sqlite-utils/docs/table.rst
2018-07-31 17:35:36 -07:00

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======================
Databases and Tables
======================
Database objects are constructed by passing in a SQLite3 database connection:
.. code-block:: python
from sqlite_utils import Database
import sqlite3
db = Database(sqlite3.connect("my_database.db"))
Tables are accessed using the indexing operator, like so:
.. code-block:: python
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.
Listing tables
==============
You can list the names of tables in a database using the ``.table_names`` property::
>>> db.table_names
['dogs']
You can also iterate through the table objects themselves using ``.tables``::
>>> db.tables
[<Table dogs>]
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))
Enabling full-text search
=========================
You can enable full-text search on a table using ``.enable_fts(columns)``:
.. code-block:: python
dogs.enable_fts(["name", "twitter"])
You can then run searches using the ``.search()`` method:
.. code-block:: python
rows = dogs.search("cleo")
If you insert additioal records into the table you will need to refresh the search index using ``populate_fts()``:
.. code-block:: python
dogs.insert({
"id": 2,
"name": "Marnie",
"twitter": "MarnieTheDog",
"age": 16,
"is_good_dog": True,
}, pk="id")
dogs.populate_fts(["name", "twitter"])