promato_analyse/import_data.py
2025-04-19 00:33:02 +02:00

137 lines
3.8 KiB
Python

import duckdb
import pandas as pd
import os
import datetime
# Create connection to DuckDB
con = duckdb.connect('working_times.db')
# Path to the CSV file
csv_file = 'data/lawi-2025-04-01-2025-04-30-2025-04-17.csv'
# Check if file exists
if not os.path.exists(csv_file):
print(f"Error: File {csv_file} not found")
exit(1)
print(f"Importing data from {csv_file}...")
# Current timestamp for the import
import_timestamp = datetime.datetime.now()
print(f"Import timestamp: {import_timestamp}")
# First read the CSV file with pandas to handle encoding
print("Reading CSV file with proper encoding...")
df = pd.read_csv(csv_file, sep=';', encoding='ISO-8859-1', decimal=',')
# Create temporary table with CSV data, import timestamp, and hash
con.execute("""
CREATE TEMP TABLE temp_working_times AS
WITH base_data AS (
SELECT
*,
'{timestamp}'::TIMESTAMP AS import_timestamp
FROM df
)
SELECT
*,
md5(
"Datum" || '|' ||
"Von" || '|' ||
"Bis" || '|' ||
"Pause" || '|' ||
"Gebucht von" || '|' ||
"Gebucht am" || '|' ||
"Name" || '|' ||
"Kennung" || '|' ||
"Projekt-PSP-ID" || '|' ||
"Projektname" || '|' ||
"PSP-ID" || '|' ||
"PSP-Name" || '|' ||
"ProMaTo-Projekt-Nr." || '|' ||
"ProMaTo-Projekt" || '|' ||
"Kategorie" || '|' ||
"Gruppenname" || '|' ||
"Jira-Epic" || '|' ||
"Aufgaben-Nr." || '|' ||
"Aufgabenname" || '|' ||
"Leistungsart" || '|' ||
"Leistungsart (Bezeichnung)" || '|' ||
"Zeit [h]" || '|' ||
"Kommentar"
) AS row_hash
FROM base_data
""".format(timestamp=import_timestamp))
# Create the working_times table if it doesn't exist
con.execute("""
CREATE TABLE IF NOT EXISTS working_times AS
SELECT * FROM temp_working_times LIMIT 0
""")
# Add column for delete flag if it doesn't exist
con.execute("""
ALTER TABLE working_times
ADD COLUMN IF NOT EXISTS delete BOOLEAN DEFAULT NULL
""")
# Get all unique dates from the new data
con.execute("""
CREATE TEMP TABLE temp_import_dates AS
SELECT DISTINCT "Datum" FROM temp_working_times
""")
# Get all unique dates from existing data
con.execute("""
CREATE TEMP TABLE temp_existing_dates AS
SELECT DISTINCT "Datum" FROM working_times
""")
# Find dates that are new (not in existing data)
con.execute("""
CREATE TEMP TABLE temp_new_dates AS
SELECT t."Datum"
FROM temp_import_dates t
LEFT JOIN temp_existing_dates e ON t."Datum" = e."Datum"
WHERE e."Datum" IS NULL
""")
# Find dates that exist in both tables and might have changes
con.execute("""
CREATE TEMP TABLE temp_changed_dates AS
SELECT DISTINCT t."Datum"
FROM temp_working_times t
JOIN working_times e ON t."Datum" = e."Datum"
WHERE NOT EXISTS (
SELECT 1
FROM working_times
WHERE "Datum" = t."Datum"
AND row_hash = t.row_hash
)
""")
# Insert new data for new and changed dates
con.execute("""
INSERT INTO working_times
SELECT *, NULL as delete FROM temp_working_times
WHERE "Datum" IN (
SELECT "Datum" FROM temp_new_dates
UNION
SELECT "Datum" FROM temp_changed_dates
)
""")
# Verify the data was imported
count = con.execute("SELECT COUNT(*) FROM working_times").fetchone()[0]
print(f"Successfully imported data. Total records in database: {count}")
# Show the table schema
print("\nTable Schema:")
schema = con.execute("DESCRIBE working_times").fetchall()
for col in schema:
print(f"{col[0]}: {col[1]}")
# Close the connection
con.close()
print("\nData import complete. Database saved to working_times.db")