In this post I ll make a quick introduction by example on how to use Zeitgeist s Python API for good and profit.
If you re interested in using Zeitgeist from C instead, see the
libzeitgeist examples; to use it with C++/Qt, Trever s
a web browser in 4 steps may be of interest.
First things first
In case you re not familiar with
Zeitgeist, it may prove helpful to first read Mikkel s
introduction to Zeitgeist post.
If that s too much to read, just should know that Zeitgeist is an event log. Like the history in your browser, it keeps track of what websites you open at which point in time. It also keeps track of when you close them, and of what browser you used, since it s a system-wide service. Furthermore, it does the same for files, conversations, e-mails, and anything else you want to insert into it.
So Zeitgeist is a database of events, and an event can be pretty much anything. But what does it look like? It s main attributes are the following:
- timestamp when did the event happen (milliseconds since Unix epoch)
- interpretation what sort of event is it (eg. opened, closed)
- manifestation why did it happen (user activity, notification )
- actor which is the primary application involved
- origin where did it come from (eg. website where you clicked the link that opened this page)
Additionally, each event has one or more subjects, which have the following attributes:
- uri
- current_uri updated URI if it changed since the event
- interpretation abstract type (document, image, video )
- manifestation how it is stored (file, remote object, website)
- origin parent folder for files, domain name for websites
- mimetype
- text a title for the event (eg. filename, website title )
- storage identifier for the storage medium of the subject (eg. local, online, pendrive X)
Retrieving recent data
Okay, so let s say you want to know the last song you ve listened to (if you have a Zeitgeist-enabled music player). It s a simple as:
from zeitgeist.client import ZeitgeistClient
from zeitgeist.datamodel import *
zeitgeist = ZeitgeistClient()
def on_events_received(events):
if events:
song = events[0]
print "Last song: %s" % song.subjects[0].uri
else:
print "You haven't listened to any songs."
template = Event.new_for_values(subject_interpretation=Interpretation.AUDIO)
zeitgeist.find_events_for_template(template, on_events_received, num_events=1)
# Start a mainloop - note: the Qt mainloop also works
from gi.repository import GLib
GLib.MainLoop().run()
This may need some explaining. We start by importing the
Zeitgeist client and some associated
data structures (such as
Event and
Interpretation), and create an instance of the client. The
ZeitgeistClient class is a wrapper around
Zeitgeist s D-Bus API which not only makes it much nicer to use, but also makes it easy to install monitors (as we will see later) and provides convenient functionality such as automatic reconnection if the connection to the engine is lost.
To query for the most recent song, we just need to create a template with the restrictions we want to impose and submit it to Zeitgeist using the
find_events_for_template call. If you haven t read
Mikkel s post yet, please do so, as it introduces the structure of events and subjects (in short: an event has a timestamp, some other properties, and one or more subjects representing the resources -files, websites, people - involved in the event).
The Python API is inherently asynchronous (if for some reason you need a synchronous API, you may still use the lower level ZeitgeistDBusInterface class), so we need to define a callback function to handle the results we receive from the Zeitgeist engine.
Finally, we need to create a main loop so the asynchronous functions can run.
Now this was a pretty simple example. Let s make it more interesting. One song isn t much, so let s get the 5 most recent songs. Also, now we want both songs and videos.
The first part is pretty easy, we just need to change the
num_events parameter. For the second extension, we have to change the event template. In fact, now we need two different event templates and the
find_events_for_templates function, which takes an arbitrary number of event templates and ORs them. The result is as follows:
from zeitgeist.client import ZeitgeistClient
from zeitgeist.datamodel import *
zeitgeist = ZeitgeistClient()
def on_events_received(events):
for event in events:
print "- %s" % event.subjects[0].uri
tmpl1 = Event.new_for_values(subject_interpretation=Interpretation.AUDIO)
tmpl2 = Event.new_for_values(subject_interpretation=Interpretation.VIDEO)
zeitgeist.find_events_for_templates([tmpl1, tmpl2],
on_events_received, num_events=5)
# Start a mainloop
from gi.repository import GLib
GLib.MainLoop().run()
This will work, but unless you re lucky you re likely to get some duplicate line. Why is this? Well, other than that you may have used the same file twice, don t forget that what you are requesting are actually events. If you ve started playing a given song, you probably also stopped playing it, so that s actually two of them (an
AccessEvent and a
LeaveEvent). Since this isn t what we want, we ll change the query a bit:
zeitgeist.find_events_for_templates(
[tmpl1, tmpl2],
on_events_received,
num_events=5,
result_type=ResultType.MostRecentSubjects,
storage_state=StorageState.Available)
By requesting the most recent
subjects, vs. the most recent
events, we can filter out events with duplicate URI. See the
ResultType documentation for other modes you can use. Note particularly the MostPopularSubjects result type.
I also used the chance to introduce the
storage_state parameter. This one will filter out events for files Zeitgeist knows aren t available (this mostly means online resources won t be shown if you don t have a network connnection; there s also support for handling external storage media, but because of problems with GIO this is currently disabled).
Last but not least, the
find_events_for_* methods also accept a
timerange parameter. It defaults to
TimeRange.until_now(), but you may change it to
TimeRange.always() (if for some reason you re working with events in the future) or to any other time range of your choice. Here it s important to note that Zeitgeist s timestamps use millisecond precision.
For more advanced queries, you can use more complex combinations of events and subject templates. The rule to keep in mind here is that events are OR d and subjects are ANDed.
Additionally, some field (actor, origin, mimetype, uri and current_uri) may be prefixed with an exclamation mark ( ! ) for NOT, or you may append an asterisc ( * ) to them for prefix search. You can even combine the two operators together. Here s an example of a template you could build:
subj1 = Subject.new_for_values(interpretation=Interpretation.SOURCE_CODE,
uri="file:///home/rainct/Development/*")
subj2 = Subject.new_for_values(uri="!file:///home/rainct/Development/zeitgeist/*")
tmpl1 = Event.new_for_values(interpretation=Interpretation.MODIFY_EVENT,
subjects=[subj1, subj2])
templates = [tmpl1]
In my case, this template would fetch a list of the source code files I modified most recently but excluding those related to the Zeitgeist project.
Working with big sets of data
In case you re trying to do something crazy, you may end up with a Zeitgeist query complaining that it exceeded the memory limit. You re not supposed to do that. Instead, we provide some methods for working with large collections of events.
from zeitgeist.client import ZeitgeistClient
from zeitgeist.datamodel import *
zeitgeist = ZeitgeistClient()
def on_events_received(events):
for event in events:
print '- %s' % event.subjects[0].uri
def on_ids_received(event_ids):
print 'A total of %d source code files were found.' % len(event_ids)
print 'Fetching the first 100...'
zeitgeist.get_events(event_ids[:100], on_events_received)
tmpl = Event.new_for_values(subject_interpretation=Interpretation.SOURCE_CODE)
zeitgeist.find_event_ids_for_templates(
[tmpl],
on_ids_received,
num_events=10000, # you can use 0 for "all events", but do you really need to?
timerange=TimeRange.from_seconds_ago(3600*24*30*3),
result_type=ResultType.MostPopularSubjects)
# Start a mainloop
from gi.repository import GLib
GLib.MainLoop().run()
And there you have the source code files you worked with during the last 3 months, ordered from most to least popular (
popularity is measured counting the number of events; for more precision, maybe you could limit the results to events with interpretation AccessEvent).
Why do we provide this mechanism instead of querying with a simple offset? Well, this avoids problems when the log changes (events are inserted or deleted). Have you ever been exploring the latest posts in some website, and as you change to the next page some of the results from the previous page show up again (because new posts have been added in the meantime)? With Zeitgeist this won t happen.
Receiving information in real time
At this point you re an expert at requesting all sorts of data from Zeitgeist, but now you want to show a list of the last kitten images you ve viewed, updated in real time. Don t worry, Zeitgeist can provide for this:
from zeitgeist.client import ZeitgeistClient
from zeitgeist.datamodel import *
zeitgeist = ZeitgeistClient()
def on_insert(time_range, events):
# do awesome stuff with the events here
print events
def on_delete(time_range, event_ids):
# a previously inserted event was deleted
print event_ids
templates = [Event.new_for_values(subject_uri='file:///home/user/kittens/*',
subject_interpretation=Interpretation.IMAGE)]
zeitgeist.install_monitor(TimeRange.always(), templates, on_insert, on_delete)
# Start a mainloop
from gi.repository import GLib
GLib.MainLoop().run()
It s important to note that
on_delete won t be called when an image is deleted (that d be a newly inserted event with
interpretation=DELETE_EVENT); rather, it s called when a previously inserted event is deleted (for example, using the forget recent history option in
Activity Log Manager).
In case you re curious: for best performance, this doesn t actually use D-Bus signals. Instead, this little call will setup a D-Bus object behind the scenes and register it with the Zeitgeist engine, so it can notify said object when (and only when) an event of its interest is registered.
To stop receiving notifications for a template, you ll need the save the object returned by the
install_monitor call:
m = zeitgeist.install_monitor(TimeRange.always(), templates, on_insert, on_delete)
zeitgeist.remove_monitor(m)
Pro Tip: You can use the
Zeitgeist Explorer GUI to quickly try out different queries (
note: it s still work in progress, so much funcionality is missing, but it does work somewhat).
Contextual awesomeness: finding related events
By now you re familiar with retrieving events and keeping them up to date. Now it s time for a little secret:
import time
from zeitgeist.client import ZeitgeistClient
from zeitgeist.datamodel import *
zeitgeist = ZeitgeistClient()
def on_related_received(uris):
print 'Related URIs:'
for uri in uris:
print ' - %s' % uri
query_templates = [Event.new_for_values(
subject_interpretation=Interpretation.SOURCE_CODE,
subject_uri='file:///home/rainct/Development/zeitgeist/*',
subject_mimetype="text/x-vala")]
result_templates = [Event.new_for_values(
subject_interpretation=Interpretation.WEBSITE,
subject_manifestation=Manifestation.WEB_DATA_OBJECT)]
now = time.time()*1000
zeitgeist.find_related_uris_for_events(
query_templates,
on_related_received,
time_range=TimeRange(now - 1000*3600*24*30*6, now),
result_event_templates=result_templates,
num_events=10)
# Start a mainloop
from gi.repository import GLib
GLib.MainLoop().run()
This little query example will return up to 10 websites I used at the same time as the Vala files inside my Zeitgeist directory, considering only data from the last 6 months. Nice, huh?
This is an experimental feature, and it doesn t work well when operating on big inputs, so it s usually better to use the
find_related_uris_for_uris variant (which replaces the first
query_templates parameter with a list of URIs).
Advanced searching: the FTS extension
Some people think prefix searches aren t good enough for them, and this is why the Zeitgeist engine ships by default with a FTS (
Full Text Search) extension.
Using the methods provided by this extension you can perform more advanced queries against subjects
current_uri and
text properties (unlike the name may suggest, the FTS extension doesn t index the content of the files, but just the information in the event).
This is exposed as
zeitgeist_index_search in libzeitgeist (the C library), but unfortunately isn t currently available in the Python API. If you still need it, you ll have to fallback to pretty much using the D-Bus interface (you still get reconnection support, though). Here s an example:
from zeitgeist.client import ZeitgeistClient
from zeitgeist.datamodel import *
zeitgeist = ZeitgeistClient()
index = zeitgeist._iface.get_extension('Index', 'index/activity')
query = 'hello' # search query
time_range = TimeRange.always()
event_templates = []
offset = 0
num_events = 10
result_type = 100 # magic number for "relevancy" (ResultType.* also work)
def on_reply(events, num_estimated_matches):
print 'Got %d out of ~%d results.' % (len(events), num_estimated_matches)
events = map(Event, events)
for event in events:
print ' - %s' % event.subjects[0].uri
def on_error(exception):
print 'Error from FTS:', exception
index.Search(query, time_range, event_templates,
offset, num_events, result_type,
reply_handler=on_reply, error_handler=on_error)
# Start a mainloop
from gi.repository import GLib
GLib.MainLoop().run()
The most interesting thing here is the
query parameter. Quoting from the C documentation:
The default boolean operator is AND. Thus the query foo bar will
be interpreted as foo AND bar. To exclude a term from the result
set prepend it with a minus sign - eg foo -bar. Phrase queries
can be done by double quoting the string "foo is a bar". You can
truncate terms by appending a *.
There are a few keys you can prefix to a term or phrase to search
within a specific set of metadata. They are used like key:value.
The keys name and title search strictly within the text field of
the event subjects. The key app searches within the application
name or description that is found in the actor attribute of the
events. Lastly you can use the site key to search within the
domain name of the subject URIs.
You can also control the results with the boolean operators AND
and OR and you may use brackets, ( and ), to control the operator
precedence.
Modifying the log
So far we ve only queried Zeitgeist for information, let s get a bit more active.
You can delete events from Zeitgeist with the following query:
from zeitgeist.client import ZeitgeistClient
zeitgeist = ZeitgeistClient()
def on_deleted(timerange):
print 'Deleted events going from %s to %s' % (timerange[0], timerange[1])
event_ids = [50] # put the IDs of the events you want to delete here
zeitgeist.delete_events(event_ids, on_deleted)
# Start a mainloop
from gi.repository import GLib
GLib.MainLoop().run()
The confirmation callback will receive a timerange going from the first to the last event. If no events were deleted (because they didn t exist), you ll get
(-1, -1).
And now for the interesting part. If your application involves resources (files, websites, contacts, etc.) of any sort, you ll probably want to let Zeitgeist know that you re using them. It s time that you write a data-source!
We start by registering the data-source. Here we go:
import time
from gi.repository import GLib
from zeitgeist.client import ZeitgeistClient
from zeitgeist.datamodel import *
zeitgeist = ZeitgeistClient()
def on_status_changed_callback(enabled):
""" This method will be called whenever someone enables or disables
the data-source. """
if enabled:
print 'Data-source enabled and ready to send events!'
else:
print 'Data-source disabled; don\'t send event, they\'ll be ignored.'
def register():
# Always use the same unique_id. Name and description can change
# freely.
unique_id = 'com.example.your.data.source'
name = 'user visible name (may be translated)'
description = 'user visible description (may be translated)'
# Describe what sort of events will be inserted (optional)
subject_template = Subject()
subject_template.interpretation = Interpretation.PLAIN_TEXT_DOCUMENT
subject_template.manifestation = Manifestation.FILE_DATA_OBJECT
templates = []
for interp in (Interpretation.ACCESS_EVENT, Interpretation.LEAVE_EVENT):
event_template = Event()
event_template.interpretation = interp
event_template.manifestation = Manifestation.USER_ACTIVITY
event_template.append_subject(subject_template)
templates.append(event_template)
zeitgeist.register_data_source(unique_id, name, description, templates,
on_status_changed_callback)
Once that s done (and if it is enabled), we are free to send our events:
def log(title, uri, opened):
subject = Subject.new_for_values(
uri=uri,
interpretation=Interpretation.PLAIN_TEXT_DOCUMENT,
manifestation=Manifestation.FILE_DATA_OBJECT,
origin=GLib.path_get_dirname(uri),
mimetype='text/plain',
text=title)
event = Event.new_for_values(
timestamp=time.time()*1000,
manifestation=Manifestation.USER_ACTIVITY,
actor='application://your_application_name.desktop',
subjects=[subject])
if opened:
event.interpretation = Interpretation.ACCESS_EVENT
else:
event.interpretation = Interpretation.LEAVE_EVENT
def on_id_received(event_ids):
print 'Logged %s (%d) with event id %d.' % (title, opened, event_ids[0])
zeitgeist.insert_events([event], on_id_received)
if __name__ == '__main__':
register()
log('test.txt', 'file:///tmp/test.txt', opened=True)
log('another_file.txt', 'file:///tmp/another_file.txt', opened=True)
log('another_file.txt', 'file:///tmp/another_file.txt', opened=False)
log('test.txt', 'file:///tmp/test.txt', opened=False)
# Start a mainloop
GLib.MainLoop().run()
If you don t know what interpretation and manifestation your subject should have, you can use the following utility methods:
from zeitgeist.mimetypes import *
print get_interpretation_for_mimetype('text/plain')
print get_manifestation_for_uri('file:///tmp/test.txt')
Event better, with Zeitgeist 0.9 you can just leave the subject (but not event!) interpretation and manifestation fields empty, and they ll be guessed the same way as if you used those utility methods.
Pro Tip: You can examine all registered data-sources and toggle whether they are enabled or not using the
zeitgeist-data-sources-gtk.py tool.
Conclusion
Wow, I m impressed if you ve got this far. By now you should have quite a good idea on how to use the Zeitgeist API, and I m looking forward to seeing what you do with it in your next awesome project.
If you have any problem with Zeitgeist, feel free to visit us on IRC (#zeitgeist on irc.freenode.net), or join our
mailing list. We ll also be at
GUADEC next week, so if you re there make sure to say hi!
In case you missed them, here are some useful links:
No comments
Siegfried-Angel Gevatter Pujals, 2012.
Permalink
License
Post tags: gnome, zeitgeist
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