Metadata-Version: 1.0
Name: ads
Version: 0.11.1
Summary: A Python module for NASA's ADS that doesn't suck.
Home-page: http://www.github.com/andycasey/ads/
Author: Andrew R. Casey
Author-email: andy@astrowizici.st
License: MIT
Description: **A Python Module to Interact with NASA's ADS that Doesn't Suck™**
        ==================================================================
        
        [![Build Status](http://img.shields.io/travis/andycasey/ads.svg?branch-master)](https://travis-ci.org/andycasey/ads) [![PyPi download count image](http://img.shields.io/pypi/dm/ads.svg)](https://pypi.python.org/pypi/ads/)
        
        If you're in research, then you pretty much _need_ NASA's ADS. It's tried, true, and people go crazy on the rare occasions when it goes down.
        
        **Getting Started**
        
        1. You'll need an API key from NASA ADS labs. Sign up for the newest version of ADS search at https://ui.adsabs.harvard.edu, visit account settings and generate a new API token. The official documentation is available at https://github.com/adsabs/adsabs-dev-api
        
        2. When you get your API key, save it to a file called ``~/.ads/dev_key`` or save it as an environment variable named ``ADS_DEV_KEY``
        
        3. From a terminal type ``pip install ads`` (or [if you must](https://stackoverflow.com/questions/3220404/why-use-pip-over-easy-install), use ``easy_install ads``)
        
        Happy Hacking!
        
        
        **Examples**
        
        You can use this module to search for some popular supernova papers:
        ````
        >>> import ads
        
        # Opps, I forgot to follow step 2 in "Getting Started"
        >>> ads.config.token = 'my token'
        
        >>> papers = ads.SearchQuery(q="supernova", sort="citations")
        
        >>> for paper in papers:
        >>>    print(paper.title)
           ...:     
        [u'Maps of Dust Infrared Emission for Use in Estimation of Reddening and Cosmic Microwave Background Radiation Foregrounds']
        [u'Measurements of Omega and Lambda from 42 High-Redshift Supernovae']
        [u'Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant']
        [u'First-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Determination of Cosmological Parameters']
        [u'Abundances of the elements: Meteoritic and solar']
        ````
        
        Or search for papers first-authored by someone:
        ````
        >>> people = list(ads.SearchQuery(first_author="Reiss, A"))
        
        >>> people[0].author
        [u'Reiss, A. W.']
        ````
        
        Or papers where they are anywhere in the author list:
        ````
        >>> papers = list(ads.SearchQuery(author="Reiss, A"))
        
        >>> papers[0].author
        [u'Goodwin, F. E.', u'Henderson, D. M.', u'Reiss, A.', u'Wilkerson, John L.']
        ````
        
        Or search by affiliation:
        ````
        >>> papers = list(ads.SearchQuery(aff="*stromlo*"))
        
        >>> papers[0].aff
        [u'University of California, Berkeley',
         u'University of Kansas',
         u'Royal Greenwich Observatory',
         u"Queen's University",
         u'Mt. Stromlo Observatory',
         u'University of Durham']
        ````
        
        In the above examples we `list()` the results from `ads.SearchQuery` because `ads.SearchQuery` is a generator, allowing us to return any number of articles. 
        To prevent deep pagination of results, a default of `max_pages=3` is set. 
        Feel free to change this, but be aware that each new page fetched will count against your daily API limit. 
        Each object returned is an ````ads.Article```` object, which has a number of *very* handy attributes and functions:
        
        ````
        >>> first_paper = papers[0]
        
        >>> first_paper
        <ads.search.Article at 0x7ff1b913dd10>
        
        # Show some brief details about the paper
        >>> print first_paper
        <Zepf, S. et al. 1994, 1994AAS...185.7506Z>
        
        # You can access attributes of an object in IPython by using the 'tab' button:
        >>> first_paper.
        first_paper.abstract              first_paper.build_citation_tree   first_paper.first_author_norm     first_paper.keys                  first_paper.pubdate
        first_paper.aff                   first_paper.build_reference_tree  first_paper.id                    first_paper.keyword               first_paper.read_count
        first_paper.author                first_paper.citation              first_paper.identifier            first_paper.metrics               first_paper.reference
        first_paper.bibcode               first_paper.citation_count        first_paper.issue                 first_paper.page                  first_paper.title
        first_paper.bibstem               first_paper.database              first_paper.items                 first_paper.property              first_paper.volume
        first_paper.bibtex                first_paper.first_author          first_paper.iteritems             first_paper.pub                   first_paper.year
        ````
        
        Which allows you to easily build complicated queries. Feel free to fork this repository and add your own examples!
        
        **Authors**
        
        Vladimir Sudilovsky & Andy Casey, Geert Barentsen, Dan Foreman-Mackey, Miguel de Val-Borro
        
        **License**
        
        Copyright 2014 the authors 
        
        This is open source software available under the MIT License. For details see the LICENSE file.
        
Platform: UNKNOWN
