Requirements
------------
-* taskwarrior_ v2.1.x or above.
+* taskwarrior_ v2.1.x or above, although newest minor release is recommended.
Installation
------------
>>> tw = TaskWarrior(data_location='~/.task', create=True)
+The ``TaskWarrior`` instance will also use your .taskrc configuration (so that
+it recognizes the same UDAs as your task binary, uses the same configuration,
+etc.). To override the location of the .taskrc, use
+``taskrc_location=~/some/different/path``.
+
Creating Tasks
--------------
Attributes should be set using the correct Python representation, which will be
serialized into the correct format when the task is saved.
+Task properties
+---------------
+
+Tasklib defines several properties upon ``Task`` object, for convenience::
+
+ >>> t.save()
+ >>> t.saved
+ True
+ >>> t.pending
+ True
+ >>> t.active
+ False
+ >>> t.start()
+ >>> t.active
+ True
+ >>> t.done()
+ >>> t.completed
+ True
+ >>> t.pending
+ False
+ >>> t.delete()
+ >>> t.deleted
+ True
+
Operations on Tasks
-------------------
>>> task['tags']
['someday']
+Tasks can also be started and stopped. Use ``start()`` and ``stop()``
+respectively::
+
+ >>> task.start()
+ >>> task['start']
+ datetime.datetime(2015, 7, 16, 18, 48, 28, tzinfo=<DstTzInfo 'Europe/Prague' CEST+2:00:00 DST>)
+ >>> task.stop()
+ >>> task['start']
+ >>> task.done()
+ >>> task['end']
+ datetime.datetime(2015, 7, 16, 18, 49, 2, tzinfo=<DstTzInfo 'Europe/Prague' CEST+2:00:00 DST>)
+
Retrieving Tasks
----------------
>>> task3 == task1
True
+Accessing original values
+-------------------------
+
+To access the saved state of the Task, use dict-like access using the
+``original`` attribute:
+
+ >>> t = Task(tw, description="tidy up")
+ >>> t.save()
+ >>> t['description'] = "tidy up the kitchen and bathroom"
+ >>> t['description']
+ "tidy up the kitchen and bathroom"
+ >>> t.original['description']
+ "tidy up"
+
+When you save the task, original values are refreshed to reflect the
+saved state of the task:
+
+ >>> t.save()
+ >>> t.original['description']
+ "tidy up the kitchen and bathroom"
+
Dealing with dates and time
---------------------------
>>> t['due']
datetime.datetime(2015, 2, 1, 19, 44, 4, 770001, tzinfo=<DstTzInfo 'Europe/Berlin' CET+1:00:00 STD>)
>>> now.astimezone(pytz.utc)
- datetime.datetime(2015, 2, 1, 18, 44, 4, 770001, tzinfo=<DstTzInfo 'Europe/Berlin' CET+1:00:00 STD>)
+ datetime.datetime(2015, 2, 1, 18, 44, 4, 770001, tzinfo=<UTC>)
>>> t['due'] == now.astimezone(pytz.utc)
True
+*Note*: Following behaviour is available only for TaskWarrior >= 2.4.0.
+
+There is a third approach to setting up date time values, which leverages
+the 'task calc' command. You can simply set any datetime attribute to
+any string that contains an acceptable TaskWarrior-formatted time expression::
+
+ $ task calc now + 1d
+ 2015-07-17T21:17:54
+
+This syntax can be leveraged in the python interpreter as follows::
+
+ >>> t['due'] = "now + 1d"
+ >>> t['due']
+ datetime.datetime(2015, 7, 17, 21, 19, 31, tzinfo=<DstTzInfo 'Europe/Berlin' CEST+2:00:00 DST>)
+
+It can be easily seen that the string with TaskWarrior-formatted time expression
+is automatically converted to native datetime in the local time zone.
+
+For the list of acceptable formats and keywords, please consult:
+
+* http://taskwarrior.org/docs/dates.html
+* http://taskwarrior.org/docs/named_dates.html
+
+However, as each such assigment involves call to 'task calc' for conversion,
+it might cause some performance issues when assigning strings to datetime
+attributes repeatedly, in a automated manner.
Working with annotations
------------------------
>>> tw.execute_command(['3', 'done'], config_override={'gc': 'off'}) # Will mark 3 as completed and it will retain its ID
+
+Additionally, you can use ``return_all=True`` flag, which returns
+``(stdout, sterr, return_code)`` triplet, and ``allow_failure=False``, which will
+prevent tasklib from raising an exception if the task binary returned non-zero
+return code::
+
+ >>> tw.execute_command(['invalidcommand'], allow_failure=False, return_all=True)
+ ([u''],
+ [u'Using alternate .taskrc file /home/tbabej/.taskrc',
+ u"[task next rc:/home/tbabej/.taskrc rc.recurrence.confirmation=no rc.json.array=off rc.confirmation=no rc.bulk=0 rc.dependency.confirmation=no description ~ 'invalidcommand']",
+ u'Configuration override rc.recurrence.confirmation:no',
+ u'Configuration override rc.json.array:off',
+ u'Configuration override rc.confirmation:no',
+ u'Configuration override rc.bulk:0',
+ u'Configuration override rc.dependency.confirmation:no',
+ u'No matches.',
+ u'There are local changes. Sync required.'],
+ 1)
+
+
Setting custom configuration values
-----------------------------------
-By default, TaskWarrior does not use any of configuration values stored in
-your .taskrc. To see what configuration values are passed to each executed
+By default, TaskWarrior uses configuration values stored in your .taskrc.
+To see what configuration value overrides are passed to each executed
task command, have a peek into ``config`` attribute of ``TaskWarrior`` object::
>>> tw.config
{'confirmation': 'no', 'data.location': '/home/tbabej/.task'}
-To pass your own configuration, you just need to update this dictionary::
+To pass your own configuration overrides, you just need to update this dictionary::
>>> tw.config.update({'hooks': 'off'}) # tasklib will not trigger hooks
This removes the need for maintaining two copies of the same code base and/or
boilerplate code.
+In ``on-modify`` events, tasklib loads both the original version and the modified
+version of the task to the returned ``Task`` object. To access the original data
+(in read-only manner), use ``original`` dict-like attribute:
+
+ >>> t = Task.from_input()
+ >>> t['description']
+ "Modified description"
+ >>> t.original['description']
+ "Original description"
Working with UDAs
-----------------
-Since TaskWarrior does not read your .taskrc, you need to define any UDAs
-in the TaskWarrior's config dictionary, as described above.
+Since TaskWarrior does read your .taskrc, you need not to define any UDAs
+in the TaskWarrior's config dictionary, as described above. Suppose we have
+a estimate UDA in the .taskrc::
-Let us demonstrate this on the same example as in the TaskWarrior's docs::
-
- >>> tw = TaskWarrior()
- >>> tw.config.update({'uda.estimate.type': 'numeric'})
+ uda.estimate.type = numeric
-Now we can filter and create tasks using the estimate UDA::
+We can simply filter and create tasks using the estimate UDA out of the box::
+ >>> tw = TaskWarrior()
>>> task = Task(tw, description="Long task", estimate=1000)
>>> task.save()
>>> task['id']
$ task 1 export
{"id":1,"description":"Long task","estimate":1000, ...}
-As long as ``TaskWarrior``'s config is updated, we can approach UDAs as built in attributes::
+We can also speficy UDAs as arguments in the TaskFilter::
>>> tw.tasks.filter(estimate=1000)
Long task
Syncing
-------
-Syncing is not directly supported by tasklib, but it can be made to work in a similiar way
-as the UDAs. First we need to update the ``config`` dictionary by the values required for
-sync to work, and then we can run the sync command using the ``execute_command()`` method::
+If you have configurated the needed config variables in your .taskrc, syncing
+is as easy as::
+
+ >>> tw = TaskWarrior()
+ >>> tw.execute_command(['sync'])
+
+If you want to use non-standard server/credentials, you'll need to provide configuration
+overrides to the ``TaskWarrior`` instance. Update the ``config`` dictionary with the
+values you desire to override, and then we can run the sync command using
+the ``execute_command()`` method::
>>> tw = TaskWarrior()
>>> sync_config = {
projects / etc / taskwarrior.git / blobdiff