def collect(transform: dict, expr: ibis.Expr) -> ibis.Expr:
fields = promote_list(transform["sort"]["field"])
orders = promote_list(transform["sort"].get("order", ["ascending"] * len(fields)))
assert len(fields) == len(orders)
rules = [
(field, (True if order == "ascending" else False))
for field, order in zip(fields, orders)
]
return expr.sort_by(rules)
def maybe_add_random_sort(
self, data_client: ibis.client, table: ibis.Expr
) -> ibis.Expr:
"""Return a randomly sorted query if it is supported for the client."""
if type(data_client) in RANDOM_SORT_SUPPORTS:
return table.sort_by(
RandomSortKey(RANDOM_SORT_SUPPORTS[type(data_client)]).to_expr()
)
if type(data_client) != TeradataClient:
# Teradata 'SAMPLE' is random by nature and does not require a sort by
logging.warning(
"Data Client %s Does Not Enforce Random Sort on Sample",
str(type(data_client)),
)
return table
def collect(transform: dict, expr: ibis.Expr) -> ibis.Expr:
"""
Apply a vega collect transform to an ibis expression.
https://vega.github.io/vega/docs/transforms/collect/
Parameters
----------
transform: dict
A JSON-able dictionary representing the vega transform.
expr: ibis.Expr
The expression to which to apply the transform.
Returns
-------
transformed_expr: the transformed expression
"""
fields = promote_list(transform["sort"]["field"])
orders = promote_list(transform["sort"].get("order",
["ascending"] * len(fields)))
assert len(fields) == len(orders)
rules = [(field, (True if order == "ascending" else False))
for field, order in zip(fields, orders)]
return expr.sort_by(rules)