crossref module

class habanero.Crossref(base_url='https://api.crossref.org', api_key=None, mailto=None)[source]

Crossref: Class for Crossref search API methods



Includes methods matching Crossref API routes

Also:

What am I actually searching when using the Crossref search API?

You are using the Crossref search API described at https://github.com/CrossRef/rest-api-doc/blob/master/rest_api.md. When you search with query terms, on Crossref servers they are not searching full text, or even abstracts of articles, but only what is available in the data that is returned to you. That is, they search article titles, authors, etc. For some discussion on this, see https://github.com/CrossRef/rest-api-doc/issues/101

The Polite Pool

As of September 18th 2017 any API queries that use HTTPS and have appropriate contact information will be directed to a special pool of API machines that are reserved for polite users. If you connect to the Crossreef API using HTTPS and provide contact information, then they will send you to a separate pool of machines, with better control the performance of these machines because they can block abusive users.

We have been using https in habanero for a while now, so that’s good to go. To get into the Polite Pool, also set your mailto email address when you instantiate the Crossref object. See examples below.

Doing setup:

from habanero import Crossref
cr = Crossref()
# set a different base url
Crossref(base_url = "http://some.other.url")
# set an api key
Crossref(api_key = "123456")
# set a mailto address
Crossref(mailto = "foo@bar.com")

Rate limits

See the headers X-Rate-Limit-Limit and X-Rate-Limit-Interval for current rate limits. As of this writing the limit is 50 requests per second, but that could change. In addiiton, it’s not clear what the time is to reset. See below for getting header info for your requests.

Verbose curl output:

import requests
import logging
import httplib as http_client
http_client.HTTPConnection.debuglevel = 1
logging.basicConfig()
logging.getLogger().setLevel(logging.DEBUG)
requests_log = logging.getLogger("requests.packages.urllib3")
requests_log.setLevel(logging.DEBUG)
requests_log.propagate = True

import requests
import logging
logging.getLogger().setLevel(logging.DEBUG)
requests_log = logging.getLogger("requests.packages.urllib3")
requests_log.setLevel(logging.DEBUG)
requests_log.propagate = True

from habanero import Crossref
cr = Crossref()
cr.works(query = "ecology")

Field queries

One or more field queries. Field queries are searches on specific fields. For example, using query_title searches titles instead of full search across all fields as would happen by default. Acceptable set of field query parameters are:

  • query_title - Query title and subtitle
  • query_container_title - Query container-title aka. publication name
  • query_author - Query author first and given names
  • query_editor - Query editor first and given names
  • query_chair - Query chair first and given names
  • query_translator - Query translator first and given names
  • query_contributor - Query author, editor, chair and translator first and given names
  • query_bibliographic - Query bibliographic infomration, useful for citation look up. Includes titles, authors, ISSNs and publication years
  • query_affiliation - Query contributor affiliations

Sort options

  • score or relevance - Sort by relevance score
  • updated - Sort by date of most recent change to metadata. Currently the same as deposited.
  • deposited - Sort by time of most recent deposit
  • indexed - Sort by time of most recent index
  • published - Sort by publication date
  • published-print - Sort by print publication date
  • published-online - Sort by online publication date
  • issued - Sort by issued date (earliest known publication date)
  • is-referenced-by-count - Sort by number of references to documents
  • references-count - Sort by number of references made by documents

Facet count options

  • affiliation - Author affiliation. Allowed value: *
  • year - Earliest year of publication, synonym for published. Allowed value: *
  • funder-name - Funder literal name as deposited alongside DOIs. Allowed value: *
  • funder-doi - Funder DOI. Allowed value: *
  • orcid - Contributor ORCID. Max value: 100
  • container-title - Work container title, such as journal title, or book title. Max value: 100
  • assertion - Custom Crossmark assertion name. Allowed value: *
  • archive - Archive location. Allowed value: *
  • update-type - Significant update type. Allowed value: *
  • issn - Journal ISSN (any - print, electronic, link). Max value: 100
  • published - Earliest year of publication. Allowed value: *
  • type-name - Work type name, such as journal-article or book-chapter. Allowed value: *
  • license - License URI of work. Allowed value: *
  • category-name - Category name of work. Allowed value: *
  • relation-type - Relation type described by work or described by another work with work as object. Allowed value: *
  • assertion-group - Custom Crossmark assertion group name. Allowed value: *



funders(ids=None, query=None, filter=None, offset=None, limit=None, sample=None, sort=None, order=None, facet=None, works=False, select=None, cursor=None, cursor_max=5000, **kwargs)[source]

Search Crossref funders

Note that funders without IDs don’t show up on the /funders route, that is, won’t show up in searches via this method

Parameters:
  • ids – [Array] DOIs (digital object identifier) or other identifiers
  • query – [String] A query string
  • filter – [Hash] Filter options. See examples for usage. Accepts a dict, with filter names and their values. For repeating filter names pass in a list of the values to that filter name, e.g., {‘award_funder’: [‘10.13039/100004440’, ‘10.13039/100000861’]}. See https://github.com/CrossRef/rest-api-doc#filter-names for filter names and their descriptions and filter_names() and filter_details()
  • offset – [Fixnum] Number of record to start at, from 1 to 10000
  • limit – [Fixnum] Number of results to return. Not relavant when searching with specific dois. Default: 20. Max: 1000
  • sample – [Fixnum] Number of random results to return. when you use the sample parameter, the limit and offset parameters are ignored. This parameter only used when works requested. Max: 100
  • sort – [String] Field to sort on. Note: If the API call includes a query, then the sort order will be by the relevance score. If no query is included, then the sort order will be by DOI update date. See sorting for possible values.
  • order – [String] Sort order, one of ‘asc’ or ‘desc’
  • facet – [Boolean/String] Set to true to include facet results (default: false). Optionally, pass a query string, e.g., facet=type-name:* or facet=license=* See Facets for options.
  • select – [String/list(Strings)] Crossref metadata records can be quite large. Sometimes you just want a few elements from the schema. You can “select” a subset of elements to return. This can make your API calls much more efficient. Not clear yet which fields are allowed here.
  • works – [Boolean] If true, works returned as well. Default: false
  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples and FieldQueries)
Returns:

A dict

Usage:

from habanero import Crossref
cr = Crossref()
cr.funders(ids = '10.13039/100000001')
cr.funders(query = "NSF")

# get works
cr.funders(ids = '10.13039/100000001', works = True)

# cursor - deep paging
res = cr.funders(ids = '10.13039/100000001', works = True, cursor = "*", limit = 200)
sum([ len(z['message']['items']) for z in res ])
items = [ z['message']['items'] for z in res ]
items = [ item for sublist in items for item in sublist ]
[ z['DOI'] for z in items ][0:50]

# field queries
res = cr.funders(ids = "10.13039/100000001", works = True, query_container_title = 'engineering', filter = {'type': 'journal-article'})
eds = [ x.get('editor') for x in res['message']['items'] ]
[ z for z in eds if z is not None ]
journals(ids=None, query=None, filter=None, offset=None, limit=None, sample=None, sort=None, order=None, facet=None, works=False, select=None, cursor=None, cursor_max=5000, **kwargs)[source]

Search Crossref journals

Parameters:
  • ids – [Array] DOIs (digital object identifier) or other identifiers
  • query – [String] A query string
  • filter – [Hash] Filter options. See examples for usage. Accepts a dict, with filter names and their values. For repeating filter names pass in a list of the values to that filter name, e.g., {‘award_funder’: [‘10.13039/100004440’, ‘10.13039/100000861’]}. See https://github.com/CrossRef/rest-api-doc#filter-names for filter names and their descriptions and filter_names() and filter_details()
  • offset – [Fixnum] Number of record to start at, from 1 to 10000
  • limit – [Fixnum] Number of results to return. Not relavant when searching with specific dois. Default: 20. Max: 1000
  • sample – [Fixnum] Number of random results to return. when you use the sample parameter, the limit and offset parameters are ignored. This parameter only used when works requested. Max: 100
  • sort – [String] Field to sort on. Note: If the API call includes a query, then the sort order will be by the relevance score. If no query is included, then the sort order will be by DOI update date. See sorting for possible values.
  • order – [String] Sort order, one of ‘asc’ or ‘desc’
  • facet – [Boolean/String] Set to true to include facet results (default: false). Optionally, pass a query string, e.g., facet=type-name:* or facet=license=*. See Facets for options.
  • select – [String/list(Strings)] Crossref metadata records can be quite large. Sometimes you just want a few elements from the schema. You can “select” a subset of elements to return. This can make your API calls much more efficient. Not clear yet which fields are allowed here.
  • works – [Boolean] If true, works returned as well. Default: false
  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples and FieldQueries)
Returns:

A dict

Usage:

from habanero import Crossref
cr = Crossref()
cr.journals(ids = "2167-8359")
cr.journals()

# pass many ids
cr.journals(ids = ['1803-2427', '2326-4225'])

# search
cr.journals(query = "ecology")
cr.journals(query = "peerj")

# get works
cr.journals(ids = "2167-8359", works = True)
cr.journals(ids = "2167-8359", query = 'ecology', works = True, sort = 'score', order = "asc")
cr.journals(ids = "2167-8359", query = 'ecology', works = True, sort = 'score', order = "desc")
cr.journals(ids = "2167-8359", works = True, filter = {'from_pub_date': '2014-03-03'})
cr.journals(ids = '1803-2427', works = True)
cr.journals(ids = '1803-2427', works = True, sample = 1)
cr.journals(limit: 2)

# cursor - deep paging
res = cr.funders(ids = '10.13039/100000001', works = True, cursor = "*", limit = 200)
sum([ len(z['message']['items']) for z in res ])
items = [ z['message']['items'] for z in res ]
items = [ item for sublist in items for item in sublist ]
[ z['DOI'] for z in items ][0:50]

# field queries
res = cr.journals(ids = "2167-8359", works = True, query_title = 'fish', filter = {'type': 'journal-article'})
[ x.get('title') for x in res['message']['items'] ]
licenses(query=None, offset=None, limit=None, sample=None, sort=None, order=None, facet=None, **kwargs)[source]

Search Crossref licenses

Parameters:
  • query – [String] A query string
  • offset – [Fixnum] Number of record to start at, from 1 to 10000
  • limit – [Fixnum] Number of results to return. Not relavant when searching with specific dois. Default: 20. Max: 1000
  • sort – [String] Field to sort on. Note: If the API call includes a query, then the sort order will be by the relevance score. If no query is included, then the sort order will be by DOI update date. See sorting for possible values.
  • order – [String] Sort order, one of ‘asc’ or ‘desc’
  • facet – [Boolean/String] Set to true to include facet results (default: false). Optionally, pass a query string, e.g., facet=type-name:* or facet=license=* See Facets for options.
  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples and FieldQueries)
Returns:

A dict

Usage:

from habanero import Crossref
cr = Crossref()
cr.licenses()
cr.licenses(query = "creative")
members(ids=None, query=None, filter=None, offset=None, limit=None, sample=None, sort=None, order=None, facet=None, works=False, select=None, cursor=None, cursor_max=5000, **kwargs)[source]

Search Crossref members

Parameters:
  • ids – [Array] DOIs (digital object identifier) or other identifiers
  • query – [String] A query string
  • filter – [Hash] Filter options. See examples for usage. Accepts a dict, with filter names and their values. For repeating filter names pass in a list of the values to that filter name, e.g., {‘award_funder’: [‘10.13039/100004440’, ‘10.13039/100000861’]}. See https://github.com/CrossRef/rest-api-doc#filter-names for filter names and their descriptions and filter_names() and filter_details()
  • offset – [Fixnum] Number of record to start at, from 1 to 10000
  • limit – [Fixnum] Number of results to return. Not relavant when searching with specific dois. Default: 20. Max: 1000
  • sample – [Fixnum] Number of random results to return. when you use the sample parameter, the limit and offset parameters are ignored. This parameter only used when works requested. Max: 100
  • sort – [String] Field to sort on. Note: If the API call includes a query, then the sort order will be by the relevance score. If no query is included, then the sort order will be by DOI update date. See sorting for possible values.
  • order – [String] Sort order, one of ‘asc’ or ‘desc’
  • facet – [Boolean/String] Set to true to include facet results (default: false). Optionally, pass a query string, e.g., facet=type-name:* or facet=license=* See Facets for options.
  • select – [String/list(Strings)] Crossref metadata records can be quite large. Sometimes you just want a few elements from the schema. You can “select” a subset of elements to return. This can make your API calls much more efficient. Not clear yet which fields are allowed here.
  • works – [Boolean] If true, works returned as well. Default: false
  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples and FieldQueries)
Returns:

A dict

Usage:

from habanero import Crossref
cr = Crossref()
cr.members(ids = 98)

# get works
res = cr.members(ids = 98, works = True, limit = 3)
len(res['message']['items'])
[ z['DOI'] for z in res['message']['items'] ]

# cursor - deep paging
res = cr.members(ids = 98, works = True, cursor = "*")
sum([ len(z['message']['items']) for z in res ])
items = [ z['message']['items'] for z in res ]
items = [ item for sublist in items for item in sublist ]
[ z['DOI'] for z in items ][0:50]

# field queries
res = cr.members(ids = 98, works = True, query_author = 'carl boettiger', limit = 7)
[ x['author'][0]['family'] for x in res['message']['items'] ]
prefixes(ids=None, filter=None, offset=None, limit=None, sample=None, sort=None, order=None, facet=None, works=False, select=None, cursor=None, cursor_max=5000, **kwargs)[source]

Search Crossref prefixes

Parameters:
  • ids – [Array] DOIs (digital object identifier) or other identifiers
  • filter – [Hash] Filter options. See examples for usage. Accepts a dict, with filter names and their values. For repeating filter names pass in a list of the values to that filter name, e.g., {‘award_funder’: [‘10.13039/100004440’, ‘10.13039/100000861’]}. See https://github.com/CrossRef/rest-api-doc#filter-names for filter names and their descriptions and filter_names() and filter_details()
  • offset – [Fixnum] Number of record to start at, from 1 to 10000
  • limit – [Fixnum] Number of results to return. Not relavant when searching with specific dois. Default: 20. Max: 1000
  • sample – [Fixnum] Number of random results to return. when you use the sample parameter, the limit and offset parameters are ignored. This parameter only used when works requested. Max: 100
  • sort – [String] Field to sort on. Note: If the API call includes a query, then the sort order will be by the relevance score. If no query is included, then the sort order will be by DOI update date. See sorting for possible values.
  • order – [String] Sort order, one of ‘asc’ or ‘desc’
  • facet – [Boolean/String] Set to true to include facet results (default: false). Optionally, pass a query string, e.g., facet=type-name:* or facet=license=* See Facets for options.
  • select – [String/list(Strings)] Crossref metadata records can be quite large. Sometimes you just want a few elements from the schema. You can “select” a subset of elements to return. This can make your API calls much more efficient. Not clear yet which fields are allowed here.
  • works – [Boolean] If true, works returned as well. Default: false
  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples and FieldQueries)
Returns:

A dict

Usage:

from habanero import Crossref
cr = Crossref()
cr.prefixes(ids = "10.1016")
cr.prefixes(ids = ['10.1016','10.1371','10.1023','10.4176','10.1093'])

# get works
cr.prefixes(ids = "10.1016", works = True)

# Limit number of results
cr.prefixes(ids = "10.1016", works = True, limit = 3)

# Sort and order
cr.prefixes(ids = "10.1016", works = True, sort = "relevance", order = "asc")

# cursor - deep paging
res = cr.prefixes(ids = "10.1016", works = True, cursor = "*", limit = 200)
sum([ len(z['message']['items']) for z in res ])
items = [ z['message']['items'] for z in res ]
items = [ item for sublist in items for item in sublist ]
[ z['DOI'] for z in items ][0:50]

# field queries
res = cr.prefixes(ids = "10.1371", works = True, query_editor = 'cooper', filter = {'type': 'journal-article'})
eds = [ x.get('editor') for x in res['message']['items'] ]
[ z for z in eds if z is not None ]
random_dois(sample=10, **kwargs)[source]

Get a random set of DOIs

Parameters:
  • sample – [Fixnum] Number of random DOIs to return. Default: 10. Max: 100
  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples)
Returns:

[Array] of DOIs

Usage:

from habanero import Crossref
cr = Crossref()
cr.random_dois(1)
cr.random_dois(10)
cr.random_dois(50)
cr.random_dois(100)
registration_agency(ids, **kwargs)[source]

Determine registration agency for DOIs

Parameters:
  • ids – [Array] DOIs (digital object identifier) or other identifiers
  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples)
Returns:

list of DOI minting agencies

Usage:

from habanero import Crossref
cr = Crossref()
cr.registration_agency('10.1371/journal.pone.0033693')
cr.registration_agency(ids = ['10.1007/12080.1874-1746','10.1007/10452.1573-5125', '10.1111/(issn)1442-9993'])
types(ids=None, query=None, filter=None, offset=None, limit=None, sample=None, sort=None, order=None, facet=None, works=False, select=None, cursor=None, cursor_max=5000, **kwargs)[source]

Search Crossref types

Parameters:
  • ids – [Array] Type identifier, e.g., journal
  • query – [String] A query string
  • filter – [Hash] Filter options. See examples for usage. Accepts a dict, with filter names and their values. For repeating filter names pass in a list of the values to that filter name, e.g., {‘award_funder’: [‘10.13039/100004440’, ‘10.13039/100000861’]}. See https://github.com/CrossRef/rest-api-doc#filter-names for filter names and their descriptions and filter_names() and filter_details()
  • offset – [Fixnum] Number of record to start at, from 1 to 10000
  • limit – [Fixnum] Number of results to return. Not relavant when searching with specific dois. Default: 20. Max: 1000
  • sample – [Fixnum] Number of random results to return. when you use the sample parameter, the limit and offset parameters are ignored. This parameter only used when works requested. Max: 100
  • sort – [String] Field to sort on. Note: If the API call includes a query, then the sort order will be by the relevance score. If no query is included, then the sort order will be by DOI update date. See sorting for possible values.
  • order – [String] Sort order, one of ‘asc’ or ‘desc’
  • facet – [Boolean/String] Set to true to include facet results (default: false). Optionally, pass a query string, e.g., facet=type-name:* or facet=license=* See Facets for options.
  • select – [String/list(Strings)] Crossref metadata records can be quite large. Sometimes you just want a few elements from the schema. You can “select” a subset of elements to return. This can make your API calls much more efficient. Not clear yet which fields are allowed here.
  • works – [Boolean] If true, works returned as well. Default: false
  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples and FieldQueries)
Returns:

A dict

Usage:

from habanero import Crossref
cr = Crossref()
cr.types()
cr.types(ids = "journal")
cr.types(ids = "journal-article")
cr.types(ids = "journal", works = True)

# field queries
res = cr.types(ids = "journal-article", works = True, query_title = 'gender', rows = 100)
[ x.get('title') for x in res['message']['items'] ]
works(ids=None, query=None, filter=None, offset=None, limit=None, sample=None, sort=None, order=None, facet=None, select=None, cursor=None, cursor_max=5000, **kwargs)[source]

Search Crossref works

Parameters:
  • ids – [Array] DOIs (digital object identifier) or other identifiers
  • query – [String] A query string
  • filter – [Hash] Filter options. See examples for usage. Accepts a dict, with filter names and their values. For repeating filter names pass in a list of the values to that filter name, e.g., {‘award_funder’: [‘10.13039/100004440’, ‘10.13039/100000861’]}. See https://github.com/CrossRef/rest-api-doc#filter-names for filter names and their descriptions and filter_names() and filter_details()
  • offset – [Fixnum] Number of record to start at, from 1 to 10000
  • limit – [Fixnum] Number of results to return. Not relavant when searching with specific dois. Default: 20. Max: 1000
  • sample – [Fixnum] Number of random results to return. when you use the sample parameter, the limit and offset parameters are ignored. Max: 100
  • sort – [String] Field to sort on. Note: If the API call includes a query, then the sort order will be by the relevance score. If no query is included, then the sort order will be by DOI update date. See sorting for possible values.
  • order – [String] Sort order, one of ‘asc’ or ‘desc’
  • facet – [Boolean/String] Set to true to include facet results (default: false). Optionally, pass a query string, e.g., facet=type-name:* or facet=license=*. See Facets for options.
  • select – [String/list(Strings)] Crossref metadata records can be quite large. Sometimes you just want a few elements from the schema. You can “select” a subset of elements to return. This can make your API calls much more efficient. Not clear yet which fields are allowed here.
  • cursor – [String] Cursor character string to do deep paging. Default is None. Pass in ‘*’ to start deep paging. Any combination of query, filters and facets may be used with deep paging cursors. While rows may be specified along with cursor, offset and sample cannot be used. See https://github.com/CrossRef/rest-api-doc/blob/master/rest_api.md#deep-paging-with-cursors
  • cursor_max – [Fixnum] Max records to retrieve. Only used when cursor param used. Because deep paging can result in continuous requests until all are retrieved, use this parameter to set a maximum number of records. Of course, if there are less records found than this value, you will get only those found.
  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples and FieldQueries)
Returns:

A dict

Usage:

from habanero import Crossref
cr = Crossref()
cr.works()
cr.works(ids = '10.1371/journal.pone.0033693')
dois = ['10.1371/journal.pone.0033693', ]
cr.works(ids = dois)
x = cr.works(query = "ecology")
x['status']
x['message-type']
x['message-version']
x['message']
x['message']['total-results']
x['message']['items-per-page']
x['message']['query']
x['message']['items']

# Get full text links
x = cr.works(filter = {'has_full_text': True})
x

# Parse output to various data pieces
x = cr.works(filter = {'has_full_text': True})
## get doi for each item
[ z['DOI'] for z in x['message']['items'] ]
## get doi and url for each item
[ {"doi": z['DOI'], "url": z['URL']} for z in x['message']['items'] ]
### print every doi
for i in x['message']['items']:
     print i['DOI']

# filters - pass in as a dict
## see https://github.com/CrossRef/rest-api-doc#filter-names
cr.works(filter = {'has_full_text': True})
cr.works(filter = {'has_funder': True, 'has_full_text': True})
cr.works(filter = {'award_number': 'CBET-0756451', 'award_funder': '10.13039/100000001'})
## to repeat a filter name, pass in a list
x = cr.works(filter = {'award_funder': ['10.13039/100004440', '10.13039/100000861']}, limit = 100)
map(lambda z:z['funder'][0]['DOI'], x['message']['items'])

# Deep paging, using the cursor parameter
## this search should lead to only ~215 results
cr.works(query = "widget", cursor = "*", cursor_max = 100)
## this search should lead to only ~2500 results, in chunks of 500
res = cr.works(query = "octopus", cursor = "*", limit = 500)
sum([ len(z['message']['items']) for z in res ])
## about 167 results
res = cr.works(query = "extravagant", cursor = "*", limit = 50, cursor_max = 500)
sum([ len(z['message']['items']) for z in res ])
## cursor_max to get back only a maximum set of results
res = cr.works(query = "widget", cursor = "*", cursor_max = 100)
sum([ len(z['message']['items']) for z in res ])
## cursor_max - especially useful when a request could be very large
### e.g., "ecology" results in ~275K records, lets max at 10,000
###   with 1000 at a time
res = cr.works(query = "ecology", cursor = "*", cursor_max = 10000, limit = 1000)
sum([ len(z['message']['items']) for z in res ])
items = [ z['message']['items'] for z in res ]
items = [ item for sublist in items for item in sublist ]
[ z['DOI'] for z in items ][0:50]

# field queries
res = cr.works(query = "ecology", query_author = 'carl boettiger')
[ x['author'][0]['family'] for x in res['message']['items'] ]

# select certain fields to return
## as a comma separated string
cr.works(query = "ecology", select = "DOI,title")
## or as a list
cr.works(query = "ecology", select = ["DOI","title"])