Jam.py documentation

Dataset

Jam.py framework uses a dataset concept that is very close to datasets of Embarcadero Delphi.

Note

There are other ways to read and modify the database data. You can use the connect method of the task to get a connection from the connection pool and use the connection to get access to the database using Python Database API.

All items with item_type “item” or “table” as well as their details (see Task tree) can access data from associated tables from the project database and write changes to it. They all are objects of the Item class

• Item class (on the client)

• Item class (on the server)

Both of these classes have the same attributes, methods, and events associated with the data handling.

To get a dataset (a set of records) from the project dataset table, use the open method. This method, based on parameters, generates an SQL query to get a dataset.

After dataset is opened, the application can navigate it, change its records or insert new ones and write changes to the item’s database table.

For example, the following functions will set support_rep_id field values to the values of the id field on the client and server respectively:

function set_support_id(customers) {
    customers.open();
    while (!customers.eof()) {
        customers.edit();
        customers.support_rep_id.value = customers.id.value;
        customers.post();
        customers.next();
    }
    customers.apply();
}

def set_support_id(customers):
    customers.open()
    while not customers.eof():
        customers.edit()
        customers.support_rep_id.value = customers.id.value
        customers.post()
        customers.next()
    customers.apply();

These functions get the customers item as a parameter. Then the open method is used to get a list of records from the customers table and each record is modified. In the end the changes are saved in the database table, using the apply method (see Modifying datasets ).

Note

There is a shorter way to navigate a dataset (see Navigating datasets ). For example, in python, the following loops are equivalent:

while not customers.eof():
    print customers.firstname.value
    customers.next()

for c in customers:
    print c.firstname.value

Videos

Datasets and Datasets Part 2 demonstrate almost all methods of working with datasets on specific examples