{ "info": { "author": "Kostis Anagnostopoulos at European Commission (JRC)", "author_email": "ankostis@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Environment :: Console", "Intended Audience :: Developers", "Intended Audience :: Manufacturing", "Intended Audience :: Science/Research", "License :: OSI Approved :: European Union Public Licence 1.1 (EUPL 1.1)", "Natural Language :: English", "Operating System :: MacOS :: MacOS X", "Operating System :: Microsoft :: Windows", "Operating System :: OS Independent", "Operating System :: POSIX", "Operating System :: Unix", "Programming Language :: Python", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: Implementation :: CPython", "Topic :: Scientific/Engineering", "Topic :: Scientific/Engineering :: Information Analysis", "Topic :: Software Development :: Libraries :: Python Modules", "Topic :: Utilities" ], "description": "###########################################################\npandalone: process data-trees with relocatable-paths\n###########################################################\n|pypi-ver| |conda-ver| |gh-version| |docs-status| |travis-status| |appveyor-status| |cover-status| \n|dependencies| |downloads-count| |github-issues| |python-ver| |codestyle| |proj-license|\n\n.. doc/_static/pandalone_logo.png\n :width: 300 px\n :align: center\n\n**pandalone** is a collection of utilities for working with *hierarchical-data*\nusing *relocatable-paths*.\n\n:Release: 0.5.0\n:Date: 2020-05-14 23:59\n:Documentation: https://pandalone.readthedocs.org/\n:Source: https://github.com/pandalone/pandalone\n:PyPI repo: https://pypi.python.org/pypi/pandalone\n:Keywords: calculation, data, dependencies, engineering, excel, library,\n numpy, pandas, processing, python, resolution, scientific,\n simulink, tree, utility\n:Copyright: 2015 European Commission (`JRC-IET\n `_)\n:License: `EUPL 1.1+ `_\n\nCurrently only 2 portions of the envisioned functionality are ready for use:\n\n- mod(`pandalone.xleash`): A mini-language for \"throwing the rope\" around rectangular areas\n of Excel-sheets.\n- mod(`pandalone.mappings`): Hierarchical string-like objects that may be used for\n indexing, facilitating renaming keys and column-names at a later stage.\n\n\nOur goal is to facilitate the composition of *engineering-models* from\nloosely-coupled *components*.\nInitially envisioned as an *indirection-framework* around *pandas* coupled\nwith a *dependency-resolver*, every such model should auto-adapt and process\nonly values available, and allow *remapping* of the paths accessing them,\nto run on renamed/relocated *value-trees* without component-code modifications.\n\nIt is an open source library written and tested on *Python-3.6+* , *Windows* and *Linux*.\n\n.. Note::\n The project, as of May-2015, is considered at an alpha-stage,\n without any released version in *pypi* yet.\n\n\n.. _end-opening:\n.. contents:: Table of Contents\n :backlinks: top\n.. _begin-intro:\n\nIntroduction\n============\n\nOverview\n--------\n\nAt the most fundamental level, an \"execution\" or a \"run\" of any data-processing\ncan be thought like that::\n\n .--------------. _____________ .-------------.\n ; DataTree ; | | ; DataTree ;\n ;--------------; ==> | | ==> ;--------------;\n ; /some/data ; | | ; /some/data ;\n ; /some/other ; | ... | ; /some/other ;\n ; /foo/bar ; |_____________| ; /foo/bar ;\n '--------------' '--------------.\n\n\n- The *data-tree* might come from *json*, *hdf5*, *excel-workbooks*, or\n plain dictionaries and lists.\n Its values are strings and numbers, *numpy-lists*, *pandas* or\n *xray-datasets*, etc.\n\n- The *component-functions* must abide to the following simple signature::\n\n cfunc_do_something(pandelone, datatree)\n\n and must not return any value, just read and write into the data-tree.\n\n- Here is a simple component-function:\n\n .. code-block:: python\n\n def cfunc_standardize(pandelone, datatree):\n pin, pon = pandelone.paths(),\n df = datatree.get(pin.A)\n df[pon.A.B_std] = df[pin.A.B] / df[pin.A.B].std()\n\n- Notice the use of the *relocatable-paths* marked specifically as input or\n output.\n\n- TODO: continue rough example in tutorial...\n\n\n\nQuick-start\n-----------\n\nThe program runs on **Python-3.5+** and requires **numpy**, **pandas** and \n(optionally) **win32** libraries along with their *native backends*.\n\n.. code-block:: bash\n\n pip install pandalone ## Use `--pre` if version-string has a build-suffix.\n\n... but probably you need the following for `xleash` to work:\n\n.. code-block:: bash\n\n pip install pandalone[xlrd]\n\nAll \"extras\" are: ``test, doc, excel, pandas, xlrd, dev, all``\n\nIn case you need the very latest from `master` branch :\n\n.. code-block:: bash\n\n pip install git+https://github.com/pandalone/pandalone.git\n\nOr in to install in *develop* mode, with all dependencies needed for development, \nand with pre-commit hook for auto-formatting python-code with *black*,\nclone locally this project from the remote repo, and run:\n\n.. code-block:: bash\n\n pip install -e [dev]\n pre-commit install\n\n\nProject files and folders\n-------------------------\nThe files and folders of the project are listed below::\n\n +--pandalone/ ## (package) Python-code\n +--tests/ ## (package) Test-cases\n +--doc/ ## Documentation folder\n +--setup.py ## (script) The entry point for `setuptools`, installing, testing, etc\n +--requirements/ ## (txt-files) Various pip and conda dependencies.\n +--README.rst\n +--CHANGES.rst\n +--AUTHORS.rst\n +--CONTRIBUTING.rst\n +--LICENSE.txt\n\n\n\n.. _usage:\n\nUsage\n=====\nCurrently 2 portions of this library are ready for use: mod(`pandalone.xleash`) and\nmod(`pandalone.mappings`)\n\n.. _cmd-line-usage:\n\n\nGUI usage\n---------\n.. Attention:: Desktop UI requires Python 3!\n\nFor a quick-'n-dirty method to explore the structure of the data-tree and run an experiment,\njust run:\n\n.. code-block:: bash\n\n $ pandalone gui\n\n\n\n.. _excel-usage:\n\nExcel usage\n-----------\n.. Attention:: Excel-integration requires Python-3 and *Windows* or *OS X*!\n\nIn *Windows* and *OS X* you may utilize the excellent `xlwings `_ library\nto use Excel files for providing input and output to the experiment.\n\nTo create the necessary template-files in your current-directory you should enter:\n\n.. code-block:: console\n\n $ pandalone excel\n\n\nYou could type instead samp(`pandalone excel {file_path}`) to specify a different destination path.\n\n[TBD]\n\n\n\n.. _python-usage:\n\nPython usage\n------------\nExample python REPL (Read-Eval-Print Loop) example-commands are given below\nthat setup and run an *experiment*.\n\nFirst run command(`python`) or command(`ipython`) and try to import the project to check its version:\n\ncode-block::\n\n >>> import pandalone\n\n >>> pandalone.__version__ ## Check version once more.\n '0.5.0'\n\n >>> pandalone.__file__ ## To check where it was installed. # doctest: +SKIP\n /usr/local/lib/site-package/pandalone-...\n\n\n.. Tip:\n The use command(`ipython`) is preffered over command(`python`) since it offers various user-friendly\n facilities, such as pressing kbd(`Tab`) for completions, or allowing you to suffix commands with `?` or `??`\n to get help and read their source-code.\n\n Additionally you can copy any python commands starting with ``>>>`` and ``...`` and copy paste them directly\n into the ipython interpreter; it will remove these prefixes.\n But in command(`python`) you have to remove it youself.\n\nIf everything works, create the **data-tree** to hold the input-data (strings and numbers).\nYou assemble data-tree by the use of:\n\n* sequences,\n* dictionaries,\n* class(`pandas.DataFrame`),\n* class(`pandas.Series`), and\n* URI-references to other data-trees.\n\n\n[TBD]\n\n\n\n.. _contribute:\n\nGetting Involved\n================\nThis project is hosted in **github**.\nTo provide feedback about bugs and errors or questions and requests for enhancements,\nuse `github's Issue-tracker `_.\n\n\n\nSources & Dependencies\n----------------------\nTo get involved with development, you need a POSIX environment to fully build it\n(*Linux*, *OSX* or *Cygwin* on *Windows*).\n\nFirst you need to download the latest sources:\n\n.. code-block:: console\n\n $ git clone https://github.com/pandalone/pandalone.git pandalone.git\n $ cd pandalone.git\n\n\n.. Admonition:: Virtualenv\n :class: note\n\n You may choose to work in a |virtualenv|_,\n to install dependency libraries isolated from system's ones, and/or without *admin-rights*\n (this is recommended for *Linux*/*Mac OS*).\n\n .. Attention::\n If you decide to reuse stystem-installed packages using option ``--system-site-packages``\n with ``virtualenv <= 1.11.6``\n (to avoid, for instance, having to reinstall *numpy* and *pandas* that require native-libraries)\n you may be bitten by `bug #461 `_ which\n prevents you from upgrading any of the pre-installed packages with command(`pip`).\n\n.. Admonition:: Liclipse IDE\n :class: note\n\n Within the sources there are two sample files for the comprehensive\n `LiClipse IDE `_:\n\n * file(`eclipse.project`)\n * file(`eclipse.pydevproject`)\n\n Remove the `eclipse` prefix, (but leave the dot(`.`)) and import it as \"existing project\" from\n Eclipse's `File` menu.\n\n Another issue is caused due to the fact that LiClipse contains its own implementation of *Git*, *EGit*,\n which badly interacts with unix *symbolic-links*, such as the file(`docs/docs`), and it detects\n working-directory changes even after a fresh checkout. To workaround this, Right-click on the above file\n menuselection(`Properties --> Team --> Advanced --> Assume Unchanged`)\n\n\nThen you can install all project's dependencies in *`development mode* using the file(`setup.py`) script:\n\n.. code-block:: console\n\n $ python setup.py --help ## Get help for this script.\n Common commands: (see '--help-commands' for more)\n\n setup.py build will build the package underneath 'build/'\n setup.py install will install the package\n\n Global options:\n --verbose (-v) run verbosely (default)\n --quiet (-q) run quietly (turns verbosity off)\n --dry-run (-n) don't actually do anything\n ...\n\n $ python setup.py develop ## Also installs dependencies into project's folder.\n $ python setup.py build ## Check that the project indeed builds ok.\n\n\nYou should now run the test-cases to check\nthat the sources are in good shape:\n\n.. code-block:: console\n\n $ python setup.py test\n\n\n.. Note:: The above commands installed the dependencies inside the project folder and\n for the *virtual-environment*. That is why all build and testing actions have to go through\n samp(`python setup.py {some_cmd}`).\n\n If you are dealing with installation problems and/or you want to permantly install dependant packages,\n you have to *deactivate* the virtual-environment and start installing them into your *base*\n python environment:\n\n .. code-block:: console\n\n $ deactivate\n $ python setup.py develop\n\n or even try the more *permanent* installation-mode:\n\n .. code-block:: console\n\n $ python setup.py install # May require admin-rights\n\n\n\nDesign\n------\nSee `architecture live-document\n`_.\n\n\n\n.. _faq:\n\nFAQ\n===\n\nWhy another XXX? What about YYY?\n---------------------------------\nThese are the knowingly related python projects:\n\n- `OpenMDAO `_:\n It has influenced pandalone's design.\n It is planned to interoperate by converting to and from it's data-types.\n But it is Python-2 only and its architecture needs attending from\n programmers (no `setup.py`, no official test-cases).\n\n- `PyDSTool `_:\n It does not overlap, since it does not cover IO and dependencies of data.\n Also planned to interoperate with it (as soon as we have\n a better grasp of it :-).\n It has some issues with the documentation, but they are working on it.\n\n- `xray `_:\n Pandas for higher dimensions; data-trees should in principle work\n with \"xray\".\n\n- `Blaze `_:\n NumPy and Pandas interface to Big Data; data-trees should in principle work\n with \"blaze\".\n\n- `netCDF4 `_:\n Hierarchical file-data-format similar to `hdf5`; a data-tree may derive\n in principle from \"netCDF4 \".\n\n- `hdf5 `_:\n Hierarchical file-data-format, `supported natively by pandas\n `_;\n a data-tree may derive in principle from \"netCDF4 \".\n\nWhich other projects/ideas have you reviewed when building this library?\n------------------------------------------------------------------------\n- `bubbles ETL `_:\n Processing-pipelines for (mostly) categorical data.\n\n- `Data-protocols `_:\n\n - `JTSKit `_, A utility library for\n working with `JSON Table Schema `_\n in Python.\n - `Data Packages `_\n\n- `Celery `_:\n Execute distributed asynchronous tasks using message passing on a single or\n more worker servers using multiprocessing, Eventlet, or gevent.\n\n- `Fuzzywuzzy `_ and\n `Jellyfish `_:\n Fuzzy string matching in python. Use it for writting code that can read\n coarsely-known column-names.\n\n- `\"Other's people's messy data (and how not to hate it)\"\n `_,\n PyCon 2015(Canada) presentation by Mali Akmanalp.\n\n\n.. _glossary:\n\nGlossary\n========\nrubric::\n\n data-tree\n The *container* of data consumed and produced by a :term`model`, which\n may contain also the model.\n Its values are accessed using **path** s.\n It is implemented by class(`pandalone.pandata.Pandel`) as\n a mergeable stack of **JSON-schema** abiding trees of strings and\n numbers, formed with:\n\n - sequences,\n - dictionaries,\n - mod(`pandas`) instances, and\n - URI-references.\n\n value-tree\n That part of the **data-tree** that relates only to the I/O data\n processed.\n\n model\n A collection of **component** s and accompanying **mappings**.\n\n component\n Encapsulates a data-transformation function, using **path**\n to refer to its inputs/outputs within the **value-tree**.\n\n path\n A `/file/like` string functioning as the *id* of data-values\n in the **data-tree**.\n It is composed of **step**, and it follows the syntax of\n the **JSON-pointer**.\n\n step\n pstep\n path-step\n The parts between between two conjecutive slashes(`/`) within\n a **path**. The class(`Pstep`) facilitates their manipulation.\n\n pmod\n pmods\n pmods-hierarchy\n mapping\n mappings\n Specifies a transformation of an \"origin\" path to\n a \"destination\" one (also called as \"from\" and \"to\" paths).\n The mapping always transforms the *final* path-step, and it can\n either *rename* or *relocate* that step, like that::\n\n ORIGIN DESTINATION RESULT_PATH\n ------ ----------- -----------\n /rename/path foo --> /rename/foo ## renaming\n /relocate/path foo/bar --> /relocate/foo/bar ## relocation\n /root a/b/c --> /a/b/c ## Relocates all /root sub-paths.\n\n The hierarchy is formed by class(`Pmod`) instances,\n which are build when parsing the **mappings** list, above.\n\n JSON-schema\n The `JSON schema `_ is an `IETF draft\n `_\n that provides a *contract* for what JSON-data is required for\n a given application and how to interact with it.\n JSON Schema is intended to define validation, documentation,\n hyperlink navigation, and interaction control of JSON data.\n You can learn more about it from this `excellent guide\n `_,\n and experiment with this `on-line validator `_.\n\n JSON-pointer\n JSON Pointer(rfc(`6901`)) defines a string syntax for identifying\n a specific value within a JavaScript Object Notation (JSON) document.\n It aims to serve the same purpose as *XPath* from the XML world,\n but it is much simpler.\n\n\n\n.. _begin-replacements:\n\n.. |virtualenv| replace:: *virtualenv* (isolated Python environment)\n.. _virtualenv: http://docs.python-guide.org/en/latest/dev/virtualenvs/\n\n.. |pypi| replace:: *PyPi* repo\n.. _pypi: https://pypi.python.org/pypi/pandalone\n\n.. |winpython| replace:: *WinPython*\n.. _winpython: http://winpython.github.io/\n\n.. |anaconda| replace:: *Anaconda*\n.. _anaconda: http://docs.continuum.io/anaconda/\n\n.. |travis-status| image:: https://travis-ci.org/pandalone/pandalone.svg\n :alt: Travis build status (Linux)\n :scale: 100%\n :target: https://travis-ci.org/pandalone/pandalone\n\n.. 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