Improve performance of SQL generation by using deepcopy less

[RobinL]

Fixes #2210

This takes 2 seconds before, 0.1 second after this PR

example

import time

from splink.blocking import block_using_rules_sqls
from splink.datasets import splink_datasets
from splink.duckdb.blocking_rule_library import block_on
from splink.duckdb.comparison_library import (
    exact_match,
    levenshtein_at_thresholds,
)
from splink.duckdb.linker import DuckDBLinker

df = splink_datasets.fake_1000

settings = {
    "probability_two_random_records_match": 0.01,
    "link_type": "dedupe_only",
    "blocking_rules_to_generate_predictions": [
        block_on(["first_name"]),
        block_on(["surname"]),
        block_on(["dob"]),
        block_on(["city"]),
        block_on(["email", "city", "first_name"]),
    ],
    "comparisons": [
        levenshtein_at_thresholds("first_name", 2),
        exact_match("surname"),
        exact_match("dob"),
        exact_match("city", term_frequency_adjustments=True),
        exact_match("email"),
    ],
    "retain_intermediate_calculation_columns": True,
    "additional_columns_to_retain": [
        "cluster",
        "surname",
        "email",
        "city",
        "dob",
        "first_name",
    ],
}


linker = DuckDBLinker(df, settings)

start_time = time.time()
block_using_rules_sqls(linker)
end_time = time.time()
print(f"Blocking took {end_time - start_time} seconds")

Deepcopy was resulting in the settings object being copied repeatedly I think - in any case, a shallow copy is sufficient becasue the only thing that is being copied is the column builder

[samnlindsay]