| =================== |
| Output Immutability |
| =================== |
| |
| In Hamilton, functions are only called once! |
| |
| Immutability means, that once a "data structure", e.g. a column is created, and output by a function, the values in the |
| column are not changeable. |
| |
| When Hamilton figures out the execution call path, it walks it and calls functions only once. This means, that if the |
| output of a function is immutable, then there's only one place it was created; it's not modified anywhere else. This |
| provides a great debugging experience if there are ever issues in your dataflow. We believe that by default, one should |
| always strive for immutability of outputs. |
| |
| However, it is up to you, the Hamilton function writer, to ensure that immutability is something that is adhered to. |
| |
| Best practice: |
| -------------- |
| |
| #. To preserve “immutability” of outputs, don’t mutate passed in data structures. e.g. if you get passed in a pandas series, don’t mutate it. |
| |
| #. Test for this in your unit tests if this is something important to you! |
| |
| #. Otherwise YMMV with debugging: |
| |
| #. Clearly document mutating inputs in your function documentation if you do mutate inputs provided. That will make debugging your code that much simpler! |
