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modifiche a standardizer-app-file_extractor #21

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Merged
MARCOP001 merged 1 commit into from
May 29, 2026
Merged

modifiche a standardizer-app-file_extractor #21

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34 changes: 23 additions & 11 deletions app.py
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Original file line number Diff line number Diff line change
Expand Up @@ -772,22 +772,33 @@ def mostra():
elif selected_action == "1A": # Dati Locali (Base Level)
files = input.Dataset()
if files:
all_raw_records = []
# --- FASE 1: EXTRACT ---
all_standardized_dfs = []

# --- FASE 1, 2, 3: EXTRACT & TRANSFORM PER FILE ---
for file_info in files:
file_path = file_info["datapath"]
file_name = file_info["name"]
# Extract the extension to pass to standardizer
file_ext = os.path.splitext(file_name)[1].lower()

try:
# Extract raw records from the specific file
raw_records = extract_from_file(file_path, source=source_upper)
all_raw_records.extend(raw_records)

if raw_records:
# Transform to DF immediately using the specific file_type
df_part = convert2df(raw_records, source=source_upper, file_type=file_ext, validate=True)
all_standardized_dfs.append(df_part)

except Exception as e:
ui.notification_show(f"Errore di estrazione ({file_info['name']}): {e}", type="error", duration=8)
ui.notification_show(f"Errore di elaborazione per ({file_name}): {e}", type="error", duration=8)

# --- FASE 2, 3 e 4: TRANSFORM ---
if all_raw_records:
# --- FASE 4: MERGE E LOAD ---
if all_standardized_dfs:
try:
standardized_df = convert2df(all_raw_records, source=source_upper, validate=True)
# Combine all standard dataframes into one
standardized_df = pd.concat(all_standardized_dfs, ignore_index=True)

# ---> AGGIUNGI QUESTE 3 RIGHE QUI <---
# Converte l'anno in numerico e rimuove le righe senza anno valido
standardized_df["PY"] = pd.to_numeric(standardized_df["PY"], errors="coerce")
standardized_df = standardized_df.dropna(subset=["PY"])
Expand All @@ -799,8 +810,7 @@ def mostra():
ui.notification_show(f"✅ ETL completato con successo! Elaborati {len(standardized_df)} record.", duration=5)

except Exception as e:
ui.notification_show(f"❌ Errore durante la standardizzazione: {e}", type="error", duration=10)

ui.notification_show(f"❌ Errore durante l'aggregazione dei dati: {e}", type="error", duration=10)
# -------- ADVICE BUTTON --------
@render.ui
@reactive.event(input.advice_modal_completeness)
Expand Down Expand Up @@ -962,7 +972,9 @@ def esegui_pipeline_api():

# --- FASE 2, 3 e 4: TRANSFORM E LOAD ---
source_mapped = "OPENALEX" if source == "openalex" else "PUBMED"
standardized_df = convert2df(raw_records, source=source_mapped, validate=True)

# Pass "api" as file_type since these aren't traditional physical files
standardized_df = convert2df(raw_records, source=source_mapped, file_type="api", validate=True)

# Prepara il dato per i calcoli temporali della UI
standardized_df["PY"] = pd.to_numeric(standardized_df["PY"], errors="coerce")
Expand Down
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