Welcome to tasklib's documentation!
***********************************

tasklib is a Python library for interacting with taskwarrior
databases, using a queryset API similar to that of Django's ORM.

Supports Python 3.5 and above, with taskwarrior 2.4.x and above. Older
versions of taskwarrior are untested and may not work.


Requirements
============

* taskwarrior v2.4.x or above, although newest minor release is
  recommended.


Installation
============

Install via pip (recommended):

   pip install tasklib

Or clone from github:

   git clone https://github.com/robgolding/tasklib.git
   cd tasklib
   python setup.py install


Initialization
==============

Optionally initialize the "TaskWarrior" instance with "data_location"
(the database directory). If it doesn't already exist, this will be
created automatically unless "create=False".

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
==============

To create a task, simply create a new "Task" object:

   >>> new_task = Task(tw, description="throw out the trash")

This task is not yet saved to TaskWarrior (same as in Django), not
until you call ".save()" method:

   >>> new_task.save()

You can set any attribute as a keyword argument to the Task object:

   >>> complex_task = Task(tw, description="finally fix the shower", due=datetime(2015,2,14,8,0,0), priority='H')

or by setting the attributes one by one:

   >>> complex_task = Task(tw)
   >>> complex_task['description'] = "finally fix the shower"
   >>> complex_task['due'] = datetime(2015,2,14,8,0,0)
   >>> complex_task['priority'] = 'H'


Modifying Task
==============

To modify a created or retrieved "Task" object, use dictionary-like
access:

   >>> homework = tw.tasks.get(tags=['chores'])
   >>> homework['project'] = 'Home'

The change is not propagated to the TaskWarrior until you run the
"save()" method:

   >>> homework.save()

Attributes, which map to native Python objects are converted. See Task
Attributes section.


Task Attributes
===============

Attributes of task objects are accessible through indices, like so:

   >>> task = tw.tasks.pending().get(tags__contain='work')  # There is only one pending task with 'work' tag
   >>> task['description']
   'Upgrade Ubuntu Server'
   >>> task['id']
   15
   >>> task['due']
   datetime.datetime(2015, 2, 5, 0, 0, tzinfo=<DstTzInfo 'Europe/Berlin' CET+1:00:00 STD>)
   >>> task['tags']
   ['work', 'servers']

The following fields are deserialized into Python objects:

* "due", "wait", "scheduled", "until", "entry": deserialized to a
  "datetime" object

* "annotations": deserialized to a list of "TaskAnnotation" objects

* "tags": deserialized to a list of strings

* "depends": deserialized to a set of "Task" 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
===================

After modifying one or more attributes, simple call "save()" to write
those changes to the database:

   >>> task = tw.tasks.pending().get(tags__contain='work')
   >>> task['due'] = datetime(year=2014, month=1, day=5)
   >>> task.save()

To mark a task as complete, use "done()":

   >>> task = tw.tasks.pending().get(tags__contain='work')
   >>> task.done()
   >>> len(tw.tasks.pending().filter(tags__contain='work'))
   0

To delete a task, use "delete()":

   >>> task = tw.tasks.get(description="task added by mistake")
   >>> task.delete()

To update a task object with values from TaskWarrior database, use
"refresh()". Example:

   >>> task = Task(tw, description="learn to cook")
   >>> task.save()
   >>> task['id']
   5
   >>> task['tags']
   []

Now, suppose the we modify the task using the TaskWarrior interface in
another terminal:

   $ task 5 modify +someday
   Task 5 modified.

Switching back to the open python process:

   >>> task['tags']
   []
   >>> task.refresh()
   >>> 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
================

"tw.tasks" is a "TaskQuerySet" object which emulates the Django
QuerySet API. To get all tasks (including completed ones):

   >>> tw.tasks.all()
   ['First task', 'Completed task', 'Deleted task', ...]


Filtering
=========

Filter tasks using the same familiar syntax:

   >>> tw.tasks.filter(status='pending', tags__contains=['work'])
   ['Upgrade Ubuntu Server']

Filter arguments are passed to the "task" command ("__" is replaced by
a period) so the above example is equivalent to the following command:

   $ task status:pending tags.contain=work

Tasks can also be filtered using raw commands, like so:

   >>> tw.tasks.filter('status:pending +work')
   ['Upgrade Ubuntu Server']

Although this practice is discouraged, as by using raw commands you
may lose some of the portability of your commands over different
TaskWarrior versions.

However, you can mix raw commands with keyword filters, as in the
given example:

   >>> tw.tasks.filter('+BLOCKING', project='Home')  # Gets all blocking tasks in project Home
   ['Fix the toilette']

This can be a neat way how to use syntax not yet supported by tasklib.
The above is excellent example, since virtual tags do not work the
same way as the ordinary ones, that is:

   >>> tw.tasks.filter(tags=['BLOCKING'])
   >>> []

will not work.

There are built-in functions for retrieving pending & completed tasks:

   >>> tw.tasks.pending().filter(tags__contain='work')
   ['Upgrade Ubuntu Server']
   >>> len(tw.tasks.completed())
   227

Use "get()" to return the only task in a "TaskQuerySet", or raise an
exception:

   >>> tw.tasks.get(tags__contain='work')['status']
   'pending'
   >>> tw.tasks.get(status='completed', tags__contains='work')  # Status of only task with the work tag is pending, so this should fail
   Traceback (most recent call last):
     File "<stdin>", line 1, in <module>
     File "tasklib/task.py", line 224, in get
       'Lookup parameters were {0}'.format(kwargs))
   tasklib.task.DoesNotExist: Task matching query does not exist. Lookup parameters were {'status': 'completed', 'tags__contains': ['work']}
   >>> tw.tasks.get(status='pending')
   Traceback (most recent call last):
     File "<stdin>", line 1, in <module>
     File "tasklib/task.py", line 227, in get
       'Lookup parameters were {1}'.format(num, kwargs))
   ValueError: get() returned more than one Task -- it returned 23! Lookup parameters were {'status': 'pending'}

Additionally, since filters return "TaskQuerySets" you can stack
filters on top of each other:

   >>> home_tasks = tw.tasks.filter(project='Wife')
   >>> home_tasks.filter(due__before=datetime(2015,2,14,14,14,14))  # What I have to do until Valentine's day
   ['Prepare surprise birthday party']


Equality of Task objects
========================

Two Tasks are considered equal if they have the same UUIDs:

   >>> task1 = Task(tw, description="Pet the dog")
   >>> task1.save()
   >>> task2 = tw.tasks.get(description="Pet the dog")
   >>> task1 == task2
   True

If you compare the two unsaved tasks, they are considered equal only
if it's the same Python object:

   >>> task1 = Task(tw, description="Pet the cat")
   >>> task2 = Task(tw, description="Pet the cat")
   >>> task1 == task2
   False
   >>> task3 = task1
   >>> 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 "zoneinfo"
Python module, which brings the Olsen timezone database 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 = zoneinfo.ZoneInfo('Europe/Berlin')
>>> midnight = datetime(2015,2,2,0,0,0,tzinfo=myzone)
>>> 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 attributes:

>>> t = Task(tw, description="Buy new shoes", due=date(2015,2,5))
>>> t['due']
datetime.datetime(2015, 2, 5, 0, 0, tzinfo=<DstTzInfo 'Europe/Berlin' CET+1:00:00 STD>)
>>> t['due'] = date(2015,2,6,15,15,15)
>>> t['due']
datetime.datetime(2015, 2, 6, 15, 15, 15, tzinfo=<DstTzInfo 'Europe/Berlin' CET+1:00:00 STD>)

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=<DstTzInfo 'Europe/Berlin' CET+1:00:00 STD>)
>>> t['due'] == now
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  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
>>> now = datetime.now().astimezone()
>>> t['due'] = now
>>> now
datetime.datetime(2015, 2, 1, 19, 44, 4, 770001, tzinfo=<DstTzInfo 'Europe/Berlin' CET+1:00:00 STD>)
>>> t['due'] == now
True

Also, note that it does not matter whether the timezone aware datetime
objects are set in the same timezone:

>>> import zoneinfo
>>> t['due']
datetime.datetime(2015, 2, 1, 19, 44, 4, 770001, tzinfo=<DstTzInfo 'Europe/Berlin' CET+1:00:00 STD>)
>>> now.astimezone(zoneinfo.ZoneInfo('UTC'))
datetime.datetime(2015, 2, 1, 18, 44, 4, 770001, tzinfo=<UTC>)
>>> t['due'] == now.astimezone(zoneinfo.ZoneInfo('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 assignment 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
========================

Annotations of the tasks are represented in tasklib by
"TaskAnnotation" objects. These are much like "Task" objects, albeit
very simplified.

>>> annotated_task = tw.tasks.get(description='Annotated task')
>>> annotated_task['annotations']
[Yeah, I am annotated!]

Annotations have only defined "entry" and "description" values:

   >>> annotation = annotated_task['annotations'][0]
   >>> annotation['entry']
   datetime.datetime(2015, 1, 3, 21, 13, 55, tzinfo=<DstTzInfo 'Europe/Berlin' CET+1:00:00 STD>)
   >>> annotation['description']
   u'Yeah, I am annotated!'

To add a annotation to a Task, use "add_annotation()":

   >>> task = Task(tw, description="new task")
   >>> task.add_annotation("we can annotate any task")
   Traceback (most recent call last):
     File "<stdin>", line 1, in <module>
       File "build/bdist.linux-x86_64/egg/tasklib/task.py", line 355, in add_annotation
   tasklib.task.NotSaved: Task needs to be saved to add annotation

However, Task needs to be saved before you can add a annotation to it:

   >>> task.save()
   >>> task.add_annotation("we can annotate saved tasks")
   >>> task['annotations']
   [we can annotate saved tasks]

To remove the annotation, pass its description to
"remove_annotation()" method:

   >>> task.remove_annotation("we can annotate saved tasks")

Alternatively, you can pass the "TaskAnnotation" object itself:

   >>> task.remove_annotation(task['annotations'][0])


Running custom commands
=======================

To run a custom commands, use "execute_command()" method of
"TaskWarrior" object:

   >>> tw = TaskWarrior()
   >>> tw.execute_command(['log', 'Finish high school.'])
   [u'Logged task.']

You can use "config_override" keyword argument to specify a dictionary
of configuration overrides:

   >>> 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 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.overrides
   {'confirmation': 'no', 'data.location': '/home/tbabej/.task'}

To pass your own configuration overrides, you just need to update this
dictionary:

   >>> tw.overrides.update({'hooks': 'off'})  # tasklib will not trigger hooks


Creating hook scripts
=====================

From version 2.4.0, TaskWarrior has support for hook scripts. Tasklib
provides some very useful helpers to write those. With tasklib,
writing these becomes a breeze:

   #!/usr/bin/python

   from tasklib.task import Task
   task = Task.from_input()
   # ... <custom logic>
   print task.export_data()

For example, plugin which would assign the priority "H" to any task
containing three exclamation marks in the description, would go like
this:

   #!/usr/bin/python

   from tasklib.task import Task
   task = Task.from_input()

   if "!!!" in task['description']:
       task['priority'] = "H"

   print task.export_data()

Tasklib can automatically detect whether it's running in the "on-
modify" event, which provides more input than "on-add" event and reads
the data accordingly.

This means the example above works both for "on-add" and "on-modify"
events!

Consenquently, you can create just one hook file for both "on-add" and
"on-modify" events, and you just need to create a symlink for the
other one. 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 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:

   uda.estimate.type = numeric

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']
   1

This is saved as UDA in the TaskWarrior:

   $ task 1 export
   {"id":1,"description":"Long task","estimate":1000, ...}

We can also speficy UDAs as arguments in the TaskFilter:

   >>> tw.tasks.filter(estimate=1000)
   Long task


Syncing
=======

If you have configured the required configuration 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 = {
   ...     'taskd.certificate': '/home/tbabej/.task/tbabej.cert.pem',
   ...     'taskd.credentials': 'Public/tbabej/34af54de-3cb2-4d3d-82be-33ddb8fd3e66',
   ...     'taskd.server': 'task.server.com:53589',
   ...     'taskd.ca': '/home/tbabej/.task/ca.cert.pem',
   ...     'taskd.trust': 'ignore hostname'}
   >>> tw.config.update(sync_config)
   >>> tw.execute_command(['sync'])
