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Suppression de la variable globale df_filtered, et adaptations

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Colin Maudry
2025-09-27 23:57:51 +02:00
parent 944f207d9b
commit bfa181cefd
2 changed files with 71 additions and 47 deletions
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src/pages/home.py
+23 -47
View File
@@ -9,17 +9,16 @@ from src.utils import (
add_org_links,
add_resource_link,
booleans_to_strings,
filter_table_data,
format_number,
lf,
logger,
split_filter_part,
sort_table_data,
)
load_dotenv()
update_date = os.path.getmtime(os.getenv("DATA_FILE_PARQUET_PATH"))
update_date = datetime.fromtimestamp(update_date).strftime("%d/%m/%Y")
df_filtered = pl.DataFrame()
# Suppression des colonnes inutiles
lf = lf.drop(
@@ -128,6 +127,7 @@ layout = [
disabled=True,
),
dcc.Download(id="download-data"),
dcc.Store(id="filtered_data", storage_type="memory"),
html.P("Données mises à jour le " + str(update_date)),
],
className="table-menu",
@@ -141,6 +141,7 @@ layout = [
@callback(
Output("table", "data"),
Output("table", "columns"),
# Output("filtered_data", "data"),
Output("table", "data_timestamp"),
Output("nb_rows", "children"),
Output("btn-download-data", "disabled"),
@@ -154,55 +155,22 @@ layout = [
)
def update_table(page_current, page_size, filter_query, sort_by, data_timestamp):
print(" + + + + + + + + + + + + + + + + + + ")
global df_filtered
# Application des filtres
lff: pl.LazyFrame = lf # start from the original data
if filter_query:
filtering_expressions = filter_query.split(" && ")
for filter_part in filtering_expressions:
col_name, operator, filter_value = split_filter_part(filter_part)
col_type = str(schema[col_name])
print("filter_value:", filter_value)
print("filter_value_type:", type(filter_value))
print("col_type:", col_type)
if operator in ("<", "<=", ">", ">="):
filter_value = int(filter_value)
if operator == "<":
lff = lff.filter(pl.col(col_name) < filter_value)
elif operator == ">":
lff = lff.filter(pl.col(col_name) > filter_value)
elif operator == ">=":
lff = lff.filter(pl.col(col_name) >= filter_value)
elif operator == "<=":
lff = lff.filter(pl.col(col_name) <= filter_value)
elif col_type.startswith("Int") or col_type.startswith("Float"):
try:
filter_value = int(filter_value)
except ValueError:
logger.error(f"Invalid numeric filter value: {filter_value}")
continue
lff = lff.filter(pl.col(col_name) == filter_value)
elif operator == "contains" and col_type == "String":
lff = lff.filter(pl.col(col_name).str.contains("(?i)" + filter_value))
# elif operator == 'datestartswith':
# lff = lff.filter(pl.col(col_name).str.startswith(filter_value)")
lff = filter_table_data(lff, filter_query)
if len(sort_by) > 0:
lff = lff.sort(
[col["column_id"] for col in sort_by],
descending=[col["direction"] == "desc" for col in sort_by],
nulls_last=True,
)
print(sort_by)
lff = sort_table_data(lff, sort_by)
# Matérialisation des filtres
dff: pl.DataFrame = lff.collect()
df_filtered = dff.clone()
# if filter_query or sort_by:
# filtered_data = dff.to_dicts()
# else:
# filtered_data = {}
height = dff.height
@@ -257,18 +225,26 @@ def update_table(page_current, page_size, filter_query, sort_by, data_timestamp)
@callback(
Output("download-data", "data"),
Input("btn-download-data", "n_clicks"),
State("table", "filter_query"),
State("table", "sort_by"),
State("table", "hidden_columns"),
prevent_initial_call=True,
)
def download_data(n_clicks, hidden_columns: list = None):
df_to_download = df_filtered.clone()
def download_data(n_clicks, filter_query, sort_by, hidden_columns: list = None):
lff: pl.LazyFrame = lf # start from the original data
# Les colonnes masquées sont supprimées
if hidden_columns:
df_to_download = df_to_download.drop(hidden_columns)
lff = lff.drop(hidden_columns)
if filter_query:
lff = filter_table_data(lff, filter_query)
if len(sort_by) > 0:
lff = sort_table_data(lff, sort_by)
def to_bytes(buffer):
df_to_download.write_excel(buffer, worksheet="DECP")
lff.collect(engine="streaming").write_excel(buffer, worksheet="DECP")
date = datetime.now().strftime("%Y-%m-%d_%H:%M:%S")
return dcc.send_bytes(to_bytes, filename=f"decp_{date}.xlsx")
src/utils.py
+48
View File
@@ -150,5 +150,53 @@ def get_departement_region(code_postal):
return code_departement, nom_departement, nom_region
def filter_table_data(lff: pl.LazyFrame, filter_query: str) -> pl.LazyFrame:
schema = lff.collect_schema()
filtering_expressions = filter_query.split(" && ")
for filter_part in filtering_expressions:
col_name, operator, filter_value = split_filter_part(filter_part)
col_type = str(schema[col_name])
print("filter_value:", filter_value)
print("filter_value_type:", type(filter_value))
print("col_type:", col_type)
if operator in ("<", "<=", ">", ">="):
filter_value = int(filter_value)
if operator == "<":
lff = lff.filter(pl.col(col_name) < filter_value)
elif operator == ">":
lff = lff.filter(pl.col(col_name) > filter_value)
elif operator == ">=":
lff = lff.filter(pl.col(col_name) >= filter_value)
elif operator == "<=":
lff = lff.filter(pl.col(col_name) <= filter_value)
elif col_type.startswith("Int") or col_type.startswith("Float"):
try:
filter_value = int(filter_value)
except ValueError:
logger.error(f"Invalid numeric filter value: {filter_value}")
continue
lff = lff.filter(pl.col(col_name) == filter_value)
elif operator == "contains" and col_type == "String":
lff = lff.filter(pl.col(col_name).str.contains("(?i)" + filter_value))
# elif operator == 'datestartswith':
# lff = lff.filter(pl.col(col_name).str.startswith(filter_value)")
return lff
def sort_table_data(lff: pl.LazyFrame, sort_by: list) -> pl.LazyFrame:
lff = lff.sort(
[col["column_id"] for col in sort_by],
descending=[col["direction"] == "desc" for col in sort_by],
nulls_last=True,
)
print(sort_by)
return lff
lf = get_decp_data()
departements = get_departements()