On 18/12/2022 16:44, songbird wrote:
Peter Otten wrote:
...
While I think what you need is a database instead of the collection of
csv files the way to alter namedtuples is to create a new one:
from collections import namedtuple
Row = namedtuple("Row", "foo bar baz")
row = Row(1, 2, 3)
row._replace(bar=42)
Row(foo=1, bar=42, baz=3)
namedtuple is easier to use as that will use the csv and
csvreader and create the records without me having to do any
conversion or direct handling myself. it's all automagically
done. my initial version works, but i'd like it to be a bit
more elegant and handle descriptions it hasn't seen before
in a more robust manner.
An alternative would be dataclasses where basic usage is just as easy:
from dataclasses import make_dataclass
Row = make_dataclass("Row", "foo bar baz".split())
row = Row(1, 2, 3)
row
Row(foo=1, bar=2, baz=3)
row.bar = 42
row
Row(foo=1, bar=42, baz=3)
i do like that i can directly reference each field in a
dataclass and not have to specify a _replace for each change.
is there an easy way to convert from namedtuple to dataclass?
i can see there is a _asdict converter, but don't really like
how that turns out as then i have to do a bunch of:
rec['fieldname'] = blah
rec.fieldname is much easier to understand.
I recommend that you use a dataclass /instead/ of a namedtuple, not
both. However, for a dataclass with the same fields in the same order as
in your namedtuple the conversion is trivial:
Create compatible namedtuple and dataclass types:
>>> NTRow = namedtuple("NTRow", ["alpha", "beta", "gamma"])
>>> DCRow = make_dataclass("DCRow", NTRow._fields)
Build the namedtuple:
>>> ntrow = NTRow(1, "two", 3.0)
>>> ntrow
NTRow(alpha=1, beta='two', gamma=3.0)
Convert to dataclass:
>>> dcrow = DCRow(*ntrow)
>>> dcrow
DCRow(alpha=1, beta='two', gamma=3.0)
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