Manage projects

Project management

Required user role: SUPER

To work with Databucket, you first have to create a project. Projects are isolated from each other. You can assign multiple users to a project, and a user can be assigned to multiple projects.

Project fields:

• Id - [unique] project id (*)
• Enabled - users can sign in only to enabled projects; signing in to a disabled project is refused with the message "The project is disabled!"
• Name - project name (*)
• Description - explanatory description
• Expiration date - end date of the project's activity; after it users can't sign in to the project
• Users - number of users assigned to the project; edit the row to select the users
• Created at - creation date and time
• Created by - creator name
• Modified at - last modification date and time (*)
• Modified by - last modifier (*)

(*) Displayed in the projects selection list.

Row actions

• Edit - change the project's fields and users
• Import dataset - fill an empty project with a dataset (see below); disabled when the project isn't empty
• Export dataset - download the project's content as a dataset file; disabled for an empty project
• Clear project - remove all the content of the project: buckets with their data and history, views, columns, filters, classes, enums, tags, groups, teams, tasks and icons. The project and its users stay. The dialog shows what the project holds and asks you to type the project's name to confirm. This can't be undone.
• Delete - delete the project; only an empty project can be deleted, so clear it first

Datasets

A dataset is the content of a project in one JSON file: the project's structure (classes, enums, tags, groups, buckets, columns, filters, views, tasks, teams, icons) and the data rows of its buckets. Use datasets to start a project with example data, or to keep a project for a training or a demo in a file and recreate it whenever you need it.

Users are not part of a dataset: after the import, assign users to the project and to its teams.

Importing a dataset

Import dataset fills an empty project. You can choose:

• a built-in dataset - shipped with Databucket. DEMO is an example project with users, scheduler, jobs and configuration buckets in dev, int and prd environments, with tags, enums, filters, views, tasks and 1868 data rows.
• a dataset of the server (marked server) - a file from the folder set in the configuration with databucket.datasets-dir (see Installation). A file named like a built-in dataset replaces it.
• From a file… - a dataset file from your disk, e.g. a project exported before. The dialog shows its name, description and what it holds before you import it. The file can be up to 50 MB.

The data rows are created by you; rows that are reserved in the dataset are reserved for you, and you join the teams of the dataset.

Every dataset is checked before anything is created: its objects must be valid as if they were saved in the settings (names, sizes, safe icons) and they may refer only to objects of the same dataset. When something is wrong, the dialog lists the problems, for example:

The dataset can't be imported:
Icon evil: structure: The icon contains a forbidden element: script
View - all -: refers to a missing columns 999

The import runs in one transaction: when it fails, the project stays empty.

Exporting a project

Export dataset downloads the project as <project name>.json in the same format. Objects deleted before are not exported, and references to them are removed, so the file can always be imported again. You can put the file into the server's datasets folder, keep it on your disk, or edit it, e.g. to change the description.

A dataset file starts with its format version ("format": 1). A file of a newer format than the running Databucket reads is refused with a message saying so.