class pipableai.core.postgresql_connector.PostgresConfig(host: str, port: int, database: str, user: str, password: str)

Bases: object

Data class for PostgreSQL connection configuration.

Args:

host (str): The hostname or IP address of the PostgreSQL server. port (int): The port number to connect to on the PostgreSQL server. database (str): The name of the PostgreSQL database. user (str): The username for connecting to the PostgreSQL server. password (str): The password for the specified username.

Attributes:

host (str): The hostname or IP address of the PostgreSQL server. port (int): The port number to connect to on the PostgreSQL server. database (str): The name of the PostgreSQL database. user (str): The username for connecting to the PostgreSQL server. password (str): The password for the specified username.

database: str

host: str

password: str

port: int

user: str

class pipableai.core.postgresql_connector.PostgresConnector(config: PostgresConfig)

Bases: DatabaseConnectorInterface

A class for establishing and managing the PostgreSQL database connection.

This class provides methods for connecting to a remote PostgreSQL server and executing SQL queries. It uses the psycopg2 library for database interaction.

Args:

config (PostgresConfig): The configuration for connecting to the PostgreSQL server.

Attributes:

config (PostgresConfig): The configuration for connecting to the PostgreSQL server. connection (psycopg2.extensions.connection): The connection to the PostgreSQL server. cursor (psycopg2.extensions.cursor): The cursor for executing SQL queries.

Raises:

ConnectionError: If failed to connect to the PostgreSQL server. ValueError: If an error occurs during query execution.

Note:

The execute_query method returns the query results as a Pandas DataFrame.

Warning:

Ensure to disconnect from the database using the disconnect method after executing queries to release resources.

Example:

To establish a connection and execute a query, create an instance of PostgresConnector and call the execute_query method.

from pipable.connector import PostgresConnector, PostgresConfig

# Define PostgreSQL configuration
postgres_config = PostgresConfig(
    host="your_postgres_host",
    port=5432,  # Replace with your port number
    database="your_database_name",
    user="your_username",
    password="your_password",
)

# Initialize the PostgresConnector instance
connector = PostgresConnector(postgres_config)

# Execute a SQL query
result = connector.execute_query("SELECT * FROM Employees")

connect()

Establish a connection to the PostgreSQL server.

disconnect()

Close the connection to the PostgreSQL server.

execute_query(query: str) → DataFrame

Execute an SQL query on the connected PostgreSQL server and return the result as a Pandas DataFrame.

Args:

query (str): The SQL query to execute.

Returns:

DataFrame: A Pandas DataFrame representing the query results.

Raises:

ValueError: If an error occurs during query execution.