Showing a computation as a DataFrame
Computation objects have a method to_df() which allows them to be shown as a DataFrame. This provides a quick summary of the states and values of each node, as well as useful timing information:
>>> from loman import *
>>> comp = Computation()
>>> comp.add_node('a', value=1)
>>> comp.add_node('b', lambda a: a + 1)
>>> comp.add_node('c', lambda a: 2 * a)
>>> comp.add_node('d', lambda b, c: b + c)
>>> comp.compute_all()
>>> comp.to_df()
state |
value |
start |
end |
duration |
|
|---|---|---|---|---|---|
a |
States.UPTODATE |
1 |
NaT |
NaT |
nan |
b |
States.UPTODATE |
2 |
2024-11-30 18:49:41.626849 |
2024-11-30 18:49:41.626849 |
0 |
c |
States.UPTODATE |
2 |
2024-11-30 18:49:41.626849 |
2024-11-30 18:49:41.626849 |
0 |
d |
States.UPTODATE |
4 |
2024-11-30 18:49:41.626849 |
2024-11-30 18:49:41.626849 |
0 |
Tip
If your values are not scalars, it can be useful to drop the value column.
>>> comp.to_df().drop(columns='value')