
      "Location" TEXT
    ,
    FOREIGN KEY ("PlantType") REFERENCES [PlantType](id),
        FOREIGN KEY ("qCaretaker") REFERENCES [qCaretaker](id),
        FOREIGN KEY ("qSpecies") REFERENCES [qSpecies](id),
        FOREIGN KEY ("qSiteInfo") REFERENCES [qSiteInfo](id),
        FOREIGN KEY ("qCareAssistant") REFERENCES [qCareAssistant](id),
        FOREIGN KEY ("qLegalStatus") REFERENCES [qLegalStatus](id))