pandalone 0.5.0
pandalone: process data-trees with relocatable-paths
Requires Python: >=3.6
Keywords: python,utility,library,data,tree,processing,calculation,dependencies,resolution,scientific,engineering,pandas,simulink

###########################################################
pandalone: process data-trees with relocatable-paths
###########################################################
|pypi-ver| |conda-ver| |gh-version| |docs-status| |travis-status| |appveyor-status| |cover-status| 
|dependencies| |downloads-count| |github-issues| |python-ver| |codestyle| |proj-license|

..  doc/_static/pandalone_logo.png
   :width: 300 px
   :align: center

**pandalone** is a collection of utilities for working with *hierarchical-data*
using *relocatable-paths*.

:Release:       0.5.0
:Date:          2020-05-14 23:59
:Documentation: https://pandalone.readthedocs.org/
:Source:        https://github.com/pandalone/pandalone
:PyPI repo:     https://pypi.python.org/pypi/pandalone
:Keywords:      calculation, data, dependencies, engineering, excel, library,
                numpy, pandas, processing, python, resolution, scientific,
                simulink, tree, utility
:Copyright:     2015 European Commission (`JRC-IET
                <https://ec.europa.eu/jrc/en/institutes/iet>`_)
:License:       `EUPL 1.1+ <https://joinup.ec.europa.eu/software/page/eupl>`_

Currently only 2 portions of the envisioned functionality are ready for use:

- mod(`pandalone.xleash`): A mini-language for "throwing the rope" around rectangular areas
  of Excel-sheets.
- mod(`pandalone.mappings`): Hierarchical string-like objects that may be used for
  indexing, facilitating renaming keys and column-names at a later stage.


Our goal is to facilitate the composition of *engineering-models* from
loosely-coupled *components*.
Initially envisioned as an *indirection-framework* around *pandas* coupled
with a *dependency-resolver*, every such model should auto-adapt and process
only values available, and allow *remapping* of the paths accessing them,
to run on renamed/relocated *value-trees* without component-code modifications.

It is an open source library written and tested on *Python-3.6+* , *Windows* and *Linux*.

.. Note::
    The project, as of May-2015, is considered at an alpha-stage,
    without any released version in *pypi* yet.


.. _end-opening:
.. contents:: Table of Contents
  :backlinks: top
.. _begin-intro:

Introduction
============

Overview
--------

At the most fundamental level, an "execution" or a "run" of any data-processing
can be thought like that::

          .--------------.     _____________        .-------------.
         ;  DataTree    ;    |             |      ;   DataTree   ;
        ;--------------; ==> |  <cfunc_1>  | ==> ;--------------;
       ; /some/data   ;      |  <cfunc_2>  |    ; /some/data   ;
      ;  /some/other ;       |     ...     |   ;  /some/other ;
     ;   /foo/bar   ;        |_____________|  ;   /foo/bar   ;
    '--------------'                         '--------------.


- The *data-tree* might come from *json*, *hdf5*, *excel-workbooks*, or
  plain dictionaries and lists.
  Its values are strings and numbers, *numpy-lists*, *pandas* or
  *xray-datasets*, etc.

- The *component-functions* must abide to the following simple signature::

    cfunc_do_something(pandelone, datatree)

  and must not return any value, just read and write into the data-tree.

- Here is a simple component-function:

  .. code-block:: python

    def cfunc_standardize(pandelone, datatree):
        pin, pon = pandelone.paths(),
        df = datatree.get(pin.A)
        df[pon.A.B_std] = df[pin.A.B] / df[pin.A.B].std()

- Notice the use of the *relocatable-paths* marked specifically as input or
  output.

- TODO: continue rough example in tutorial...



Quick-start
-----------

The program runs on **Python-3.5+** and requires **numpy**, **pandas** and 
(optionally) **win32** libraries along with their *native backends*.

.. code-block:: bash

    pip install pandalone                 ## Use `--pre` if version-string has a build-suffix.

... but probably you need the following for `xleash` to work:

.. code-block:: bash

    pip install pandalone[xlrd]

All "extras" are: ``test, doc, excel, pandas, xlrd, dev, all``

In case you need the very latest from `master` branch :

.. code-block:: bash

    pip install git+https://github.com/pandalone/pandalone.git

Or in to install in *develop* mode, with all dependencies needed for development, 
and with pre-commit hook for auto-formatting python-code with *black*,
clone locally this project from the remote repo, and run:

.. code-block:: bash

    pip install -e <pandalone-dr>[dev]
    pre-commit install


Project files and folders
-------------------------
The files and folders of the project are listed below::

    +--pandalone/       ## (package) Python-code
    +--tests/           ## (package) Test-cases
    +--doc/             ## Documentation folder
    +--setup.py         ## (script) The entry point for `setuptools`, installing, testing, etc
    +--requirements/    ## (txt-files) Various pip and conda dependencies.
    +--README.rst
    +--CHANGES.rst
    +--AUTHORS.rst
    +--CONTRIBUTING.rst
    +--LICENSE.txt



.. _usage:

Usage
=====
Currently 2 portions of this library are ready for use: mod(`pandalone.xleash`) and
mod(`pandalone.mappings`)

.. _cmd-line-usage:


GUI usage
---------
.. Attention:: Desktop UI requires Python 3!

For a quick-'n-dirty method to explore the structure of the data-tree and run an experiment,
just run:

.. code-block:: bash

    $ pandalone gui



.. _excel-usage:

Excel usage
-----------
.. Attention:: Excel-integration requires Python-3 and *Windows* or *OS X*!

In *Windows* and *OS X* you may utilize the excellent `xlwings <http://xlwings.org/quickstart/>`_ library
to use Excel files for providing input and output to the experiment.

To create the necessary template-files in your current-directory you should enter:

.. code-block:: console

     $ pandalone excel


You could type instead samp(`pandalone excel {file_path}`) to specify a different destination path.

[TBD]



.. _python-usage:

Python usage
------------
Example python REPL (Read-Eval-Print Loop) example-commands  are given below
that setup and run an *experiment*.

First run command(`python`) or command(`ipython`) and try to import the project to check its version:

code-block::

    >>> import pandalone

    >>> pandalone.__version__           ## Check version once more.
    '0.5.0'

    >>> pandalone.__file__              ## To check where it was installed.         # doctest: +SKIP
    /usr/local/lib/site-package/pandalone-...


.. Tip:
    The use command(`ipython`) is preffered over command(`python`) since it offers various user-friendly
    facilities, such as pressing kbd(`Tab`) for completions, or allowing you to suffix commands with `?` or `??`
    to get help and read their source-code.

    Additionally you can <b>copy any python commands starting with ``>>>`` and ``...``</b> and copy paste them directly
    into the ipython interpreter; it will remove these prefixes.
    But in command(`python`) you have to remove it youself.

If everything works, create the **data-tree** to hold the input-data (strings and numbers).
You assemble data-tree by the use of:

* sequences,
* dictionaries,
* class(`pandas.DataFrame`),
* class(`pandas.Series`), and
* URI-references to other data-trees.


[TBD]



.. _contribute:

Getting Involved
================
This project is hosted in **github**.
To provide feedback about bugs and errors or questions and requests for enhancements,
use `github's Issue-tracker <https://github.com/pandalone/pandalone/issues>`_.



Sources & Dependencies
----------------------
To get involved with development, you need a POSIX environment to fully build it
(*Linux*, *OSX* or *Cygwin* on *Windows*).

First you need to download the latest sources:

.. code-block:: console

    $ git clone https://github.com/pandalone/pandalone.git pandalone.git
    $ cd pandalone.git


.. Admonition:: Virtualenv
    :class: note

    You may choose to work in a |virtualenv|_,
    to install dependency libraries isolated from system's ones, and/or without *admin-rights*
    (this is recommended for *Linux*/*Mac OS*).

    .. Attention::
        If you decide to reuse stystem-installed packages using  option ``--system-site-packages``
        with ``virtualenv <= 1.11.6``
        (to avoid, for instance, having to reinstall *numpy* and *pandas* that require native-libraries)
        you may be bitten by `bug #461 <https://github.com/pypa/virtualenv/issues/461>`_ which
        prevents you from upgrading any of the pre-installed packages with command(`pip`).

.. Admonition:: Liclipse IDE
    :class: note

    Within the sources there are two sample files for the comprehensive
    `LiClipse IDE <http://www.liclipse.com/>`_:

    * file(`eclipse.project`)
    * file(`eclipse.pydevproject`)

    Remove the `eclipse` prefix, (but leave the dot(`.`)) and import it as "existing project" from
    Eclipse's `File` menu.

    Another issue is caused due to the fact that LiClipse contains its own implementation of *Git*, *EGit*,
    which badly interacts with unix *symbolic-links*, such as the file(`docs/docs`), and it detects
    working-directory changes even after a fresh checkout.  To workaround this, Right-click on the above file
    menuselection(`Properties --> Team --> Advanced --> Assume Unchanged`)


Then you can install all project's dependencies in *`development mode* using the file(`setup.py`) script:

.. code-block:: console

    $ python setup.py --help                           ## Get help for this script.
    Common commands: (see '--help-commands' for more)

      setup.py build      will build the package underneath 'build/'
      setup.py install    will install the package

    Global options:
      --verbose (-v)      run verbosely (default)
      --quiet (-q)        run quietly (turns verbosity off)
      --dry-run (-n)      don't actually do anything
    ...

    $ python setup.py develop                           ## Also installs dependencies into project's folder.
    $ python setup.py build                             ## Check that the project indeed builds ok.


You should now run the test-cases to check
that the sources are in good shape:

.. code-block:: console

   $ python setup.py test


.. Note:: The above commands installed the dependencies inside the project folder and
    for the *virtual-environment*.  That is why all build and testing actions have to go through
    samp(`python setup.py {some_cmd}`).

    If you are dealing with installation problems and/or you want to permantly install dependant packages,
    you have to *deactivate* the virtual-environment and start installing them into your *base*
    python environment:

    .. code-block:: console

       $ deactivate
       $ python setup.py develop

    or even try the more *permanent* installation-mode:

    .. code-block:: console

       $ python setup.py install                # May require admin-rights



Design
------
See `architecture live-document
<https://docs.google.com/document/d/1P73jgcAEzR_Vw491DQR0zogdunJOj3qh0h_lvphdaHk>`_.



.. _faq:

FAQ
===

Why another XXX?  What about YYY?
---------------------------------
These are the knowingly related python projects:

- `OpenMDAO <http://openmdao.org/>`_:
  It has influenced pandalone's design.
  It is planned to interoperate by converting to and from it's data-types.
  But it is Python-2 only and its architecture needs attending from
  programmers (no `setup.py`, no official test-cases).

- `PyDSTool <http://www2.gsu.edu/~matrhc/PyDSTool.htm>`_:
  It does not overlap, since it does not cover IO and dependencies of data.
  Also planned to interoperate with it (as soon as we have
  a better grasp of it :-).
  It has some issues with the documentation, but they are working on it.

- `xray <http://xray.readthedocs.org/en/stable/faq.html>`_:
  Pandas for higher dimensions; data-trees should in principle work
  with "xray".

- `Blaze <http://blaze.pydata.org>`_:
  NumPy and Pandas interface to Big Data; data-trees should in principle work
  with "blaze".

- `netCDF4 <http://unidata.github.io/netcdf4-python/>`_:
  Hierarchical file-data-format similar to `hdf5`; a data-tree may derive
  in principle from "netCDF4 ".

- `hdf5 <http://www.h5py.org/>`_:
  Hierarchical file-data-format, `supported natively by pandas
  <http://pandas.pydata.org/pandas-docs/version/0.15.2/io.html#io-hdf5>`_;
  a data-tree may derive in principle from "netCDF4 ".

Which other projects/ideas have you reviewed when building this library?
------------------------------------------------------------------------
- `bubbles ETL <http://bubbles.databrewery.org/documentation.html>`_:
  Processing-pipelines for (mostly) categorical data.

- `Data-protocols <http://dataprotocols.org/>`_:

  - `JTSKit <https://github.com/okfn/jtskit-py>`_, A utility library for
    working with `JSON Table Schema <http://dataprotocols.org/json-table-schema/>`_
    in Python.
  - `Data Packages <http://dataprotocols.org/data-packages/>`_

- `Celery <http://www.celeryproject.org/>`_:
  Execute distributed asynchronous tasks using message passing on a single or
  more worker servers using multiprocessing, Eventlet, or gevent.

- `Fuzzywuzzy <https://github.com/seatgeek/fuzzywuzzy>`_ and
  `Jellyfish <https://github.com/sunlightlabs/jellyfish>`_:
  Fuzzy string matching in python.  Use it for writting code that can read
  coarsely-known column-names.

- `"Other's people's messy data (and how not to hate it)"
  <https://youtu.be/_eQ_8U5kruQ>`_,
  PyCon 2015(Canada) presentation by Mali Akmanalp.


.. _glossary:

Glossary
========
rubric::

    data-tree
        The *container* of data consumed and produced by a :term`model`, which
        may contain also the model.
        Its values are accessed using **path** s.
        It is implemented by class(`pandalone.pandata.Pandel`) as
        a mergeable stack of **JSON-schema** abiding trees of strings and
        numbers, formed with:

            - sequences,
            - dictionaries,
            - mod(`pandas`) instances, and
            - URI-references.

    value-tree
        That part of the **data-tree**  that relates only to the I/O data
        processed.

    model
        A collection of **component** s and accompanying **mappings**.

    component
        Encapsulates a data-transformation function, using **path**
        to refer to its inputs/outputs within the **value-tree**.

    path
        A `/file/like` string functioning as the *id* of data-values
        in the **data-tree**.
        It is composed of **step**, and it follows the syntax of
        the **JSON-pointer**.

    step
    pstep
    path-step
        The parts between between two conjecutive slashes(`/`) within
        a **path**.  The class(`Pstep`) facilitates their manipulation.

    pmod
    pmods
    pmods-hierarchy
    mapping
    mappings
        Specifies a transformation of an "origin" path to
        a "destination" one (also called as "from" and "to" paths).
        The mapping always transforms the *final* path-step, and it can
        either *rename* or *relocate* that step, like that::

            ORIGIN          DESTINATION   RESULT_PATH
            ------          -----------   -----------
            /rename/path    foo       --> /rename/foo        ## renaming
            /relocate/path  foo/bar   --> /relocate/foo/bar  ## relocation
            /root           a/b/c     --> /a/b/c             ## Relocates all /root sub-paths.

        The hierarchy is formed by class(`Pmod`) instances,
        which are build when parsing the **mappings** list, above.

    JSON-schema
        The `JSON schema <http://json-schema.org/>`_ is an `IETF draft
        <http://tools.ietf.org/html/draft-zyp-json-schema-03>`_
        that provides a *contract* for what JSON-data is required for
        a given application and how to interact with it.
        JSON Schema is intended to define validation, documentation,
        hyperlink navigation, and interaction control of JSON data.
        You can learn more about it from this `excellent guide
        <http://spacetelescope.github.io/understanding-json-schema/>`_,
        and experiment with this `on-line validator <http://www.jsonschema.net/>`_.

    JSON-pointer
        JSON Pointer(rfc(`6901`)) defines a string syntax for identifying
        a specific value within a JavaScript Object Notation (JSON) document.
        It aims to serve the same purpose as *XPath* from the XML world,
        but it is much simpler.



.. _begin-replacements:

.. |virtualenv| replace::  *virtualenv* (isolated Python environment)
.. _virtualenv: http://docs.python-guide.org/en/latest/dev/virtualenvs/

.. |pypi| replace:: *PyPi* repo
.. _pypi: https://pypi.python.org/pypi/pandalone

.. |winpython| replace:: *WinPython*
.. _winpython: http://winpython.github.io/

.. |anaconda| replace:: *Anaconda*
.. _anaconda: http://docs.continuum.io/anaconda/

.. |travis-status| image:: https://travis-ci.org/pandalone/pandalone.svg
    :alt: Travis build status (Linux)
    :scale: 100%
    :target: https://travis-ci.org/pandalone/pandalone

.. |appveyor-status| image:: https://ci.appveyor.com/api/projects/status/jayah84y3ae7ddfc?svg=true
    :alt: Apveyor build status (Windows)
    :scale: 100%
    :target: https://ci.appveyor.com/project/ankostis/pandalone

.. |cover-status| image:: https://coveralls.io/repos/pandalone/pandalone/badge.svg
    :target: https://coveralls.io/r/pandalone/pandalone

.. |pypi-ver| image::  https://img.shields.io/pypi/v/pandalone.svg
    :target: https://pypi.python.org/pypi/pandalone/
    :alt: Latest Version in PyPI

.. |gh-version| image::  https://img.shields.io/github/v/release/pandalone/pandalone?label=GitHub%20release&include_prereleases
    :target: https://github.com/pandalone/pandalone/releases
    :alt: Latest release in GitHub

.. |conda-ver| image:: https://anaconda.org/ankostis/pandalone/badges/version.svg
    :target: https://anaconda.org/ankostis/pandalone
    :alt: Latest version in Anaconda-cloud 

.. |python-ver| image:: https://img.shields.io/pypi/pyversions/pandalone.svg
    :target: https://pypi.python.org/pypi/pandalone/
    :alt: Supported Python version
    
.. |downloads-count| image:: https://img.shields.io/pypi/dm/pandalone.svg?period=month
    :target: https://pypi.python.org/pypi/pandalone/
    :alt: Downloads

.. |github-issues| image:: https://img.shields.io/github/issues/pandalone/pandalone.svg
    :target: https://github.com/pandalone/pandalone/issues
    :alt: Issues count

.. |proj-license| image:: https://img.shields.io/badge/license-EUPL%201.1%2B-blue.svg
    :target: https://raw.githubusercontent.com/pandalone/pandalone/master/LICENSE.txt
    :alt: Project License

.. |dependencies| image:: https://img.shields.io/requires/github/pandalone/pandalone.svg
    :target: https://requires.io/github/pandalone/pandalone/requirements/
    :alt: Dependencies up-to-date?

.. |docs-status| image:: https://img.shields.io/readthedocs/pandalone?branch=master
    :target: https://pandalone.readthedocs.io/en/latest/
    :alt: Documentation

.. |codestyle| image:: https://img.shields.io/badge/code%20style-black-black.svg
    :target: https://github.com/ambv/black
    :alt: Code Style