Project COUNTER/NISO SUSHI usage statistics

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Last updateLast update2021-04-12


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pycounter makes working with COUNTER <http://www.projectcounter.org/>_ usage statistics in Python easy, including fetching statistics with NISO SUSHI <http://www.niso.org/workrooms/sushi>_.

A simple command-line client for fetching JR1 reports from SUSHI servers and outputting them as tab-separated COUNTER 4 reports is included.

Developed by the Health Sciences Library System <http://www.hsls.pitt.edu>_ of the University of Pittsburgh <http://www.pitt.edu>_ to support importing usage data into our in-house Electronic Resources Management (ERM) system.

Licensed under the MIT <https://choosealicense.com/licenses/mit/>_ license. See the file LICENSE for details.

pycounter is tested on Python 3.6, 3.7, 3.8, 3.9 and pypy3

Documentation is on Read the Docs <http://pycounter.readthedocs.io>_ and the code can be found on GitHub <https://github.com/pitthsls/pycounter>_.


From pypi <https://pypi.org/project/pycounter/>_:

pip install pycounter

From inside the source distribution:

pip install [-e] .

(use -e if you plan to work on the source itself, so your changes are used in your installation. Probably do all of this in a virtualenv. The PyPA <https://packaging.python.org/tutorials/installing-packages/>_ has a good explanation of how to get started.)


In this release, reports are output in COUNTER 4 format with COUNTER 5 data, which is wrong, and probably not a valid apples-to-apples comparison since, for example, TR_J1 excludes Gold Open Access counts that would be included in JR1, and also has HTML and PDF columns that will always be 0 because these are no longer reported.

Before the 3.0 release, it should be capable of producing actual COUNTER 5 reports, probably with an API for getting COUNTER 4 style data compatible with scripts that were making assumptions about the data received to pass it into another system.


Parsing COUNTER reports (currently supports 4 in .csv, .tsv, or .xlsx files, reports JR1, JR2, DB1, DB2, BR1, BR2, and BR3) and COUNTER 5::

>>> import pycounter.report
>>> report = pycounter.report.parse("COUNTER4_2015.tsv")  # filename or path to file
>>> print(report.metric)
FT Article Requests
>>> for journal in report:
...     print(journal.title)
Sqornshellous Swamptalk
Acta Mattressica
>>> for stat in report.pubs[0]:
...     print(stat)
(datetime.date(2015, 1, 1), 'FT Article Requests', 120)
(datetime.date(2015, 2, 1), 'FT Article Requests', 42)
(datetime.date(2015, 3, 1), 'FT Article Requests', 23)

Fetching SUSHI data::

>>> import pycounter.sushi
>>> import datetime
>>> report = pycounter.sushi.get_report(wsdl_url='http://www.example.com/SushiService',
...     start_date=datetime.date(2015,1,1), end_date=datetime.date(2015,1,31),
...     requestor_id="myreqid", customer_reference="refnum", report="JR1",
...     release=4)
>>> for journal in report:
...     print(journal.title)
Sqornshellous Swamptalk
Acta Mattressica

Output of report as TSV::

>>> report.write_tsv("/tmp/counterreport.tsv")


Our code is automatically styled using black. To install the pre-commit hook:

pip install pre-commit

pre-commit install