taskjuggler-python 0.0.2
Python interfaces to TaskJuggler 3 planner
License: MIT

Unix: |Unix Build Status| Windows: |Windows Build Status|\ Metrics:
|Coverage Status| |Scrutinizer Code Quality|\ Usage: |PyPI Version|

|example screencast|

Rationale
=========

It's **[whatever current year]** and still most of the tasks/project
management tools lack support for any means of automated planning. This
library helps to integrate automated planner that's been available for
over a decade, with a shot of suporting different front-ends, complex
scheduling strategies and potentially different planners.

|example logic plan|

Realize your craziest time management dreams!

-  Current focus is on personal planning and small teams (hence no
   support for multiple resource yet)
-  No configuration is required to start
-  Utility airtable API example provided with advanced planning strategy
   (see below)

Overview
========

``python_taskjuggler`` module provides python interfaces to TaskJuggler
3 planner. It is a set of base classes that provide object abstractions
that TaskJuggler internally uses. The module comes with example
implementation of JSON project description parser.

It is still work in progress and currently supports:

-  generating taskjuggler project file
-  runnig the planner
-  importing task bookings
-  working with single default resource ``"me"``

| The package comes with an example command line utility ``tjp-client``
  that provides automatic planning for
| tasks defined as records in `airtable <https://airtable.com>`__ table.
| Working with google sheets, jira, trello, todoist, smartsheet and
  others could be implemented the same way.

The utility allows to immediately re-schedule to reflect any changes to
the plans that may arise due to new fixed appointments, dependencies,
priority amendments or required efforts re-evaluation.

Command-line utility usage:
---------------------------

::

    $ tjp-client -a airtable -k <airtable_api_key> -b <airtable_database> -t <table_name> -v <view_name>

Preparation
~~~~~~~~~~~

#. Create an `airtable <https://airtable.com>`__ database by copying
   `this example base <https://airtable.com/shrivEunRhLcBm79R>`__ or
   create a new database with table named "Tasks" with the following
   columns (**case sensitive**):

::


    1. id           - the integer (number) field used as task ID. "Auto Number" type recommended.
    2. summary      - single line text: task summary / title
    3. effort       - integer number: task effort duration measured in hours. Default value of 1 recommended
    4. priority     - single select: field with values "CRITICAL", "High", "Low", "info"
    5. preference   - integer number: optional additional number 0-99 for higher granularity of priorities
    6. depends      - single line text: with dependencies listed as id's, like: 2,3,4
    7. appointment  - date field with time: the fixed tasks or appointments that can not be moved
    8. deadline     - date: the desired deadline value. Current strategy will use it to emphasize priority if missed.
    9. booking      - date+time: this is where output will be written to. Sort your table by this column

    Other columns are just ignored.

    You can add nice calculations to the table like time difference between deadline and calculated booking.

#. Create a view called ``Work`` with all the tasks with status "Done"
   filtered out *(it is left as an exercize for the reader to create a
   new column and a filter for it)*
#. Create a calendar view with ``booking`` field
#. Add some tasks and appointments. Beware not to add impossible
   scenarios - those are not supported yet (see console output to check)
#. Get ``API key``, ``database ID``, note your table name and view name
   should be ``Tasks`` and ``Work`` respectively
#. Execute in terminal (change base name and key respectively):

.. code:: sh

    $ tjp-client -a airtable -k keyAnIuVcuhhkeAkc -b appA8ZtLosVV7HGXy -t Tasks -v Work

#. Enjoy the show of ``taskjuggler_python`` moving your tasks around!

Now try changing priorities, adding appointments and re-scheduling the
plan.

Setup
=====

Requirements
------------

-  Python 2.7+
-  TaskJuggler 3.6+

Installation
------------

Install TaskJuggler with gem:

.. code:: sh

    $ gem install taskjuggler

Install taskjuggler\_python with pip:

.. code:: sh

    $ pip install taskjuggler_python

or directly from the source code:

.. code:: sh

    $ git clone https://github.com/grandrew/taskjuggler-python.git
    $ cd taskjuggler-python
    $ python setup.py install

Usage
=====

Basic usage concepts include:

#. A ``Task``, referred to as ``issue`` throughout the code

   #. Task's ``id`` which is used to identify and map the tasks - a
      property of ``JugglerTask`` instance
   #. Task's ``effort`` measured in units set as ``UNIT`` class
      attribute of ``JugglerTaskEffort``
   #. Task's dependencies
   #. Task's ``start`` date (a.k.a. fixed appointment)
   #. Task's ``priority`` measured as interger ``0-1000`` to set
      scheduling preference. No priority is scheduled always first.

#. Bookings - the taskjuggler execution result written as
   ``JugglerTask``'s property object(s)

The minimal invocation will look like:

.. code:: python

    >>> from taskjuggler_python import juggler
    >>> jg = juggler.GenericJuggler()
    >>> t = juggler.JugglerTask()
    >>> t.set_property(juggler.JugglerTaskEffort(1)) # hours by default
    >>> jg.add_task(t)
    >>> jg.run()
    >>> t.walk(juggler.JugglerBooking)[0].decode()
    [datetime.datetime(2017, 10, 12, 13, 0, tzinfo=<UTC>), datetime.datetime(2017, 10, 12, 14, 0, tzinfo=<UTC>)]

JSON tasks loading:
-------------------

.. code:: sh

    $ python
    >>> from taskjuggler_python import jsonjuggler
    >>> my_tasks = """[
      {
        "id": 2,
        "depends": [
          1
        ],
        "allocate": "me",
        "effort": 1.2
      },
      {
        "id": 1,
        "effort": 3,
        "allocate": "me",
        "summary": "test"
      }
    ]"""
    >>> jg = jsonjuggler.JsonJuggler(my_tasks)
    >>> jg.run()
    >>> jg.toJSON()
    [
        {
            "allocate": "me",
            "booking": "2017-10-10T11:00:00+00:00",
            "depends": [
                1
            ],
            "effort": 1.2,
            "id": 2
        },
        {
            "allocate": "me",
            "booking": "2017-10-10T08:00:00+00:00",
            "effort": 3,
            "id": 1,
            "summary": "test"
        }
    ]

Python interface usage example
------------------------------

| As an example, let's create interface to automatically schedule tasks
  that are defined as airtable records
| using `Airtable API
  wrapper <https://github.com/gtalarico/airtable-python-wrapper>`__:

| We are using the fact that airtable's API already emits nicely
  formatted JSON in ``fields`` field.
| We only have to name the table columns with correct field names that
  `jsonjuggler <https://github.com/grandrew/taskjuggler-python/blob/master/taskjuggler_python/jsonjuggler.py>`__
  example wrapper expects

.. code:: python

    from airtable import Airtable
    from taskjuggler_python import juggler, jsonjuggler

    airtable = Airtable("appA8ZtLosVV7HGXy", "Tasks", api_key="keyAnIuVcuhhkeAkc")

    # use DictJuggler example wrapper from jsonjuggler module, directly feed what the API emits in "fields"
    JUGGLER = jsonjuggler.DictJuggler([x["fields"] for x in airtable.get_all(view="Work")])

    # run taskjuggler and calculate bookings
    JUGGLER.run() 

    # walk through all tasks objects
    for t in JUGGLER.walk(juggler.JugglerTask): 
        airtable.update_by_field("id", t.get_id(), 
            {"booking": t.walk(juggler.JugglerBooking)[0].decode()[0].isoformat()})
    # the last line finds first booking in this task, decodes it to datatime list and encodes to isoformat

| After executing this code you should have time assigned to all of your
  tasks, none of them overlapping,
| respecting dependencies, taking into account default time shifts,
  appointments and no overwork allowed.

Advanced booking strategies example
-----------------------------------

| Imagine that you want your older tasks to increase their percieved
  priority so that every task with
| any priority level gets a chance to be scheduled in the foreseeable
  future:

.. code:: python

    # recalculate JSON issue priorities based on deadlines

    for rec in json_issues:
        if "priority" in rec and "deadline" in rec and not rec["priority"] >= 300:

                diff_days = (datetime.datetime.now() - dateutil.parser.parse(rec["deadline"])).days

                if diff_days < 0: diff_days = 0                 # deny lowering priority
                rec["priority"] += diff_days * 3                # after 30 days priority is up by 90
                if rec["priority"] >= 250:                      # limit maximum percieved priority
                    rec["priority"] = 250                       #    > 300 is critical in our strategy

You can find the fully working example
`here <https://github.com/grandrew/taskjuggler-python/blob/master/taskjuggler_python/tjpy_client.py>`__.

Writing your own interface
--------------------------

See code for more examples of how to use the interfaces.

TODO
====

-  **documentation!!**

TaskJuggler support
-------------------

-  general error reporting support (capture stderr and decode id's)
-  emit warnings if e.g. unable to start appointed event due to slipped
   schedule
-  working hours, shifts
-  exporting of tjp file; generating reports, gantt charts, etc.
-  *deadline (date) - is a check that the task is not scheduled after
   this date [not in planner - this is a check and can not be enforced]*
-  task grouping
-  limits dailymax, etc.
-  fixed stat time/end time (ALAP/ASAP strats)

   -  period for appointments

-  non-splittable tasks (``X = effort; limits { maximum Xh }`` ??),
   split punishing
-  extensive timezone support
-  mark tasks as done / decouple depends

General enhancements
--------------------

-  Enable pylint with configuration that allows the check to pass
   (pylint.ini)
-  Loading scheduling results

   -  export back to json

-  Make ID management transparent in the API
-  Extensive testing including safe strings checks
-  TaskJuggler task identifier full path, subtask and validation
-  Bookings and timesheets support
-  Monte-carlo simulations
-  Provide JSONEncoder and JSONDecoder interfaces for jsonjuggler module

   -  https://stackoverflow.com/questions/3768895/how-to-make-a-class-json-serializable

-  Data collection, analytics and prediction (e.g. average task error)

   -  Store bookings and do automatic progress analytics

-  Different backend support (e.g. OptaPlanner/Drools; rename to
   ``python-planner`` package?)

   -  produce multivariare pareto-optimal solutions
   -  export to MiniZinc / FlatZinc for generic CP solvers
   -  GPU-accelerated CP solvers?
   -  QCL (Quantum Computation Language) export

Thoughts
--------

-  Use logging to predict average performance per day
-  Create a universal API middleware with human interface to help with
   life planning and performance measurements

   -  Solve more advanded problems

      -  like "allocate some time during the day to low-priority tasks
         if no critical-priority task exist"
      -  or "adjust (increase) priority of low-priority tasks according
         to their age"

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   :target: https://pypi.python.org/pypi/taskjuggler_python
.. |example screencast| image:: assets/at_example.gif
.. |example logic plan| image:: assets/plan_logic.png


Revision History
================

0.0.0 (YYYY/MM/DD)
------------------

-  TBD