Colin Maudry
108 lines
2.9 KiB
Python
108 lines
2.9 KiB
Python
import logging
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import os
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from time import sleep
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import polars as pl
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import polars.selectors as cs
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from dotenv import load_dotenv
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from polars.exceptions import ComputeError
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load_dotenv()
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operators = [
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["s<", "<"],
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["s>", ">"],
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["icontains", "contains"],
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]
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logger = logging.getLogger("decp.info")
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logging.basicConfig(
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format="%(asctime)s %(levelname)-8s %(message)s",
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level=logging.INFO,
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datefmt="%Y-%m-%d %H:%M:%S",
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)
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def split_filter_part(filter_part):
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print("filter part", filter_part)
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for operator_group in operators:
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if operator_group[0] in filter_part:
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name_part, value_part = filter_part.split(operator_group[0], 1)
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name_part = name_part.strip()
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value = value_part.strip()
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name = name_part[name_part.find("{") + 1 : name_part.rfind("}")]
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return name, operator_group[1], value
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return [None] * 3
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def add_annuaire_link(df: pl.LazyFrame):
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df = df.with_columns(
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pl.when(pl.col("titulaire_typeIdentifiant") == "SIRET")
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.then(
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pl.col("titulaire_id")
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+ ' <a href="https://annuaire-entreprises.data.gouv.fr/etablissement/'
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+ pl.col("titulaire_id")
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+ '">📑</a>'
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)
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.otherwise(pl.col("titulaire_id"))
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.alias("titulaire_id")
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)
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df = df.with_columns(
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(
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pl.col("acheteur_id")
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+ ' <a href="https://annuaire-entreprises.data.gouv.fr/etablissement/'
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+ pl.col("acheteur_id")
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+ '" target="_blank">📑</a>'
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).alias("acheteur_id")
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)
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return df
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def booleans_to_strings(lf: pl.LazyFrame) -> pl.LazyFrame:
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"""
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Convert all boolean columns to string type.
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"""
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lf = lf.with_columns(
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pl.col(cs.Boolean)
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.cast(pl.String)
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.str.replace("true", "oui")
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.str.replace("false", "non")
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)
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return lf
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def numbers_to_strings(lf: pl.LazyFrame) -> pl.LazyFrame:
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"""
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Convert all numeric columns to string type.
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"""
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lf = lf.with_columns(pl.col(pl.Float64, pl.Int16).cast(pl.String).fill_null(""))
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return lf
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def format_number(number) -> str:
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number = "{:,}".format(number).replace(",", " ")
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return number
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def get_decp_data() -> pl.DataFrame:
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# Chargement du fichier parquet
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# Le fichier est chargé en mémoire, ce qui est plus rapide qu'une base de données pour le moment.
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# On utilise polars pour la rapidité et la facilité de manipulation des données.
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try:
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logger.info(
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f"Lecture du fichier parquet ({os.getenv('DATA_FILE_PARQUET_PATH')})..."
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)
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ddf: pl.DataFrame = pl.read_parquet(os.getenv("DATA_FILE_PARQUET_PATH"))
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except ComputeError:
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# Le fichier est probablement en cours de mise à jour
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logger.info("Échec, nouvelle tentative dans 10s...")
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sleep(10)
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ddf: pl.DataFrame = pl.read_parquet(os.getenv("DATA_FILE_PARQUET_PATH"))
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return ddf
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df = get_decp_data()
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