ATS-Doku/database.py

import sqlite3

DB_NAME = "ats_doku.db"

def initialize_db():
    connection = sqlite3.connect(DB_NAME)
    cursor = connection.cursor()

    # --- Tabelle 1: Die Liste für dein Dropdown ---
    cursor.execute('''
        CREATE TABLE IF NOT EXISTS ats (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            name TEXT UNIQUE
        )
    ''')

    # --- Tabelle 2: Das Logbuch (jetzt mit Ort) ---
    cursor.execute('''
        CREATE TABLE IF NOT EXISTS einsaetze (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            location TEXT,
            name TEXT,
            date TEXT,
            time INTEGER
        )
    ''')

    # Optional: Ein paar Test-ats anlegen, falls die Tabelle leer ist
    # (Damit du direkt was im Dropdown siehst)
    cursor.execute("SELECT count(*) FROM ats")
    if cursor.fetchone()[0] == 0:
        ats_liste = [("Tim Grubmüller",), ("Phil Langer",), ("Max Hämmerle",)]
        cursor.executemany("INSERT INTO ats (name) VALUES (?)", ats_liste)

    connection.commit()
    connection.close()


def add_data_to_einsaetze(name, location, date, time):
    connection = sqlite3.connect(DB_NAME)
    cursor = connection.cursor()

    sql_query = "INSERT INTO einsaetze (name, ort, datum, zeit) VALUES (?, ?, ?, ?)"
    data = (name, location, date, time)

    cursor.execute(sql_query, data)
    print("DB geschrieben")

    connection.commit()
    connection.close()

def get_ats_names():
    connection = sqlite3.connect(DB_NAME)
    cursor = connection.cursor()

    # nur die Spalte 'name' aus der Tabelle 'ats'
    cursor.execute("SELECT name FROM ats ORDER BY name ASC")
    names = cursor.fetchall() 
    connection.close()

    return [row[0] for row in names]

def get_einsaetze():
    connection = sqlite3.connect(DB_NAME)
    cursor = connection.cursor()

    #Get Data an Row Names
    connection.row_factory = sqlite3.Row
    cursor.execute("SELECT * FROM einsaetze ORDER BY id DESC")
    data = cursor.fetchall()

    connection.commit()
    connection.close()

    return [dict(row) for row in data]