How can i collect all the Data from a Database by using SqlQuery at once?

I would like to collect all entries in a database and write them into a .csv-file.

To do so, i tried to come up with a while-loop like this:


def create_csv():
     query = QSqlQuery(db=db)
     query.prepare("SELECT * FROM database_name")
     query.exec()
     rec = query.record()
            
     print(query.isSelect())
     nameCol = rec.indexOf("name")

          while query.next():
          print(query.value(nameCol))

This gives me all entries in the column "name" as expected. But since the database has got a lot more columns, i was wondering if there is an easier way to get all the columns (and the headers) at once?

All at once would make the creation of the csv a lot easier.

Solution

It took a while but I think I found something that worked for me:

I started with building the name for the file and generated 2 Lists
executed the query that gives me all values of the table
started a for-loop to get the Headers.
started a while loop that generates me the temporary list-element "row"
added the temporary list-elemt to the Value-List so it becomes a List of Lists
builded a Pandas-dataframe and used the to_csv as desired.

I´m sure there are "smarter" or faster ways to get this done. But at least it works for me.

 def create_csv(self):
    
    today = datetime.today()
    now = today.strftime("%y%m%d_%H%M_%S_")
    
    filename = f"{jetzt}COS.csv"
    
    

    Column_Header=[]
    Article_Value=[]
    
    query = QSqlQuery(db=db)
    query.prepare(r"SELECT * FROM database_name")
    query.exec()
    
    rec = query.record()
    
    for id in range(rec.count()):
        
        Column_Header.append(rec.fieldName(id))
        
    indexes = range(rec.count())
        
    while query.next():
        
        row = [query.value(index) for index in indexes]
        
        
        Article_Value.append(row)
        
    df = pd.DataFrame(Article_Value, columns=Column_Header, index=None) 

    print(df)
    
    df.to_csv(filename,sep=';',index=False)