X-Git-Url: https://git.madduck.net/etc/taskwarrior.git/blobdiff_plain/9b4cc3df6a161710e26a08dab9e549292720f407..0ad882377639865283021041f19add5aeb10126a:/docs/index.rst?ds=inline diff --git a/docs/index.rst b/docs/index.rst index 5c8b387..17ea42a 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -10,7 +10,7 @@ Older versions of taskwarrior are untested and may not work. Requirements ------------ -* taskwarrior_ v2.1.x or above. +* taskwarrior_ v2.1.x or above, although newest minor release is recommended. Installation ------------ @@ -36,6 +36,11 @@ The default location is the same as taskwarrior's:: >>> 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 -------------- @@ -84,7 +89,7 @@ Attributes of task objects are accessible through indices, like so:: >>> task['id'] 15 >>> task['due'] - datetime.datetime(2013, 12, 5, 0, 0) + datetime.datetime(2015, 2, 5, 0, 0, tzinfo=) >>> task['tags'] ['work', 'servers'] @@ -98,6 +103,30 @@ The following fields are deserialized into Python objects: 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 ------------------- @@ -142,6 +171,18 @@ Switching back to the open python process:: >>> 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=) + >>> task.stop() + >>> task['start'] + >>> task.done() + >>> task['end'] + datetime.datetime(2015, 7, 16, 18, 49, 2, tzinfo=) + Retrieving Tasks ---------------- @@ -239,6 +280,131 @@ same Python object:: >>> 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 +--------------------------- + +Any timestamp-like attributes of the tasks are converted to timezone-aware +datetime objects. To achieve this, Tasklib leverages ``pytz`` Python module, +which brings the Olsen timezone databaze to Python. + +This shields you from annoying details of Daylight Saving Time shifts +or conversion between different timezones. For example, to list all the +tasks which are due midnight if you're currently in Berlin: + + >>> myzone = pytz.timezone('Europe/Berlin') + >>> midnight = myzone.localize(datetime(2015,2,2,0,0,0)) + >>> tw.tasks.filter(due__before=midnight) + +However, this is still a little bit tedious. That's why TaskWarrior object +is capable of automatic timezone detection, using the ``tzlocal`` Python +module. If your system timezone is set to 'Europe/Berlin', following example +will work the same way as the previous one: + + >>> tw.tasks.filter(due__before=datetime(2015,2,2,0,0,0)) + +You can also use simple dates when filtering: + + >>> tw.tasks.filter(due__before=date(2015,2,2)) + +In such case, a 00:00:00 is used as the time component. + +Of course, you can use datetime naive objects when initializing Task object +or assigning values to datetime atrributes: + + >>> t = Task(tw, description="Buy new shoes", due=date(2015,2,5)) + >>> t['due'] + datetime.datetime(2015, 2, 5, 0, 0, tzinfo=) + >>> t['due'] = date(2015,2,6,15,15,15) + >>> t['due'] + datetime.datetime(2015, 2, 6, 15, 15, 15, tzinfo=) + +However, since timezone-aware and timezone-naive datetimes are not comparable +in Python, this can cause some unexpected behaviour: + + >>> from datetime import datetime + >>> now = datetime.now() + >>> t = Task(tw, description="take out the trash now") + >>> t['due'] = now + >>> now + datetime.datetime(2015, 2, 1, 19, 44, 4, 770001) + >>> t['due'] + datetime.datetime(2015, 2, 1, 19, 44, 4, 770001, tzinfo=) + >>> t['due'] == now + Traceback (most recent call last): + File "", line 1, in + TypeError: can't compare offset-naive and offset-aware datetimes + +If you want to compare datetime aware value with datetime naive value, you need +to localize the naive value first: + + >>> from datetime import datetime + >>> from tasklib.task import local_zone + >>> now = local_zone.localize(datetime.now()) + >>> t['due'] = now + >>> now + datetime.datetime(2015, 2, 1, 19, 44, 4, 770001, tzinfo=) + >>> t['due'] == now + True + +Also, note that it does not matter whether the timezone aware datetime objects +are set in the same timezone: + + >>> import pytz + >>> t['due'] + datetime.datetime(2015, 2, 1, 19, 44, 4, 770001, tzinfo=) + >>> now.astimezone(pytz.utc) + datetime.datetime(2015, 2, 1, 18, 44, 4, 770001, tzinfo=) + >>> 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=) + +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 ------------------------ @@ -253,7 +419,7 @@ Annotations have only defined ``entry`` and ``description`` values:: >>> annotation = annotated_task['annotations'][0] >>> annotation['entry'] - datetime.datetime(2015, 1, 3, 21, 13, 55) + datetime.datetime(2015, 1, 3, 21, 13, 55, tzinfo=) >>> annotation['description'] u'Yeah, I am annotated!' @@ -295,19 +461,39 @@ You can use ``config_override`` keyword argument to specify a dictionary of conf >>> 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 -task command, have a peek into ``config`` attribute of ``TaskWarrior`` object:: +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 ``overrides`` attribute of ``TaskWarrior`` object:: - >>> tw.config + >>> tw.overrides {'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 + >>> tw.overrides.update({'hooks': 'off'}) # tasklib will not trigger hooks Creating hook scripts --------------------- @@ -346,20 +532,28 @@ Consenquently, you can create just one hook file for both ``on-add`` and 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:: + uda.estimate.type = numeric - >>> tw = TaskWarrior() - >>> tw.config.update({'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'] @@ -370,7 +564,7 @@ This is saved as UDA in the TaskWarrior:: $ 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 @@ -378,9 +572,16 @@ As long as ``TaskWarrior``'s config is updated, we can approach UDAs as built in 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 = {