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Database client

crate.client.connect is the primary method to connect to CrateDB using Python. This section of the documentation outlines different methods to connect to the database cluster, as well as how to run basic inquiries to the database, and closing the connection again.

Connect to a database

Before we can start we have to import the client:

>>> from crate import client

The client provides a connect() function which is used to establish a connection, the first argument is the url of the server to connect to:

>>> connection = client.connect(crate_host)
>>> connection.close()

CrateDB is a clustered database providing high availability through replication. In order for clients to make use of this property it is recommended to specify all hosts of the cluster. This way if a server does not respond, the request is automatically routed to the next server:

>>> invalid_host = 'http://127.0.0.1:4201'
>>> connection = client.connect([invalid_host, crate_host])
>>> connection.close()

If no servers are supplied to the connect method, the default address http://127.0.0.1:4200 is used.

If the option error_trace is set to True, the client will print a whole traceback if a server error occurs:

>>> connection = client.connect([crate_host], error_trace=True)
>>> connection.close()

Network Timeouts

It's possible to define a default timeout value in seconds for all servers using the optional parameter timeout. In this case, it will serve as a total timeout (connect and read):

>>> connection = client.connect([crate_host, invalid_host], timeout=1)
>>> connection.close()

If you want to adjust the connect- vs. read-timeout values individually, please use the urllib3.Timeout object like:

>>> import urllib3
>>> connection = client.connect(
...     [crate_host, invalid_host],
...     timeout=urllib3.Timeout(connect=1, read=None))
>>> connection.close()

Authentication

Users that are trusted as by definition of the auth.host_based.config setting do not need a password, but only require the username argument to connect:

>>> connection = client.connect([crate_host],
...                             username='trusted_me')
>>> connection.client.username
'trusted_me'
>>> connection.client.password
>>> connection.close()

The username for trusted users can also be provided in the URL:

>>> connection = client.connect(['http://trusted_me@' + crate_host])
>>> connection.client.username
'trusted_me'
>>> connection.client.password
>>> connection.close()

To connect to CrateDB with as a user that requires password authentication, you also need to provide password as argument for the connect() call:

>>> connection = client.connect([crate_host],
...                             username='me',
...                             password='my_secret_pw')
>>> connection.client.username
'me'
>>> connection.client.password
'my_secret_pw'
>>> connection.close()

The authentication credentials can also be provided in the URL:

>>> connection = client.connect(['http://me:my_secret_pw@' + crate_host])
>>> connection.client.username
'me'
>>> connection.client.password
'my_secret_pw'
>>> connection.close()

Default Schema

To connect to CrateDB and use a different default schema than doc, you can provide the schema keyword argument in the connect() method, like so:

>>> connection = client.connect([crate_host],
...                             schema='custom_schema')
>>> connection.close()

Inserting Data

Use user "crate" for rest of the tests:

>>> connection = client.connect([crate_host])

Before executing any statement, a cursor has to be opened to perform database operations:

>>> cursor = connection.cursor()
>>> cursor.execute("""INSERT INTO locations
... (name, date, kind, position) VALUES (?, ?, ?, ?)""",
...                ('Einstein Cross', '2007-03-11', 'Quasar', 7))

To bulk insert data you can use the executemany function:

>>> cursor.executemany("""INSERT INTO locations
... (name, date, kind, position) VALUES (?, ?, ?, ?)""",
...                [('Cloverleaf', '2007-03-11', 'Quasar', 7),
...                 ('Old Faithful', '2007-03-11', 'Quasar', 7)])
[{'rowcount': 1}, {'rowcount': 1}]

executemany returns a list of results for every parameter. Each result contains a rowcount. If an error occurs, the rowcount is -2 and the result may contain an error_message depending on the error.

Refresh locations:

>>> cursor.execute("REFRESH TABLE locations")

Updating Data

Values for TIMESTAMP columns can be obtained as a string literal, date, or datetime object. If it contains timezone information, it is converted to UTC, and the timezone information is discarded.

>>> import datetime as dt
>>> timestamp_full = "2023-06-26T09:24:00.123+02:00"
>>> timestamp_date = "2023-06-26"
>>> datetime_aware = dt.datetime.fromisoformat("2023-06-26T09:24:00.123+02:00")
>>> datetime_naive = dt.datetime.fromisoformat("2023-06-26T09:24:00.123")
>>> datetime_date = dt.date.fromisoformat("2023-06-26")
>>> cursor.execute("UPDATE locations SET date=? WHERE name='Cloverleaf'", (timestamp_full, ))
>>> cursor.execute("UPDATE locations SET date=? WHERE name='Cloverleaf'", (timestamp_date, ))
>>> cursor.execute("UPDATE locations SET date=? WHERE name='Cloverleaf'", (datetime_aware, ))
>>> cursor.execute("UPDATE locations SET date=? WHERE name='Cloverleaf'", (datetime_naive, ))
>>> cursor.execute("UPDATE locations SET date=? WHERE name='Cloverleaf'", (datetime_date, ))

Selecting Data

To perform the select operation simply execute the statement on the open cursor:

>>> cursor.execute("SELECT name FROM locations where name = ?", ('Algol',))

To retrieve a row we can use one of the cursor's fetch functions (described below).

fetchone()

fetchone() with each call returns the next row from the results:

>>> result = cursor.fetchone()
>>> pprint(result)
['Algol']

If no more data is available, an empty result is returned:

>>> while cursor.fetchone():
...     pass
>>> cursor.fetchone()

fetchmany()

fetch_many() returns a list of all remaining rows, containing no more than the specified size of rows:

>>> cursor.execute("SELECT name FROM locations order by name")
>>> result = cursor.fetchmany(2)
>>> pprint(result)
[['Aldebaran'], ['Algol']]

If a size is not given, the cursor's arraysize, which defaults to '1', determines the number of rows to be fetched:

>>> cursor.fetchmany()
[['Allosimanius Syneca']]

It's also possible to change the cursors arraysize to an other value:

>>> cursor.arraysize = 3
>>> cursor.fetchmany()
[['Alpha Centauri'], ['Altair'], ['Argabuthon']]

fetchall()

fetchall() returns a list of all remaining rows:

>>> cursor.execute("SELECT name FROM locations order by name")
>>> result = cursor.fetchall()
>>> pprint(result)
[['Aldebaran'],
 ['Algol'],
 ['Allosimanius Syneca'],
 ['Alpha Centauri'],
 ['Altair'],
 ['Argabuthon'],
 ['Arkintoofle Minor'],
 ['Bartledan'],
 ['Cloverleaf'],
 ['Einstein Cross'],
 ['Folfanga'],
 ['Galactic Sector QQ7 Active J Gamma'],
 ['Galaxy'],
 ['North West Ripple'],
 ['Old Faithful'],
 ['Outer Eastern Rim']]

Cursor Description

The description property of the cursor returns a sequence of 7-item sequences containing the column name as first parameter. Just the name field is supported, all other fields are 'None':

>>> cursor.execute("SELECT * FROM locations order by name")
>>> result = cursor.fetchone()
>>> pprint(result)
['Aldebaran',
 1658167836758,
 1658167836758,
 1658167836758,
 None,
 None,
 'Star System',
 None,
 1,
 'Max Quordlepleen claims that the only thing left after the end of the '
 'Universe will be the sweets trolley and a fine selection of Aldebaran '
 'liqueurs.',
 None]
>>> result = cursor.description
>>> pprint(result)
(('name', None, None, None, None, None, None),
 ('date', None, None, None, None, None, None),
 ('datetime_tz', None, None, None, None, None, None),
 ('datetime_notz', None, None, None, None, None, None),
 ('nullable_datetime', None, None, None, None, None, None),
 ('nullable_date', None, None, None, None, None, None),
 ('kind', None, None, None, None, None, None),
 ('flag', None, None, None, None, None, None),
 ('position', None, None, None, None, None, None),
 ('description', None, None, None, None, None, None),
 ('details', None, None, None, None, None, None))

Closing the Cursor

The following command closes the cursor:

>>> cursor.close()

If a cursor is closed, it will be unusable from this point forward.

If any operation is attempted to a closed cursor an ProgrammingError will be raised.

>>> cursor.execute("SELECT * FROM locations")
Traceback (most recent call last):
...
crate.client.exceptions.ProgrammingError: Cursor closed

Closing the Connection

The following command closes the connection:

>>> connection.close()

If a connection is closed, it will be unusable from this point forward. If any operation using the connection is attempted to a closed connection an ProgrammingError will be raised:

>>> cursor.execute("SELECT * FROM locations")
Traceback (most recent call last):
...
crate.client.exceptions.ProgrammingError: Connection closed
>>> cursor = connection.cursor()
Traceback (most recent call last):
...
crate.client.exceptions.ProgrammingError: Connection closed