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Suppression de colonnes + renommage df=>lf #15

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Colin Maudry
2025-06-03 16:44:37 +02:00
parent 0e9597de54
commit 87f336a457
1 changed files with 17 additions and 12 deletions
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src/pages/home.py
+17 -12
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@@ -29,10 +29,15 @@ except ComputeError:
sleep(seconds=10)
df: pl.DataFrame = pl.read_parquet(os.getenv("DATA_FILE_PARQUET_PATH"))
df: pl.LazyFrame = df.lazy()
lf: pl.LazyFrame = df.lazy()
# Suppression des colonnes inutiles
lf = lf.remove(
["titulaire_siren", "acheteur_siren", "typeGroupementOperateurs", "sourceOpenData"]
)
# Ajout des liens vers l'annuaire
df = add_annuaire_link(df)
lf = add_annuaire_link(lf)
title = "Tableau"
register_page(__name__, path="/", title=f"decp.info - {title}", name=title, order=1)
@@ -47,7 +52,7 @@ datatable = dash_table.DataTable(
filter_options={"case": "insensitive", "placeholder_text": "Filtrer..."},
columns=[
{"name": i, "id": i, "presentation": "markdown"}
for i in df.collect_schema().names()
for i in lf.collect_schema().names()
],
selected_columns=[],
selected_rows=[],
@@ -126,7 +131,7 @@ def update_table(page_current, page_size, filter_query, data_timestamp):
print(" + + + + + + + + + + + + + + + + + + ")
print("Filter query:", filter_query)
# 1. Apply Filters
dff = df # start from the original data
lff: pl.LazyFrame = lf # start from the original data
if filter_query:
filtering_expressions = filter_query.split(" && ")
for filter_part in filtering_expressions:
@@ -137,26 +142,26 @@ def update_table(page_current, page_size, filter_query, data_timestamp):
if operator in ("<", "<=", ">", ">="):
filter_value = int(filter_value)
if operator == "<":
dff = dff.filter(pl.col(col_name) < filter_value)
lff = lff.filter(pl.col(col_name) < filter_value)
elif operator == ">":
dff = dff.filter(pl.col(col_name) > filter_value)
lff = lff.filter(pl.col(col_name) > filter_value)
elif operator == ">=":
dff = dff.filter(pl.col(col_name) >= filter_value)
lff = lff.filter(pl.col(col_name) >= filter_value)
elif operator == "<=":
dff = dff.filter(pl.col(col_name) <= filter_value)
lff = lff.filter(pl.col(col_name) <= filter_value)
# these operators match polars series filter operators
elif operator == "contains":
dff = dff.filter(pl.col(col_name).str.contains("(?i)" + filter_value))
lff = lff.filter(pl.col(col_name).str.contains("(?i)" + filter_value))
# elif operator == 'datestartswith':
# dff = dff.filter(pl.col(col_name).str.startswith(filter_value)")
# lff = lff.filter(pl.col(col_name).str.startswith(filter_value)")
# 2. Paginate Data
start_row = page_current * page_size
# end_row = (page_current + 1) * page_size
dff = dff.slice(start_row, page_size).collect()
# print("dff_sliced:", dff.select("titulaire.typeId"))
dff = lff.slice(start_row, page_size).collect()
# print("dff_sliced:", lff.select("titulaire.typeId"))
dff = dff.to_dicts()
return dff, data_timestamp + 1 # update data, update timestamp