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Version: Python

view

The view method creates a new formula table that includes one column for each argument.

When using view, the data being requested is not stored in memory. Rather, a formula is stored that is used to recalculate each cell every time it is accessed.

note

The syntax for the view and select methods is identical, as is the resulting table. view is recommended when:

  1. the formula is fast to compute,
  2. only a small portion of the data is being accessed,
  3. cells are accessed very few times, or
  4. memory usage must be minimized.

When memory usage or computation needs to be reduced, consider using select, update_view, update, or lazy_update. These methods have different memory and computation expenses.

caution

When using view or update_view, non-deterministic methods (e.g., random numbers, current time, or mutable structures) produce unstable results. Downstream operations on these results produce undefined behavior. Non-deterministic methods should use select or update instead.

Syntax​

view(formulas: Union[str, Sequence[str]]) -> Table

Parameters​

ParameterTypeDescription
formulasUnion[str, Sequence[str]]

Formulas to compute columns in the new table:

  • Column from table: "A" (equivalent to "A = A")
  • Renamed column from table: "X = A"
  • Calculated column: "X = A * sqrt(B)"

Returns​

A new formula table that includes one column for each argument.

Examples​

The following example returns only the column B.

from deephaven import new_table
from deephaven.column import string_col, int_col

source = new_table(
    [
        string_col("A", ["The", "At", "Is", "On"]),
        int_col("B", [1, 2, 3, 4]),
        int_col("C", [5, 6, 7, 8]),
    ]
)

result = source.view(formulas=["B"])

In the following example, the new table contains source column A (renamed as X), and column B.

from deephaven import new_table
from deephaven.column import string_col, int_col

source = new_table(
    [
        string_col("A", ["The", "At", "Is", "On"]),
        int_col("B", [1, 2, 3, 4]),
        int_col("C", [5, 6, 7, 8]),
    ]
)

result = source.view(formulas=["X = A", "B"])

The following example creates a table containing column A, column B (renamed as X), and the square root of column C (renamed as Y). While no memory is used to store column Y, the square root function is evaluated every time a cell in column Y is accessed.

from deephaven import new_table
from deephaven.column import string_col, int_col

source = new_table(
    [
        string_col("A", ["The", "At", "Is", "On"]),
        int_col("B", [1, 2, 3, 4]),
        int_col("C", [5, 6, 7, 8]),
    ]
)
result = source.view(formulas=["A", "X = B", "Y = sqrt(C)"])