Database

matchbox.common.db

Common database utilities for Matchbox.

Functions:

• sql_to_df –

  Executes the given SQLAlchemy statement or SQL string using Polars.

• validate_sql_for_data_extraction –

  Validates that the SQL statement only contains a single data-extracting command.

Attributes:

• ReturnTypeStr –
• QueryReturnType –

ReturnTypeStr module-attribute

ReturnTypeStr = Literal['arrow', 'pandas', 'polars']

QueryReturnType module-attribute

QueryReturnType = Table | DataFrame | DataFrame

sql_to_df

sql_to_df(
    stmt: str,
    connection: Engine | Connection,
    return_type: Literal["arrow", "pandas", "polars"],
    *,
    return_batches: Literal[False] = False,
    batch_size: int | None = None,
    rename: dict[str, str] | Callable | None = None,
    schema_overrides: dict[str, Any] | None = None,
    execute_options: dict[str, Any] | None = None,
) -> QueryReturnType

sql_to_df(
    stmt: str,
    connection: Engine | Connection,
    return_type: Literal["arrow", "pandas", "polars"],
    *,
    return_batches: Literal[True],
    batch_size: int | None = None,
    rename: dict[str, str] | Callable | None = None,
    schema_overrides: dict[str, Any] | None = None,
    execute_options: dict[str, Any] | None = None,
) -> Iterator[QueryReturnType]

sql_to_df(
    stmt: str,
    connection: Engine | Connection,
    return_type: ReturnTypeStr = "pandas",
    *,
    return_batches: bool = False,
    batch_size: int | None = None,
    rename: dict[str, str] | Callable | None = None,
    schema_overrides: dict[str, Any] | None = None,
    execute_options: dict[str, Any] | None = None,
) -> QueryReturnType | Iterator[QueryReturnType]

Executes the given SQLAlchemy statement or SQL string using Polars.

Parameters:

• stmt

  (str) –

  A SQL string to be executed.

• connection

  (Engine | Connection) –

  A SQLAlchemy Engine object or ADBC connection.

• return_type

  (str, default: 'pandas' ) –

  The type of the return value. One of “arrow”, “pandas”, or “polars”.

• return_batches

  (bool, default: False ) –

  If True, return an iterator that yields each batch separately. If False, return a single DataFrame with all results. Default is False.

• batch_size

  (int | None, default: None ) –

  Indicate the size of each batch when processing data in batches. Default is None.

• rename

  (dict[str, str] | Callable | None, default: None ) –

  A dictionary mapping old column names to new column names, or a callable that takes a DataFrame and returns a DataFrame with renamed columns. Default is None.

• schema_overrides

  (dict[str, Any] | None, default: None ) –

  A dictionary mapping column names to dtypes. Default is None.

• execute_options

  (dict[str, Any] | None, default: None ) –

  These options will be passed through into the underlying query execution method as kwargs. Default is None.

Returns:

• QueryReturnType | Iterator[QueryReturnType] –

  If return_batches is False: A dataframe of the query results in the specified format.

• QueryReturnType | Iterator[QueryReturnType] –

  If return_batches is True: An iterator of dataframes in the specified format.

Raises:

• ValueError –
  • If the connection is not properly configured or if an unsupported return type is specified.
  • If batch_size and return_batches are either both set or both unset.

validate_sql_for_data_extraction

validate_sql_for_data_extraction(sql: str) -> bool

Validates that the SQL statement only contains a single data-extracting command.

Parameters:

• sql

  (str) –

  The SQL statement to validate

Returns:

• bool ( bool ) –

  True if the SQL statement is valid

Raises:

• ParseError –

  If the SQL statement cannot be parsed

• MatchboxSourceExtractTransformError –

  If validation requirements are not met