execute_scalar
execute_scalar executes the query, and returns the first column of the first row in the result set returned by
the query. The additional columns or rows are ignored.
Parameters🔗
All command methods also accept keyword-only options=; see Command options.
| name | type | description | optional | default |
|---|---|---|---|---|
| sql | str |
the sql query str to execute | ||
| params | ParamType |
params to substitute in the query | None |
param= remains accepted as a 1.x compatibility alias for params=. Pass only one of the two names.
Parameter Shapes🔗
params accepts one parameter record: a mapping, mapping subclass, mutable mapping, or object/dataclass with attributes
matching the placeholder names. Top-level list params are only for execute and execute_async; read and scalar methods
raise InvalidParameterShapeException for top-level lists before opening a cursor.
params=None, param=None, or omitting both names means there is no parameter object. If the SQL contains pydapper
placeholders such as ?id?, every referenced placeholder must be supplied or pydapper raises
MissingParameterException before calling the DBAPI. An empty mapping is a real parameter record with no keys. A list
inside one parameter record, such as {"ids": []} or {"ids": [1, 2, 3]}, is one value and is reserved for future IN
list expansion support.
Tuple-query APIs (query_multiple and query_multiple_async) apply this validation to the complete tuple: the
placeholders of every query are scanned and every referenced value is resolved before a cursor is acquired or the
first query executes, so a missing parameter in any query means no query reaches the database. This is client-side
prevalidation, not transaction atomicity; after validation succeeds, a later query can still fail at runtime after
earlier queries have executed.
Cardinality🔗
- 0 rows: raises
NoResultException. - 1+ rows: returns the first column of the first row.
- SQL
NULLin the first column is returned as PythonNone.
Example🔗
Get the name of the first task owner in the database.
from pydapper import connect
with connect() as commands:
owner_name = commands.execute_scalar("select name from owner")
print(owner_name)
# Zach Schumacher