pybliometrics.scival.PublicationLookup

PublicationLookup() implements the base endpoint of the SciVal Publication Lookup API.

It accepts a Scopus ID as the main argument.

Documentation

class pybliometrics.scival.PublicationLookup(identifier=None, refresh=False, **kwds)[source]

Interaction with the Publication Lookup API.

Parameters:

  • identifier (int | str | None, optional) – The Scopus ID of the publication.

    Default: None

  • refresh (bool | int, optional) –

    Whether to refresh the cached file if it exists or not. If int is passed, cached file will be refreshed if the number of days since last modification exceeds that value.

    Default: False

  • kwds (str) – Keywords passed on as query parameters. Must contain fields and values mentioned in the API specification at https://dev.elsevier.com/documentation/SciValPublicationAPI.wadl.

property authors: list[Author] | None

A list of namedtuples representing listed authors in the form (id, name, uri).

property citation_count: int | None

Count of citations.

property doi: str | None

Digital Object Identifier (DOI).

property id: int | None

ID of the document (same as EID without “2-s2.0-“).

property institutions: list[Institution] | None

A list of namedtuples representing listed institutions in the form (id, name, country, country_code).

URL link.

property publication_year: int | None

Year of publication.

property sdgs: list[str] | None

Sustainable Development Goals.

property source_title: str | None

Title of source.

property title: str | None

Publication title.

property topic_cluster_id: int | None

Topic cluster id.

property topic_id: int | None

Topic id.

property type: str | None

Type of publication.

get_cache_file_age()

Return the age of the cached file in days.

Return type:

int

get_cache_file_mdate()

Return the modification date of the cached file.

Return type:

str

get_key_remaining_quota()

Return number of remaining requests for the current key and the current API (relative on last actual request).

Return type:

str | None

get_key_reset_time()

Return time when current key is reset (relative on last actual request).

Return type:

str | None

Examples

You initialize the class with the Scopus ID. The argument can be an integer or a string.

>>> import pybliometrics
>>> from pybliometrics.scival import PublicationLookup
>>> pybliometrics.scival.init()
>>> pub = PublicationLookup('85036568406')

You can obtain basic information just by printing the object:

>>> print(pub)
Document with Scopus Id 85036568406 received:
- Title: Soft Electrochemical Probes for Mapping the Distribution of Biomarkers and Injected Nanomaterials in Animal and Human Tissues
- DOI: 10.1002/anie.201709271
- Type: Article
- Publication Year: 2017
- 7 author(s) found
- 3 institution(s) found

There are many attributes available in the response from the API. It is possible to explore the properties as in the following example:

>>> pub.id
85036568406
>>> pub.title
'Soft Electrochemical Probes for Mapping the Distribution of Biomarkers and Injected Nanomaterials in Animal and Human Tissues'
>>> pub.doi
'10.1002/anie.201709271'
>>> pub.publication_year
2017
>>> pub.type
'Article'
>>> pub.citation_count
34
>>> pub.source_title
'Angewandte Chemie - International Edition'
>>> pub.topic_id
7563
>>> pub.topic_cluster_id
157
>>> pub.sdgs
['SDG 3: Good Health and Well-being']

You can retrieve the authors as a list of namedtuples, which pair conveniently with pandas:

>>> pub.authors
[Author(id=7404861905, name='Lin, T.-E.', uri='Author/7404861905'),
 Author(id=24537666700, name='Lu, Y.-J.', uri='Author/24537666700'),
 Author(id=7404248170, name='Sun, C.-L.', uri='Author/7404248170'),
 Author(id=7004202515, name='Pick, H.', uri='Author/7004202515'),
 Author(id=58307174900, name='Chen, J.-P.', uri='Author/58307174900'),
 Author(id=36246291500, name='Lesch, A.', uri='Author/36246291500'),
 Author(id=7102360867, name='Girault, H.H.', uri='Author/7102360867')]

>>> import pandas as pd
>>> print(pd.DataFrame(pub.authors))
            id           name                 uri
0   7404861905     Lin, T.-E.   Author/7404861905
1  24537666700      Lu, Y.-J.  Author/24537666700
2   7404248170     Sun, C.-L.   Author/7404248170
3   7004202515       Pick, H.   Author/7004202515
4  58307174900    Chen, J.-P.  Author/58307174900
5  36246291500      Lesch, A.  Author/36246291500
6   7102360867  Girault, H.H.   Author/7102360867

The same structure applies for the attribute institutions:

>>> pub.institutions
[Institution(id=217002, name='Chang Gung University', country='Taiwan', country_code='TWN'),
 Institution(id=306002, name='Swiss Federal Institute of Technology Lausanne', country='Switzerland', country_code='CHE'),
 Institution(id=725104, name='Chang Gung Memorial Hospital', country='Taiwan', country_code='TWN')]

>>> import pandas as pd
>>> print(pd.DataFrame(pub.institutions))
       id                                            name      country country_code
0  217002                           Chang Gung University       Taiwan          TWN
1  306002  Swiss Federal Institute of Technology Lausanne  Switzerland          CHE
2  725104                    Chang Gung Memorial Hospital       Taiwan          TWN

Downloaded results are cached to expedite subsequent analyses. This information may become outdated. To refresh the cached results if they exist, set refresh=True, or provide an integer that will be interpreted as the maximum allowed number of days since the last modification date. For example, if you want to refresh all cached results older than 100 days, set refresh=100. Use ab.get_cache_file_mdate() to obtain the date of last modification, and ab.get_cache_file_age() to determine the number of days since the last modification.