A simple JavaScript Bakaláři API wrapper.
You need Node and NPM (Node Package Manager)
npm install @godlessssss/bakalari.js
// Requiring the library from npm
const Bakalari = require('@godlessssss/bakalari.js')
// Instancing a user with url, username and password
let client = new Bakalari.User('URL', 'USERNAME', 'PASSWORD')
// Logging in to the Bakalari API
client.login()
// Waiting for client to be ready
client.on('ready', async () => {
// Getting marks info from the API
let marks = await client.get(Bakalari.Modules.Marks)
// logging it to the console
console.log(marks)
});await client.get(Module, ...Arguments)await client.get(Bakalari.Modules.Marks)- returns Array of Subjects, that contain Marks Array
await client.get(Bakalari.Modules.Subjects)- returns Array of Subjects
await client.get(Bakalari.Modules.Absence)- returns Absence Array and Absence by Subject Array
await client.get(Bakalari.Modules.Events)- returns Array of Events
await client.get(Bakalari.Modules.Homeworks)- returns Array of Homeworks
await client.get(Bakalari.Modules.UserInfo)- returns User Object
- Permanent Timetable
await client.get(Bakalari.Modules.Timetable)- Actual Timetable
await client.get(Bakalari.Modules.Timetable, 'actual')await client.get(Bakalari.Modules.Substitutions)- returns Array of Substitutions
await client.get(Bakalari.Modules.FinalMarks)- returns Array of school certificates and Final Marks for your term
await client.get(Bakalari.Modules.Whatif, array_of_marks)- Example
await client.get(Bakalari.Modules.Whatif, [
{
MarkText: '1',
Weight: 4,
SubjectId: ' 2',
Id: null,
MaxPoints: 0
}
])MarkText: The mark number you want to add to the prediction - must be string
Weight: The weight of the mark
SubjectId: The ID of the subject you want to predict - use Subjects module to get the ID
Id: The ID of mark - prediction marks are always null
MaxPoints: Maximum number of points to get - this is only used when you use points system
- returns Array of Marks with presumed subject average