cycquery.interface.QueryInterface¶

class QueryInterface(database, query)[source]¶

Bases: object

An interface dataclass to wrap queries, and run them.

Parameters:

database (Database) – Database object to create ORM, and query data.
query (Union[Select, Subquery, Table, DBTable, QueryInterface]) – The query.

Initialize the QueryInterface object, join and chain operations.

Methods

`clear_data`	Clear data container.
`join`	Join the query with another table.
`ops`	Chain operations with the query.
`run`	Run the query, and fetch data.
`save`	Save the query.
`union`	Union the query with another query.
`union_all`	Union all the query with another query.

Attributes

data

Get data.

__init__(database, query)[source]¶: Initialize the QueryInterface object, join and chain operations.

clear_data()[source]¶

Clear data container.

Sets the data attribute to None, thus clearing the dataframe contained.

Return type:: None

property data: DataFrame | None¶: Get data.

join(join_table, on=None, on_to_type=None, cond=None, table_cols=None, join_table_cols=None, isouter=False)[source]¶

Join the query with another table.

Parameters:

join_table (Union[Select, Subquery, Table, DBTable, QueryInterface]) – Table to join with.
on (Union[str, List[str], Tuple[str], List[Tuple[str, str]], None]) – Column(s) to join on.
on_to_type (Union[type, List[type], None]) – Type(s) to cast the column(s) to join on.
cond (Optional[BinaryExpression]) – Condition to join on.
table_cols (Union[str, List[str], None]) – Columns to select from the original table.
join_table_cols (Union[str, List[str], None]) – Columns to select from the joined table.
isouter (Optional[bool]) – Whether to perform an outer join.

Returns:

QueryInterface object with the join operation added.

Return type:

QueryInterface

ops(ops)[source]¶

Chain operations with the query.

Parameters:: ops (Union[QueryOp, Sequential]) – Operations to perform on the query.
Returns:: QueryInterface object with the operations added.
Return type:: QueryInterface

run(limit=None, index_col=None, batch_mode=False, batch_size=1000000, dtype_backend='pyarrow')[source]¶

Run the query, and fetch data.

Parameters:

limit (Optional[int]) – No. of rows to limit the query return.
backend – Backend computing framework to use, pandas or dask or datasets.
index_col (Optional[str]) – Column which becomes the index, and defines the partitioning. Should be a indexed column in the SQL server, and any orderable type.
batch_mode (bool) – Whether to run the query in batch mode. A generator is returned if True.
batch_size (int) – Batch size for the query, default 1 million rows.
dtype_backend (str) – Data type to use for the backend, default pyarrow.

Returns:

Query result.

Return type:

pandas.DataFrame or Generator[pandas.DataFrame, None, None]

save(path, file_format='parquet')[source]¶

Save the query.

Parameters:

path (str) – Path where the file will be saved.
file_format (Literal['parquet', 'csv']) – File format of the file to save.

Returns:

Processed save path for upstream use.

Return type:

str

union(other)[source]¶

Union the query with another query.

Parameters:: other (QueryInterface) – The other query to union with.
Returns:: QueryInterface object with the union operation added.
Return type:: QueryInterface

union_all(other)[source]¶

Union all the query with another query.

Parameters:: other (QueryInterface) – The other query to union all with.
Returns:: QueryInterface object with the union all operation added.
Return type:: QueryInterface