Python DB API Driver

Use the GridGain 9 Python Database API driver to connect to a cluster, configure SSL and authentication, run queries, and manage transactions.

GridGain 9 clients connect to the cluster via a standard socket connection. Clients do not become a part of the cluster topology, never hold any data, and are not used as a destination for compute calculations.

GridGain DB API driver uses the Python Database API.

Getting Started

Prerequisites

To run the Python driver, the following is required:

• CMake 3.18 or newer to build the driver

• Python 3.10 or newer (3.10, 3.11, 3.12, 3.13 and 3.14 are tested)

• Access to a running Ignite 3 or GridGain 9 node

Limitations

Script execution of SQL statements is not supported in current release.

Installation

To install Python DB API driver, download it from pip.

pip install pygridgain_dbapi

After this, you can import pygridgain_dbapi into your project and use it.

Connecting to Cluster

To connect to the cluster, use the connect() method:

addr = ['127.0.0.1:10800']
return pygridgain_dbapi.connect(address=addr, timeout=10)

Connection Parameters

The connect() function accepts the following parameters:

Parameter	Type	Description
address	str or list[str]	Required. Cluster node address(es) for initial connection and fail-over. Examples: 'localhost:10800' or ['host1:10800', 'host2:10800']
identity	str	Username for authentication. Used with secret for basic authentication.
secret	str	Password for authentication. Used with identity for basic authentication.
schema	str	Default schema name. Default: 'PUBLIC'
timezone	str	Client timezone for date/time operations. Default: server timezone
page_size	int	Maximum rows per request. Default: 1024
timeout	int	Network operation timeout in seconds. Default: 30
heartbeat_interval	float	Heartbeat interval in seconds. Set to 0 to disable. Default: 1.0
autocommit	bool	Enable automatic transaction commit. Default: True
use_ssl	bool	Enable SSL/TLS encryption. Default: False
ssl_keyfile	str	Path to SSL key file. Required if use_ssl=True and using client authentication.
ssl_certfile	str	Path to SSL certificate file. Required if use_ssl=True and using client authentication.
ssl_ca_certfile	str	Path to CA certificate for server validation. Required if use_ssl=True.

After you are done working with the cluster, remember to always close the connection to it.

conn.close()

Alternatively, you can use the with statement to automatically close the connection when no longer necessary:

with pygridgain_dbapi.connect(address=addr, timeout=10) as conn:
  conn.cursor()

Configuring SSL for Connection

To ensure secure connection to the cluster, you can enable SSL for it by providing the key file and certificate, for example:

def create_ssl_connection():
  """Create SSL-enabled connection to GridGain cluster."""
  addr = ['127.0.0.1:10800']
  return pygridgain_dbapi.connect(
      address=addr,
      timeout=10,
      use_ssl=True,
      ssl_keyfile='<path_to_ssl_keyfile.pem>',
      ssl_certfile='<path_to_ssl_certfile.pem>',
      # Optional: ssl_ca_certfile='<path_to_ssl_ca_certfile.pem>'
  )

All paths to certificate file and keys should be provided in string format appropriate for the system.

Configuring Authorization

If the cluster uses basic authorization, you need to provide user identity and secret to authorize on it, for example:

def create_authenticated_connection():
  """Create authenticated connection to GridGain cluster."""
  addr = ['127.0.0.1:10800']
  return pygridgain_dbapi.connect(
      address=addr,
      timeout=10,
      identity='user',
      secret='password'
  )

Configuring Data Access

You can configure optional properties to fine-tune how data is accessed and how the connection behaves.

Configuration name	Default	Description
schema	'PUBLIC'	A schema name to be used by default.
page_size	1024	Maximum number of rows that can be received or sent in a single request.
timeout	30	Timeout for network operations, in seconds.
heartbeat_interval	1.0	Interval between heartbeat probes, in seconds. Set to 0 or negative to disable heartbeats. See Connection Heartbeats for details.
timezone	(server)	Client's timezone. Required to correctly work with date/time values. By default, server's timezone is used.

The example below shows how to set these properties:

def create_configured_connection():
  """Create authenticated connection to GridGain cluster."""
  addr = ['127.0.0.1:10800']
  return conn = pygridgain_dbapi.connect(
    address=addr,
    timeout=10,
    schema='CUSTOM',
    page_size=2048
  )

You can also configure timeout and heartbeat_interval parameters. See Connection Parameters Reference for the full list of available parameters.

Connection Heartbeats

The Python DB API driver supports connection heartbeats to prevent the server from closing idle connections. When enabled, the driver automatically sends periodic heartbeat messages to the server during periods of inactivity.

The driver tracks when the last message was sent to the server. If the connection is idle for longer than the heartbeat_interval, a heartbeat message is sent. If other queries or operations are executed, no heartbeat is needed. Heartbeats keep the connection alive without requiring application changes.

By default, heartbeats are sent every 1 second. You can customize the heartbeat interval or disable it by setting the interval to 0:

# Custom heartbeat interval (10 seconds)
conn = pyignite_dbapi.connect(
    address='localhost:10800',
    heartbeat_interval=10.0
)

# Disable heartbeats
conn = pyignite_dbapi.connect(
    address='localhost:10800',
    heartbeat_interval=0
)

Disabling heartbeats may cause the server to close idle connections after its configured idle timeout period. Only disable heartbeats if you ensure continuous activity or can handle reconnection

Getting Cursor Object

To work with tables from Python client, you use the cursor object that can be retrieved from the connection object:

conn.cursor()

Similar to the connection, you can use the with statement when getting the cursor:

with conn.cursor() as cursor:

Executing Single Query

The cursor object can be used to execute SQL statements with the execute command:

# Create table
cursor.execute('''
          CREATE TABLE Person(
              id INT PRIMARY KEY,
              name VARCHAR,
              age INT
          )
      ''')

Executing a Batched Query

You can use the executemany command to execute SQL queries with a batch of parameters. This kind of operation offers much higher performance than executing individual queries. The example below inserts two rows into the Person table:

# Sample data
sample_data = [
  [1, "John", 30],
  [2, "Jane", 32],
  [3, "Bob", 28]
]

# Insert data (fixed table name)
cursor.executemany('INSERT INTO Person VALUES(?, ?, ?)', sample_data)

Getting Query Results

The cursor retains a reference to the operation. If the operation returns results (for example, a SELECT), they will also be stored in the cursor. You can then use the fetchone() method to retrieve query results from the cursor:

# Query data
cursor.execute('SELECT * FROM Person ORDER BY id')
results = cursor.fetchall()

print("All persons in database:")
for row in results:
  print(f"ID: {row[0]}, Name: {row[1]}, Age: {row[2]}")

Working with Transactions

By default, transactions required for database operations are handled implicitly. However, you can disable automatic transaction handling and manually handle commits.

To do this, first, disable autocommit:

conn.autocommit = False

Once autocommit is disabled, you need to commit your operations manually:

# Insert valid records
cursor.execute('INSERT INTO Person VALUES(?, ?, ?)', [4, "Alice", 29])
cursor.execute('INSERT INTO Person VALUES(?, ?, ?)', [5, "Charlie", 31])

cursor.execute('INSERT INTO Person VALUES(?, ?, ?)', [6, "Invalid", new_age])

conn.commit()
print("Transaction committed successfully")

Operations that are not committed are sent to the cluster, but not yet written to the table. The table is only updated when the commit method is called. You can roll back all uncommitted operations with the rollback command:

with conn.cursor() as cursor:
  try:
    # Insert valid records
    cursor.execute('INSERT INTO Person VALUES(?, ?, ?)', [4, "Alice", 29])
    cursor.execute('INSERT INTO Person VALUES(?, ?, ?)', [5, "Charlie", 31])

    cursor.execute('INSERT INTO Person VALUES(?, ?, ?)', [6, "Invalid", new_age])

    conn.commit()
    print("Transaction committed successfully")

  except Exception as e:
    # Rollback on any error
    conn.rollback()
    print(f"Transaction rolled back due to error: {e}")

The rollback command rolls back all uncommitted data.