{ "info": { "author": "Roberto Haddock Lobo", "author_email": "rhlobo+bigtempo@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Environment :: Console", "Intended Audience :: Developers", "Intended Audience :: Financial and Insurance Industry", "Intended Audience :: Information Technology", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Natural Language :: English", "Operating System :: OS Independent", "Programming Language :: Python :: 2.7", "Topic :: Scientific/Engineering", "Topic :: Scientific/Engineering :: Information Analysis", "Topic :: Software Development :: Libraries :: Python Modules" ], "description": ".. image:: https://pypip.in/v/bigtempo/badge.png\n :target: https://pypi.python.org/pypi/bigtempo\n\n.. image:: https://pypip.in/d/bigtempo/badge.png\n :target: https://pypi.python.org/pypi/bigtempo\n\n.. image:: https://travis-ci.org/rhlobo/bigtempo.png?branch=master\n :target: https://travis-ci.org/rhlobo/bigtempo\n\n.. image:: https://coveralls.io/repos/rhlobo/bigtempo/badge.png\n :target: https://coveralls.io/r/rhlobo/bigtempo\n\n.. image:: http://rhlobo.github.io/bigtempo/bigtempo_small.png\n\n\n:Implementation: Python 2.7\n:Status: Alpha (contract may change)\n:Download: http://pypi.python.org/pypi/bigtempo/\n:Source: http://github.com/rhlobo/bigtempo/\n:Keywords: bigdata, time series, temporal processment, temporal analysis, data processment, data analysis, scalable, distributed, data exploration, python\n\n\nThis is a Python package created to help you build complex hierarchies of processments, each refered as a datasource. \nThe package was originally conceived to handle temporal data and it is typically used as a colleague of pandas_ - dealing with time series and dataframes - but it is flexible and can easily be extended to support other data models.\nIt handles dependency resolution, provides a tagging system that enables querying operations over datasource sets, and much more.\n\nThere are other software packages that focus on lower level aspects of data processing, like pandas_, numpy_, sympy_, theano_. \nThis is not a framework to replace these. Instead, it aims to support many of these tools, helping you to stitch many processments together.\nIt provides a decoupled programming model that was built with scalability support in its heart and it takes care of a lot of the workflow management so that you can focus on the data itself.\n\nBigtempo aims to provide support an wide range of applications - including artificial intelligence systems - working in data pull fashion. \nIts philosophy is to lazyload things as possible: analysis are retrieved from cache if available, processed otherwise.\nA `datasource` serves data through processors that can be used by other `datasources` (or by you directly) and processors are made to be executed in a distributed fashion, if that is desired.\n\n.. It is here to address the plumbing associated with complex chained data evaluation processes, and because each datasource can be used as input for new datasources, it is ideal for data exploration and analysis. \n.. Using it, you are able - for instance - to easily spawn multiple variations of a processment over sets of other datasources. \n.. It is a great tool for distributed processment when you have 'a few quadrillion' [interdependent] processments for interdependent data sets.\n\n+--------------------------------------------------------------------------------------+\n| Keep in mind that the package - although performatic - is in Alpha Stage and, as so, |\n| most of its caching and distributed processing capabilities are still in the owen. |\n+--------------------------------------------------------------------------------------+\n\n\nGetting started\n---------------\n\nYou can `get started reading an ipython notebook`_, and for a better understandment of what can be done, you shall take a peek in the `pandas introduction`_.\n\n\nExample project\n^^^^^^^^^^^^^^^\n\nIf you need more examples, or just feel like checking out how bigtempo can be used in a project, please refer to stockExperiments_.\n\n\nInstallation\n------------\n\nTo install, simply:\n\n.. code-block:: bash\n\n $ pip install bigtempo\n\nOr, if you absolutely must:\n\n.. code-block:: bash\n\n $ easy_install bigtempo\n\n\nDependencies\n^^^^^^^^^^^^\n\n Both the installation methods above should take care of dependencies on its own, automatically.\n\n\nThe pandas_ library is the only direct dependency the package has in order to be executed. You should visit its page to find out what it depends on. For best results, we recommend installing optional packages as well. \n\nIf you want to run the package tests, or enjoy its testing facilities, you'll need:\n\n- mockito_ >= 0.5.1\n\nIn order to run the tests using the command contained in the ``bin`` directory, also install:\n\n- nose >= 1.3.0\n- coverage >= 3.6\n- pep8 >= 1.4.5\n\n\nInstalling from source\n^^^^^^^^^^^^^^^^^^^^^^\n\nTo install bigtempo from source you need:\n\nClone the git repository:\n\n.. code-block:: bash\n\n $ git clone https://github.com/rhlobo/bigtempo.git\n\nGet into the project directory:\n\n.. code-block:: bash\n\n $ cd bigtempo\n\nInstall dependencies (if you are not using virtualenv, it may need super user privileges):\n\n.. code-block:: bash\n\n $ pip install -r requirements.txt\n\nInstall it:\n\n.. code-block:: bash\n\n $ python setup.py install\n\nAlternatively, you can use `pip` if you want all the dependencies pulled in automatically (the optional ``-e`` option is for installing it in\n`development mode `__):\n\n.. code-block:: bash\n\n $ pip install -e .\n\n\nNext versions?\n--------------\n\n.. Although this is an open source project, some of its next big features are going to be released publicly only when they are better defined.\n.. This measure will be valid and applyed til the project achieves a Beta development stage. Feel free to get in contact if you want to know more about it.\n\nDistributed processing\n\n- Build in process pools\n- Integration with celery_\n- Integration with Apache ZooKeeper and ZeroMQ\n\nCaching\n\n- Smart temporal data caching\n\nCompatibility\n\n- Python 2.7+\n\n\nBug tracker\n-----------\n\nIf you have any suggestions, bug reports or annoyances please report them to our issue_tracker_.\n\n\nContribute\n----------\n\n1. On the tracker_, check for open issues or open a new one to start a discussion around an idea or bug.\n2. Fork the repository_ on GitHub to start making your changes.\n3. Write a test which shows that the bug was fixed or that the feature works as expected.\n4. Send a pull request and wait until it gets merged and published. Make sure to add yourself to AUTHORS_.\n\n\n.. _pandas: http://pandas.pydata.org\n.. _`pandas introduction`: http://pandas.pydata.org/pandas-docs/dev/dsintro.html\n.. _numpy: http://www.numpy.org/\n.. _sympy: http://sympy.org/\n.. _theano: http://deeplearning.net/software/theano/\n.. _mockito: https://pypi.python.org/pypi/mockito\n.. _celery: http://github.com/celery/celery\n.. _stockExperiments: https://github.com/rhlobo/stockExperiments\n.. _issue_tracker: http://github.com/rhlobo/bigtempo/issues\n.. _tracker: http://github.com/rhlobo/bigtempo/issues\n.. _repository: http://github.com/rhlobo/bigtempo\n.. _AUTHORS: https://github.com/rhlobo/bigtempo/blob/master/AUTHORS.rst\n.. _`get started reading an ipython notebook`: http://nbviewer.ipython.org/urls/raw.github.com/rhlobo/bigtempo/master/ipy-notebooks/getting_started.ipynb\n\n\n\n--------------------------------------------------------------\n\n.. image:: https://d2weczhvl823v0.cloudfront.net/rhlobo/bigtempo/trend.png\n :target: https://bitdeli.com/free\n\n.. image:: https://cruel-carlota.pagodabox.com/72a329aaa141ddda4059d84df6c4d9ea\n :target: https://githalytics.com/rhlobo/bigtempo", "description_content_type": null, "docs_url": null, "download_url": "UNKNOWN", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/rhlobo/bigtempo", "keywords": null, "license": "The MIT License (MIT)\n\nCopyright (c) 2013 Roberto Haddock Lobo\n\nPermission is hereby granted, free of charge, to any person obtaining a copy of\nthis software and associated documentation files (the \"Software\"), to deal in\nthe Software without restriction, including without limitation the rights to\nuse, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of\nthe Software, and to permit persons to whom the Software is furnished to do so,\nsubject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR\nCOPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER\nIN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN\nCONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.", "maintainer": null, "maintainer_email": null, "name": "bigtempo", "package_url": "https://pypi.org/project/bigtempo/", "platform": "UNKNOWN", "project_url": "https://pypi.org/project/bigtempo/", "project_urls": { "Download": "UNKNOWN", "Homepage": "https://github.com/rhlobo/bigtempo" }, "release_url": "https://pypi.org/project/bigtempo/0.38.9/", "requires_dist": null, "requires_python": null, "summary": "BigTempo is a powerful and scalable programming model, originally crafted for temporal data processment / analysis.", "version": "0.38.9" }, "last_serial": 964512, "releases": { "0.37": [ { "comment_text": "", "digests": { "md5": "8ad63fdea7812b1a90a9ea73cf55fd6b", "sha256": 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