import polars as pl

from pipeline.utils import fuzzy_join_on_postcode

POSTCODE = "E14 2DG"

# Price paid: unique addresses for this postcode
pp = (
    pl.scan_parquet("data_sources/pp-complete.parquet")
    .filter(pl.col("postcode") == POSTCODE)
    .select("paon", "saon", "street", "postcode")
    .unique()
    .sort("saon")
    .with_columns(
        pl.concat_str(
            [pl.col("saon"), pl.col("paon"), pl.col("street")],
            separator=" ",
            ignore_nulls=True,
        ).alias("pp_address"),
    )
)

# EPC: latest inspection per address for this postcode
epc = (
    pl.scan_csv("data_sources/epc/certificates.csv")
    .select("ADDRESS", "POSTCODE", "INSPECTION_DATE")
    .filter(pl.col("POSTCODE").str.strip_chars() == POSTCODE)
    .sort("INSPECTION_DATE", descending=True)
    .unique("ADDRESS")
    .sort("ADDRESS")
)

result = fuzzy_join_on_postcode(
    left=pp,
    right=epc,
    left_address_col="pp_address",
    right_address_col="ADDRESS",
    left_postcode_col="postcode",
    right_postcode_col="POSTCODE",
).collect()

snapshot = result.select("pp_address", "ADDRESS").sort("pp_address")

print('Testing the matching between EPC and PP addresses')
with pl.Config(tbl_rows=-1, tbl_cols=-1, fmt_str_lengths=80):
    print(snapshot)