gh-156748 : Performance - Use takeref append in _csv

[brittanyrey]

Reduce refcount churn by consuming the reference instead in lieu of calling append and decreffing.

Benchmark	base	patched	delta
50 fields × 200 rows	537.7 µs	508.3 µs	−5.5%
quoted + embedded separators/newlines	468.9 µs	435.8 µs	−7.1%
all-empty fields (50 × 200)	173.6 µs	150.0 µs	−13.6%
2 fields × 200 rows	24.0 µs	23.3 µs	−2.9% (noise 3.3%)
5 × 500-char fields (control)	2517.7 µs	2508.2 µs	−0.4% (noise 21%)

# 50 fields x 200 rows
data = "\n".join(",".join(f"f{j}" for j in range(50)) for _ in range(200))
list(csv.reader(io.StringIO(data)))

• Issue: Performance: Reduce refcount churn in csv.reader #156748

[aisk]

This should be in the Library folder. And refcount churn is not a user-observable detail, I think we should just mention the performance optimization.

[aisk]

I ran the benchmarks on my machine (MacBook Air with M3 chip) and got similar results:

Benchmark	base	patched	delta	PR
50 fields × 200 rows	408.5 µs	389.9 µs	−4.6%	−5.5%
quoted + embedded sep/newlines	725.3 µs	707.6 µs	−2.4%	−7.1%
all-empty fields (50 × 200)	115.8 µs	105.5 µs	−8.9%	−13.6%
2 fields × 200 rows	16.5 µs	16.1 µs	−2.6%	−2.9%
5 × 500-char fields (control)	2288.6 µs	2282.8 µs	−0.3%	−0.4%

[eendebakpt]

This is a duplicate of #150995. I will close in favor of the earlier PR.