crossref module

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

Crossref: Class for Crossref search API methods

Parameters:
  • base_url (str) – Base URL to use for http requests

  • api_key (str) – An API key to send with each http request

  • mailto (str) – A mailto string, see section below

  • ua_string (str) – A user agent string, see section below



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 Crossref API using HTTPS and provide contact information, then they will send you to a separate pool of machines, with better control of 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.

Setting a custom user-agent string

Using ua_string you can set an additional string that will be added to the UA string we send in every request, which looks like: python-requests/2.22.0 habanero/0.7.0. We send that string with the headers: User-Agent and X-USER-AGENT. Turn on verbose curl output to see the request headers sent. To unset the ua_string you set, just initialize a new Crossref class.

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 to get into the "polite pool"
Crossref(mailto = "foo@bar.com")
# set an additional user-agent string
Crossref(ua_string = "foo bar")

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 addition, 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 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

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_author searches author names instead of full search across all fields as would happen by default. Acceptable field query parameters have all underscores where Crossref API documentation has . or -. For example, query.funder-name using the Crossref API should be query_funder_name. See “Field queries” under the Crossref API documentation for the supported field queries.

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, progress_bar=False, warn=False, **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 (Union[List[str], str]) – DOIs (digital object identifier) or other identifiers

  • query (str) – A query string

  • filter (dict) – 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() IMPORTANT: when works=False the filters that will work are the funders filters; when works=True the filters that will work are the works filters

  • offset (float) – Number of record to start at, from 1 to 10000

  • limit (float) – Number of results to return. Not relavant when searching with specific dois. Default: 20. Max: 1000

  • sample (float) – 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 (str) – 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 (str) – Sort order, one of ‘asc’ or ‘desc’

  • facet (Union[str, bool]) – 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 (Union[List[str], str]) – 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 (bool) – If true, works returned as well. Default: false

  • cursor (str) – 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. Only used if works=True See https://github.com/CrossRef/rest-api-doc/blob/master/rest_api.md#deep-paging-with-cursors

  • cursor_max (float) – 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. Only used if works=True

  • progress_bar (bool) – print progress bar. only used when doing deep paging ( when using cursor parameter). Only used if works=True. default: False

  • warn (bool) – warn instead of raise error upon HTTP request error. default: False Especially helpful when passing in many DOIs where some may lead to request failures. Returns None when warn=True for each DOI that errors.

  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples and FieldQueries)

Return type:

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]
## use progress bar
res = cr.funders(ids = '10.13039/100000001', works = True, cursor = "*", cursor_max = 200, progress_bar = True)

# 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 ]

# filters (as of this writing, only 1 filter is avail., "location")
cr.funders(filter = {'location': "Sweden"})

# warn
cr.funders(ids = '10.13039/notarealdoi')
cr.funders(ids = '10.13039/notarealdoi', warn=True)
cr.funders(ids = '10.13039/notarealdoi', works=True, warn=True)
cr.funders(ids = ['10.13039/100000001','10.13039/notarealdoi'], works=True, warn=True)
x = cr.funders(ids = ['10.13039/100000001','10.13039/notarealdoi'], warn=True)
len(x) # 2
[type(w) for w in x] # [dict, NoneType]
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, progress_bar=False, warn=False, **kwargs)[source]

Search Crossref journals

Parameters:
  • ids (Union[List[str], str]) – DOIs (digital object identifier) or other identifiers

  • query (str) – A query string

  • filter (dict) – 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 (float) – Number of record to start at, from 1 to 10000

  • limit (float) – Number of results to return. Not relevant when searching with specific dois. Default: 20. Max: 1000

  • sample (float) – 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 (str) – 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 (str) – Sort order, one of ‘asc’ or ‘desc’

  • facet (Union[str, bool]) – 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 (Union[List[str], str]) – 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 (bool) – If true, works returned as well. Default: false

  • cursor (str) – 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. Only used if works=True See https://github.com/CrossRef/rest-api-doc/blob/master/rest_api.md#deep-paging-with-cursors

  • cursor_max (float) – 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. Only used if works=True

  • progress_bar (bool) – print progress bar. only used when doing deep paging ( when using cursor parameter). Only used if works=True. default: False

  • warn (bool) – warn instead of raise error upon HTTP request error. default: False Especially helpful when passing in many DOIs where some may lead to request failures. Returns None when warn=True for each DOI that errors.

  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples and FieldQueries)

Return type:

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.journals(ids = "2167-8359", works = True, cursor = "*", cursor_max = 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]
## use progress bar
res = cr.journals(ids = "2167-8359", works = True, cursor = "*", cursor_max = 200, progress_bar = True)

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

Search Crossref licenses

Parameters:
  • query (str) – A query string

  • offset (float) – Number of record to start at, from 1 to 10000

  • limit (float) – Number of results to return. Not relevant when searching with specific dois. Default: 20. Max: 1000

  • sort (str) – 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 (str) – Sort order, one of ‘asc’ or ‘desc’

  • facet (Union[str, bool]) – 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)

Return type:

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, progress_bar=False, warn=False, **kwargs)[source]

Search Crossref members

Parameters:
  • ids (Union[List[str], str]) – DOIs (digital object identifier) or other identifiers

  • query (str) – A query string

  • filter (dict) – 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() IMPORTANT: when works=False the filters that will work are the members filters; when works=True the filters that will work are the works filters

  • offset (float) – Number of record to start at, from 1 to 10000

  • limit (float) – Number of results to return. Not relavant when searching with specific dois. Default: 20. Max: 1000

  • sample (float) – 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 (str) – 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 (str) – Sort order, one of ‘asc’ or ‘desc’

  • facet (Union[str, bool]) – 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 (Union[List[str], str]) – 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 (bool) – If true, works returned as well. Default: false

  • cursor (str) – 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. Only used if works=True See https://github.com/CrossRef/rest-api-doc/blob/master/rest_api.md#deep-paging-with-cursors

  • cursor_max (float) – 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. Only used if works=True

  • progress_bar (bool) – print progress bar. only used when doing deep paging ( when using cursor parameter). Only used if works=True. default: False

  • warn (bool) – warn instead of raise error upon HTTP request error. default: False Especially helpful when passing in many DOIs where some may lead to request failures. Returns None when warn=True for each DOI that errors.

  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples and FieldQueries)

Return type:

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]
## use progress bar
res = cr.members(ids = 98, works = True, cursor = "*", cursor_max = 500, progress_bar = True)

# 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'] ]

# filters (as of this writing, 4 filters are avail., see filter_names())
res = cr.members(filter = {'has_public_references': True})
prefixes(ids, filter=None, offset=None, limit=None, sample=None, sort=None, order=None, facet=None, works=False, select=None, cursor=None, cursor_max=5000, progress_bar=False, warn=False, **kwargs)[source]

Search Crossref prefixes

Parameters:
  • ids (Union[List[str], str]) – DOIs (digital object identifier) or other identifiers. required

  • filter (dict) – 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 (float) – Number of record to start at, from 1 to 10000

  • limit (float) – Number of results to return. Not relevant when searching with specific dois. Default: 20. Max: 1000

  • sample (float) – 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 (str) – 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 (str) – Sort order, one of ‘asc’ or ‘desc’

  • facet (Union[str, bool]) – 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 (Union[List[str], str]) – 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 (bool) – If true, works returned as well. Default: false

  • cursor (str) – 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. Only used if works=True See https://github.com/CrossRef/rest-api-doc/blob/master/rest_api.md#deep-paging-with-cursors

  • cursor_max (float) – 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. Only used if works=True

  • progress_bar (bool) – print progress bar. only used when doing deep paging ( when using cursor parameter). Only used if works=True. default: False

  • warn (bool) – warn instead of raise error upon HTTP request error. default: False Especially helpful when passing in many DOIs where some may lead to request failures. Returns None when warn=True for each DOI that errors.

  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples and FieldQueries)

Return type:

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]
## use progress bar
res = cr.prefixes(ids = "10.1016", works = True, cursor = "*", cursor_max = 200, progress_bar = True)

# 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 (int) – 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)

Return type:

list

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 (Union[List[str], str]) – DOIs (digital object identifier) or other identifiers

  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples)

Return type:

list

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, progress_bar=False, warn=False, **kwargs)[source]

Search Crossref types

Parameters:
  • ids (Union[List[str], str]) – Type identifier, e.g., journal

  • query (str) – A query string

  • filter (dict) – 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 (float) – Number of record to start at, from 1 to 10000

  • limit (float) – Number of results to return. Not relevant when searching with specific dois. Default: 20. Max: 1000

  • sample (float) – 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 (str) – 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 (str) – Sort order, one of ‘asc’ or ‘desc’

  • facet (Union[str, bool]) – 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 (Union[List[str], str]) – 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 (bool) – If true, works returned as well. Default: false

  • cursor (str) – 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. Only used if works=True See https://github.com/CrossRef/rest-api-doc/blob/master/rest_api.md#deep-paging-with-cursors

  • cursor_max (float) – 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. Only used if works=True

  • progress_bar (bool) – print progress bar. only used when doing deep paging ( when using cursor parameter). Only used if works=True. default: False

  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples and FieldQueries)

Return type:

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)

# deep paging
res = cr.types(ids = "journal-article", works = True, cursor = "*", cursor_max = 120)
## use progress bar
res = cr.types(ids = "journal-article", works = True, cursor = "*", cursor_max = 120, progress_bar = True)

# field queries
res = cr.types(ids = "journal-article", works = True, query_bibliographic = '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, progress_bar=False, warn=False, **kwargs)[source]

Search Crossref works

Parameters:
  • ids (Union[List[str], str]) – DOIs (digital object identifier) or other identifiers

  • query (str) – A query string

  • filter (dict) – 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 (float) – Number of record to start at, from 1 to 10000

  • limit (float) – Number of results to return. Not relavant when searching with specific dois. Default: 20. Max: 1000

  • sample (float) – Number of random results to return. when you use the sample parameter, the limit and offset parameters are ignored. Max: 100

  • sort (str) – 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 (str) – Sort order, one of ‘asc’ or ‘desc’

  • facet (Union[str, bool]) – 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 (Union[List[str], str]) – 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 (str) – 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 (float) – 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.

  • progress_bar (bool) – print progress bar. only used when doing deep paging ( when using cursor parameter). default: False

  • warn (bool) – warn instead of raise error upon HTTP request error. default: False Especially helpful when passing in many DOIs where some may lead to request failures. Returns None when warn=True for each DOI that errors.

  • kwargs – additional named arguments passed on to requests.get, e.g., field queries (see examples and FieldQueries)

Return type:

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]
### use progress bar
res = cr.works(query = "octopus", cursor = "*", limit = 500, progress_bar = True)

# 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"])

# set an additional user-agent string
## the string is additional because it's added to the UA string we send in every request
## turn on verbose curl output to see the request headers sent
x = Crossref(ua_string = "foo bar")
x
x.works(ids = '10.1371/journal.pone.0033693')
## unset the additional user-agent string
x = Crossref()
x.works(ids = '10.1371/journal.pone.0033693')