# Memory Management¶

Warning

This section contains fairly advanced topics. If you find it confusing, that’s because the behavior is confusing.

## Arrays¶

If possible, you should try to be aware of when there are two code references to the same in-memory array. This can help avoid some common bugs. Let’s start with an example. Say you create a ConstantTendencyComponent object like so:

>>> import numpy as np
>>> from sympl import ConstantTendencyComponent, DataArray
>>> array = DataArray(
np.ones((5, 5, 10)),
dims=('lon', 'lat', 'lev'), attrs={'units': 'K/s'})
>>> tendencies = {'air_temperature': array}
>>> tendency_component = ConstantTendencyComponent(tendencies)


This is all fine so far. But it’s important to know that now array is the same array stored inside tendency_component:

>>> out_tendencies, out_diagnostics = tendency_component({})
>>> out_tendencies['air_temperature'] is array  # same place in memory
True


So if you were to modify array, it would change the output given by tendency_component:

>>> array[:] = array * 5.
>>> out_tendencies, out_diagnostics = tendency_component({})
>>> out_tendencies['air_temperature'] is array
True
>>> np.all(out_tendencies['air_temperature'].values == array.values)
True


When in doubt, assume that any array you put into a component when it is initialized should not be modified any more, unless changing the values in the component is intentional.

However, this code would not modify the array in tendency_component:

>>> array = array * 5.
>>> out_tendencies, out_diagnostics = tendency_component({})
>>> out_tendencies['air_temperature'] is array
False
>>> np.all(out_tendencies['air_temperature'].values == array.values)
False


What’s the difference? We took away the [:] on the left hand side of the assignment operator. when [:] is included, python modifies the array on the left hand side, but when it’s not included it tells the python variable name “array” to refer to what is on the right hand side. These are subtly different things - one involves modifying the memory that array already refers to, the other involves telling array to refer to a different place in memory. More precisely, having array = tells python that you want to change what the variable array refers to, and set it to be the thing on the right hand side, while array[:] = tells python to call the __setitem__(key, value) method of array with the contents of the square parentheses as the key and the right hand side as the value.

Interestingly, array = array * 5. has different behavior from array *= 5.. The first one will change what array refers to, as before, while the second one will modify array in-place without changing the reference. Writing array *= 5 is the same as writing array[:] = array * 5'. All similarly written operations (-=, +=, /=, etc.) are in-place operations.