Connect using the SingleStore Python Client
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The SingleStore Python client ("the client") is a Python Database API compliant database connector that can be used to connect to your SingleStore database.
Note
To facilitate transition from existing MySQL clients, the parameter substitution syntax is changed starting from the client v0.:1
for positional and :key
for dictionary keys (named) to %s
for positional and %(key)s
for dictionary keys.
Install the SingleStore Python Client
To install the client using pip
, run the following command:
pip install singlestoredb
Connect to SingleStore
You can connect to a SingleStore database using keyword parameters or a URL.
Connect using the Python Database API Parameters
To connect to a SingleStore cluster, use the following parameters:
-
host
: hostname or IP address of the SingleStore cluster -
port
: database server port -
user
: name of the database user -
password
: password of the database user -
database
(optional): name of the database
For a complete list of supported parameters, see singlestoredb.
import singlestoredb as s2conn = s2.connect(host='...', port='...', user='...',password='...', database='...')
Connect using a URL
You can specify the URL in the connection parameters, as follows:
import singlestoredb as s2conn = s2.connect('user:password@host:port/database')
You can specify the connection parameters either in the connection string or in the URL.local_
:
-
Specify the connection parameter in the URL:
conn = s2.connect('https://user:password@host:port/database?local_infile=True') -
Specify the connection parameter in the connection string:
conn = s2.connect('https://host:port/database', user='...', password='...',local_infile=True)
Execute Queries
Once a database connection is established, you can use a cursor to execute queries.Connection.
function.
If a query parameter requires substitution, it can be specified in the following two formats:
-
Named: (
%(varname)s
) -
Positional: (
%s
)
The substituted data values are automatically quoted and escaped.
Named Substitutions
When using named substitutions, you must pass a dictionary type data structure to the Cursor.
function, where the keys map to the names specified in the substitution and the values specify the substitute value.
The following example substitutes %(pattern)s
with the value 'auto%'
:
with conn.cursor() as cur:cur.execute('show variables like %(pattern)s', dict(pattern='auto%'))for row in cur.fetchall():print(row)
Positional Substitutions
When using positional parameters, you must pass a list or a tuple type data structure to the Cursor.
function.
The following example substitutes %s
with the value 'auto%'
:
with conn.cursor() as cur:cur.execute('show variables like %s', ['auto%'])for row in cur.fetchall():print(row)
Fetch Results
The Python Database API provides three Cursor
functions to fetch results:
-
Cursor.
: Use this function to fetch a single row from the result set.fetchone() -
Cursor.
: Use this function to fetch all rows in a result set.fetchall() -
Cursor.
: Use this function to fetch a specified number of rows.fetchmany([size])
Result Formats
You can specify the data structure format for the results using the results_
parameter.
Here's some examples to get results in a specific data format:
-
Tuples:
with s2.connect(results_type='tuple') as conn:with conn.cursor() as cur:cur.execute('show variables like "auto%"')for row in cur.fetchall():print(row) -
Named tuples:
with s2.connect(results_type='namedtuple') as conn:with conn.cursor() as cur:cur.execute('show variables like "auto%"')for row in cur.fetchall():print(row) -
Dictionaries:
with s2.connect(results_type='dict') as conn:with conn.cursor() as cur:cur.execute('show variables like "auto%"')for row in cur.fetchall():print(row)
API Reference
The SingleStore Python Client API Reference lists the Python Database API objects, functions, and properties that the SingleStore Python client supports.
Data Type Conversion
The following table maps the SingleStore data types to the corresponding HTTP and Python data type.
Type Name |
Type Code |
HTTP Type |
Python Type |
---|---|---|---|
TINYINT BOOL BOOLEAN |
1 |
TINYINT or UNSIGNED TINYINT |
int |
SMALLINT |
2 |
SMALLINT or UNSIGNED SMALLINT |
int |
MEDIUMINT INT24 |
9 |
MEDIUMINT |
int |
INT INTEGER |
3 |
INT or UNSIGNED INT |
int |
BIGINT |
8 |
BIGINT or UNSIGNED BIGINT |
int |
FLOAT |
4 |
FLOAT |
float |
DOUBLE REAL |
5 |
DOUBLE |
float |
DECIMAL DEC FIXED NUMERIC |
0 |
DECIMAL |
decimal. |
DATE |
10 |
DATE |
datetime. |
TIME |
11 |
TIME |
datetime. |
TIME(6) |
11 |
TIME |
datetime. |
DATETIME |
12 |
DATETIME |
datetime. |
DATETIME(6) |
12 |
DATETIME |
datetime. |
TIMESTAMP |
7 |
TIMESTAMP |
datetime. |
TIMESTAMP(6) |
7 |
TIMESTAMP |
datetime. |
YEAR |
13 |
YEAR |
int |
CHAR(LEN) |
254 |
CHAR |
str |
BINARY(LEN) |
254 |
BINARY |
bytes |
VARCHAR |
15 / 253 |
VARCHAR |
str |
VARBINARY |
15 / 253 |
VARBINARY |
bytes |
LONGTEXT |
251 |
LONGTEXT |
str |
MEDIUMTEXT |
250 |
MEDIUMTEXT |
str |
TEXT |
252 |
TEXT |
str |
TINYTEXT |
249 |
TINYTEXT |
str |
LONGBLOB |
251 |
LONGBLOB |
bytes |
MEDIUMBLOB |
250 |
MEDIUMBLOB |
bytes |
BLOB |
252 |
BLOB |
bytes |
TINYBLOB |
249 |
TINYBLOB |
bytes |
JSON |
245 |
JSON |
dict / list |
GEOGRAPHYPOINT |
|||
GEOGRAPHY |
|||
ENUM |
247 |
ENUM |
|
SET |
248 |
SET |
list[str] |
BIT |
16 |
BIT |
bytes |
Examples
We'll use the following connection parameters in the examples:
-
host='localhost'
-
port='3306'
-
user='root'
-
password='passkey'
-
database='dbTest'
-
results_
(optional)type='tuple'
Example 1
The following example connects a SingleStore database to Python and performs CRUD operations in the database using Python.
Connect to SingleStore
Create a new .
file (say pTest.
import singlestoredb as s2conn = s2.connect(host='localhost', port='3306', user='root', password='passkey', database='dbTest', results_type='tuple')with conn:with conn.cursor() as cur:flag = cur.is_connected();print(flag)
Run the following command:
python3 pTest.py
True
Create Operation Example
Add the following code to a .
file (say pCTest.
import singlestoredb as s2conn = s2.connect(host='localhost', port='3306', user='root', password='passkey', database='dbTest')data = [(1, "KorE"),(2, "PamY"),(3, "TabK"),]stmt = 'INSERT INTO testID (ID, Code) VALUES (%s, %s)'with conn:conn.autocommit(True)with conn.cursor() as cur:cur.execute('CREATE TABLE testID (ID INT PRIMARY KEY, Code VARCHAR(4));')cur.executemany(stmt, data)
Run the following command:
python3 pCTest.py
This example executes the INSERT
query against multiple sets of parameters using the Cursor.
function.
Run the following command in your SQL tool:
DESC testID;
+-------+------------+------+------+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------+------------+------+------+---------+-------+
| ID | int(11) | NO | PRI | NULL | |
| Code | varchar(4) | YES | | NULL | |
+-------+------------+------+------+---------+-------+
Read Operation Example
Add the following code to a .
file (say pRTest.
import singlestoredb as s2conn = s2.connect(host='localhost', port='3306', user='root', password='passkey', database='dbTest', results_type='tuple')with conn:conn.autocommit(True)with conn.cursor() as cur:cur.execute('SELECT * FROM testID')for row in cur.fetchall():print(row)
Run the following command:
python3 pRTest.py
(2, 'PamY')
(1, 'KorE')
(3, 'TabK')
Update Operation Example
Add the following code to a .
file (say pUTest.
import singlestoredb as s2conn = s2.connect(host='localhost', port='3306', user='root', password='passkey', database='dbTest', results_type='tuple')with conn:conn.autocommit(True)with conn.cursor() as cur:cur.execute('UPDATE testID SET Code = "DanI" WHERE ID =3')cur.execute('SELECT * FROM testID')for row in cur.fetchall():print(row)
Run the following command:
python3 pUTest.py
(2, 'PamY')
(3, 'DanI')
(1, 'KorE')
Delete Operation Example
Add the following code to a .
file (say pDTest.
import singlestoredb as s2conn = s2.connect(host='localhost', port='3306', user='root', password='passkey', database='dbTest', results_type='tuple')with conn:conn.autocommit(True)with conn.cursor() as cur:cur.execute('DELETE FROM testID WHERE ID = 2')cur.execute('SELECT * FROM testID')for row in cur.fetchall():print(row)
Run the following command:
python3 pDTest.py
(1, 'KorE')
(3, 'DanI')
Example 2: Using Substitutions
The following examples show how to use substitutions.
Using Positional Substitutions
The following example shows how to use positional substitutions:
import singlestoredb as s2conn = s2.connect(host='localhost', port='3306', user='root', password='passkey', database='dbTest')with conn:conn.autocommit(True)with conn.cursor() as cur:cur.execute('INSERT INTO testID values(%s, %s)', [2, 'RegG'])cur.execute('SELECT * FROM testID')for row in cur.fetchall():print(row)
Run the following command:
python3 pTest.py
(2, 'RegG')
(1, 'KorE')
(3, 'DanI')
Using Named Substitutions
The following example shows how to use named substitutions:
import singlestoredb as s2conn = s2.connect(host='localhost', port='3306', user='root', password='passkey', database='dbTest')with conn:conn.autocommit(True)with conn.cursor() as cur:cur.execute('INSERT INTO testID (id, code) VALUES (%s, %s)', (4, 'GarY'))cur.execute('SELECT * FROM testID')for row in cur.fetchall():print(row)
Run the following command:
python3 pTest.py
(4, 'GarY')
(2, 'RegG')
(1, 'KorE')
(3, 'DanI')
Example 3: Connect using URL
The following example shows how to connect to a SingleStore cluster via Python using a URL..
file (say testURL.
import singlestoredb as s2conn = s2.connect('root:passkey@localhost:3306/dbTest')with conn:with conn.cursor() as cur:flag = cur.is_connected();print(flag)
Run the following command to test the connection:
python3 testURL.py
True
Example 4: Specify Result Format
The following example returns the result in the dictionary format.
import singlestoredb as s2conn = s2.connect(host='localhost', port='3306', user='root', password='passkey', database='dbTest', results_type='dict')with conn:conn.autocommit(True)with conn.cursor() as cur:cur.execute('SELECT * FROM testID')for row in cur.fetchall():print(row)
Run the following command:
python3 testFormat.py
{'ID': 2, 'Code': 'RegG'}
{'ID': 4, 'Code': 'GarY'}
{'ID': 3, 'Code': 'DanI'}
{'ID': 1, 'Code': 'KorE'}
You can specify other supported formats using the results_
parameter as shown in this example.
Last modified: August 13, 2024