Features/Spent Times

Summary

Track and store the time (in seconds) spent on each activity, since the activity was started until it was closed.

Owner

Martin Abente Lahaye
Manuel Quiñones.

Current status

Targeted release: 0.104
Last updated: 04/09/14
Percentage of completion: 100%

Detailed Description

This feature is a request from the Australian OLPC deployment, this information is used for reflection and statistics generation. Considering all the different efforts (XoVis, Harvest, etc) for reflecting students work, this feature can benefit all the other deployments.

For this feature, "time" is defined as: the number of seconds for when the activity was active, since it was launched until it was closed. The activity is "active" when occupies the main screen, in other words, the time when the activity was in the background will not be accumulated.

Each journal object will contain an array for spent times, for each time the entry was launch. This created a 1-to-1 relation between spent times and the current launches times. This way, the entry metadata can reflect not only "when" but also "for how long".

Benefit to Sugar

Improve the journal's reflection capabilities.

Scope and implementation

This feature is already implemented and working on Australian au1c images. The implementation requires a small modification to sugar-toolkit and sugar-toolkit-gtk3 see initial implementation.

The change consist in modifying the base Activity class, using the launch time timestamp in conjuction with "set_active" and "save" methods, to calculate and accumulate the seconds for when the activity was "active". The spent time is stored as a string of comma separated integers, each for each time the entry was launched. The new metadata array is called "spent_times".

The scope of this feature is the time accumulation and metadata storage.

How to access this metadata

from sugar3.datastore import datastore

entries, count = datastore.find(self._query())
for entry in entries:
    raw_data = entry.metadata.get('spent-times', None)

    if raw_data is not None:
        spent_times = map(int, raw_data.split(', '))

User Experience

The user experienced is untouched.