Frequently Asked Questions

What is the difference between inplace and by reference operations?

Rayforce-Py supports two modes of operation for table queries: inplace and by reference. Understanding the difference is crucial for working effectively with tables.

Inplace Operations

Inplace operations work directly on an in-memory Table object. The table exists as a Python object in your current session, typically created using methods like Table.from_dict(), Table.from_csv(), or returned from a previous query.

>>> from rayforce import Table, Vector, Symbol, I64, Column

>>> # Create an in-memory table
>>> table = Table.from_dict({
...     "id": Vector(items=["001", "002", "003"], ray_type=Symbol),
...     "name": Vector(items=["alice", "bob", "charlie"], ray_type=Symbol),
...     "age": Vector(items=[29, 34, 41], ray_type=I64),
... })

>>> # Inplace operation - works directly on the table object
>>> result = table.update(age=100).where(Column("id") == "001").execute()
>>> result.values()[2][0].value  # age updated to 100
100

By Reference Operations

By reference operations work on tables that have been saved to the Rayforce environment behind a Symbol using table.save(). These tables are stored in the Rayforce database and accessed via Table.from_name().

>>> # Create and save a table to the Rayforce environment
>>> table = Table.from_dict({
...     "id": Vector(items=["001", "002", "003"], ray_type=Symbol),
...     "name": Vector(items=["alice", "bob", "charlie"], ray_type=Symbol),
...     "age": Vector(items=[29, 34, 41], ray_type=I64),
... })
>>> table.save("my_table")  # Save to Rayforce environment

>>> # By reference operation - works on the saved table reference
>>> result = (
...     Table.from_name("my_table")
...     .update(age=100)
...     .where(Column("id") == "001")
...     .execute()
... )
>>> result.values()[2][0].value  # age updated to 100
100