Metadata-Version: 1.1
Name: acorn
Version: 0.0.7
Summary: Automated computational research notebook.
Home-page: https://github.com/rosenbrockc/acorn
Author: Conrad W Rosenbrock
Author-email: rosenbrockc@gmail.com
License: MIT
Description: |Build Status| |Coverage Status|
        
        Automatic Computational Research Notebook
        =========================================
        
        ``acorn`` uses the mutability of python objects, together with
        decorators, to produce an automatic notebook for computational research.
        Common libraries like ``numpy``, ``scipy``, ``sklearn`` and ``pandas``
        are mutated with decorators that enable logging of calls to important
        methods within those libraries.
        
        This is really helpful for data science where experimenting with fits,
        pipelines and pre-processing transformations can result in hundreds of
        fits and predictions a day. At the end of the day, it is hard to
        remember which set of parameters produced that one fit, which (of
        course) you didn't realize was important at the time.
        
        The library is `well
        documented <https://rosenbrockc.github.io/acorn/>`__.
        
        Basic Flow
        ----------
        
        1. Depending on the logging level, every time a method/function is
           called (whether bound or unbound), we log it into a JSON database.
        2. The JSON database is analyzed using javascript by the browser to
           produce nice sets of objects, separated by project, task, date and
           specific object instances.
        3. A nice UI using ``bootstrap`` populates the HTML dynamically.
        
        Synchronization
        ---------------
        
        We recommend that the JSON database directory be configured on a Dropbox
        folder (later we will support Google Drive, etc.). The HTML notebook can
        be authorized (per session) to have access to Dropbox so that the JSON
        databases can be accessed from anywhere (and any device). Thi HTML and
        javascript is completely standalone (i.e., no server backend required
        outside of the web service requests).
        
        Contribution
        ------------
        
        If this sparks your interest, please message us. The project is still in
        early development, so we can't say more up front.
        
        Special Notes
        =============
        
        The ``matplotlib`` module is used frequently, but not in the typical
        way. Most of the methods and objects are used internally unless a plot
        is being tweaked for some special reason. The ``matplotlib.cfg`` file
        prunes the number of objects that get decorate very aggressively so that
        only the common calls are logged. You can adjust your own local config
        file if you spend a lot of time actually coding ``matplotlib``
        internals.
        
        .. |Build Status| image:: https://travis-ci.org/rosenbrockc/acorn.svg?branch=master
           :target: https://travis-ci.org/rosenbrockc/acorn
        .. |Coverage Status| image:: https://coveralls.io/repos/github/rosenbrockc/acorn/badge.svg?branch=master
           :target: https://coveralls.io/github/rosenbrockc/acorn?branch=master
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
