On 2020-06-27 09:34, Daniel. wrote:
When I need to traverse nested dicts, is a common pattern to do
somedict.get('foo', {}).get('bar', {})
But there is no such equivalent for arrays, wouldn't be nice if we can
follow
somedict.get('foo', {}).get('bar', []).get(10) ... ?
What do you think?
I would use this. I do something similar already, albeit as a set of
classes that wrap around Python `dict` and `list` to provide the
null-safe access.
to_data(somedict).foo.bar[10]
Specifically, I wrap `list` in `FlatList`, which will return `Null`
(null-safe version of `None`) instead of raising and IndexError. This
allows math on indexes without concern for corner cases, and makes
window functions easier to write:
| my_list = FlatList(my_list)
| deltas = []
| for i, this_week in enumerate(my_list):
| last_week = my_list[i-7]
| deltas.append(this_week - last_week)
by avoiding exception handling, code is simplified, and procedures
simplify to functions. Instead of code that constructs a list; the code
reads as a list definition:
| deltas = [
| this_week - last_week
| for my_list in [FlatList(my_list)]
| for i, this_week in enumerate(my_list)
| for last_week in [my_list[i-7]]
| ]
> please forgive me: where `for x in [y]` can be read as `x=y` (I am
still hesitant to use `:=`)
There are detriments to using a set of null-safe objects:
1. data structures can be polluted with a combination of null-safe
objects and regular Python structures
2. with null-safe code, there are more nulls and it seems EVERYTHING
must be null-safe, including arithmetic (notice null-safe subtraction above)
3. runs slower; all the null-safe checks dominate my profiler time.
I would be nice if Python had a series of null-safe operators. Until
then, `list.get` would eliminate my extra object creation:
| deltas = [
| this_week - (last_week or 0)
| for i, this_week in enumerate(my_list)
| for last_week in [my_list.get(i-7)]
| ]
Although we see additional null-checks required (as #2 states).
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