rispy 0.7.1

A Python reader/writer of RIS reference files

A Python 3.6+ reader/writer of RIS reference files.

Usage

Parsing:

>>> import rispy
>>> filepath = 'tests/data/example_full.ris'
>>> with open(filepath, 'r') as bibliography_file:
...     entries = rispy.load(bibliography_file)
...     for entry in entries:
...         print(entry['id'])
...         print(entry['first_authors'])
12345
['Marx, Karl', 'Lindgren, Astrid']
12345
['Marxus, Karlus', 'Lindgren, Astrid']

A file path can also be used to read RIS files. If an encoding is not specified in load, the default system encoding will be used.

>>> from pathlib import Path
>>> import rispy
>>> p = Path('tests', 'data', 'example_utf_chars.ris')
>>> entries = rispy.load(p, encoding='utf-8')
>>> for entry in entries:
...     print(entry['authors'][0])
Dobrokhotova, Yu E.

Writing:

>>> import rispy
>>> entries = [
... {'type_of_reference': 'JOUR',
...  'id': '42',
...  'primary_title': 'The title of the reference',
...  'first_authors': ['Marxus, Karlus', 'Lindgren, Astrid']
...  },{
... 'type_of_reference': 'JOUR',
...  'id': '43',
...  'primary_title': 'Reference 43',
...  'abstract': 'Lorem ipsum'
...  }]
>>> filepath = 'export.ris'
>>> with open(filepath, 'w') as bibliography_file:
...     rispy.dump(entries, bibliography_file)

Example RIS entry

1.
TY  - JOUR
ID  - 12345
T1  - Title of reference
A1  - Marx, Karl
A1  - Lindgren, Astrid
A2  - Glattauer, Daniel
Y1  - 2014//
N2  - BACKGROUND: Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus.  RESULTS: Donec quam felis, ultricies nec, pellentesque eu, pretium quis, sem. Nulla consequat massa quis enim. CONCLUSIONS: Donec pede justo, fringilla vel, aliquet nec, vulputate eget, arcu. In enim justo, rhoncus ut, imperdiet a, venenatis vitae, justo. Nullam dictum felis eu pede mollis pretium.
KW  - Pippi
KW  - Nordwind
KW  - Piraten
JF  - Lorem
JA  - lorem
VL  - 9
IS  - 3
SP  - e0815
CY  - United States
PB  - Fun Factory
PB  - Fun Factory USA
SN  - 1932-6208
M1  - 1008150341
L2  - http://example.com
ER  -

TAG_KEY_MAPPING

The most fields contain string values, but some like first_authors (A1) are parsed into lists. The default mapping were created from specifications scattered around the web, but to our knowledge there is not one single source of RIS truth, so these may need to be modified for specific export systems:

• Wikipedia
• ResearcherId
• Refman
• Refman (RIS format)
• Zotero

Complete list of ListType tags

>>> from rispy import LIST_TYPE_TAGS
>>> print(LIST_TYPE_TAGS)
['A1', 'A2', 'A3', 'A4', 'AU', 'KW', 'N1']

Complete default mapping

>>> from rispy import TAG_KEY_MAPPING
>>> from pprint import pprint
>>> pprint(TAG_KEY_MAPPING)
{'A1': 'first_authors',
 'A2': 'secondary_authors',
 'A3': 'tertiary_authors',
 'A4': 'subsidiary_authors',
 'AB': 'abstract',
 'AD': 'author_address',
 'AN': 'accession_number',
 'AU': 'authors',
 'C1': 'custom1',
 'C2': 'custom2',
 'C3': 'custom3',
 'C4': 'custom4',
 'C5': 'custom5',
 'C6': 'custom6',
 'C7': 'custom7',
 'C8': 'custom8',
 'CA': 'caption',
 'CN': 'call_number',
 'CY': 'place_published',
 'DA': 'date',
 'DB': 'name_of_database',
 'DO': 'doi',
 'DP': 'database_provider',
 'EP': 'end_page',
 'ER': 'end_of_reference',
 'ET': 'edition',
 'ID': 'id',
 'IS': 'number',
 'J2': 'alternate_title1',
 'JA': 'alternate_title2',
 'JF': 'alternate_title3',
 'JO': 'journal_name',
 'KW': 'keywords',
 'L1': 'file_attachments1',
 'L2': 'file_attachments2',
 'L4': 'figure',
 'LA': 'language',
 'LB': 'label',
 'M1': 'note',
 'M3': 'type_of_work',
 'N1': 'notes',
 'N2': 'notes_abstract',
 'NV': 'number_of_volumes',
 'OP': 'original_publication',
 'PB': 'publisher',
 'PY': 'year',
 'RI': 'reviewed_item',
 'RN': 'research_notes',
 'RP': 'reprint_edition',
 'SE': 'section',
 'SN': 'issn',
 'SP': 'start_page',
 'ST': 'short_title',
 'T1': 'primary_title',
 'T2': 'secondary_title',
 'T3': 'tertiary_title',
 'TA': 'translated_author',
 'TI': 'title',
 'TT': 'translated_title',
 'TY': 'type_of_reference',
 'UK': 'unknown_tag',
 'UR': 'url',
 'VL': 'volume',
 'Y1': 'publication_year',
 'Y2': 'access_date'}

Override key mapping

The parser use a TAG_KEY_MAPPING, which one can override by calling rispy.load() with the mapping parameter.

>>> from copy import deepcopy
>>> import rispy
>>> from pprint import pprint

>>> filepath = 'tests/data/example_full.ris'
>>> mapping = deepcopy(rispy.TAG_KEY_MAPPING)
>>> mapping["SP"] = "pages_this_is_my_fun"
>>> with open(filepath, 'r') as bibliography_file:
...     entries = rispy.load(bibliography_file, mapping=mapping)
...     pprint(sorted(entries[0].keys()))
['alternate_title2',
 'alternate_title3',
 'file_attachments2',
 'first_authors',
 'id',
 'issn',
 'keywords',
 'note',
 'notes_abstract',
 'number',
 'pages_this_is_my_fun',
 'place_published',
 'primary_title',
 'publication_year',
 'publisher',
 'secondary_authors',
 'type_of_reference',
 'url',
 'volume']

List tags can be customized in the same way, by passing a list to the list_tags parameter.

Changing rispy behavior

There are a few flags that can be passed to rispy.load() and rispy.dump() that change how rispy deals with tags. For example, setting skip_unknown_tags to True will cause rispy do not read or write tags not in the tag map. More can be found in the docstrings for each class. If more customization is necessary, a custom implementation can be created (see next section).

Using custom implementations

Not all RIS files follow the same formatting guidelines. There is an interface for creating custom implementations for reading and writing such files. An implementation contains the methods and parameters used to work with RIS files, and should be passed to rispy.load() or rispy.dump().

Customizing implementations

Creating a custom implentation involves creating a class that inherits a base class, and overriding the necessary variables and methods. One of the existing parsers can also be inherited. Inheriting an existing class is advantageous if only minor changes need to be made. The sections below document what is available to be overriden, along with a few examples.

Parsing

Custom parsers can inherit RisParser (the default parser) or BaseParser. Various parameters and methods can be overridden when creating a new parser. These are documented in the BaseParser docstring.

Examples:

class WokParser(BaseParser):
    """Subclass of Base for reading Wok RIS files."""

    START_TAG = "PT"
    IGNORE = ["FN", "VR", "EF"]
    PATTERN = r"^[A-Z][A-Z0-9] |^ER\s?|^EF\s?"
    DEFAULT_MAPPING = WOK_TAG_KEY_MAPPING
    DEFAULT_LIST_TAGS = WOK_LIST_TYPE_TAGS

    def get_content(self, line):
        return line[2:].strip()

    def is_header(self, line):
        return True

Writing

Writing is very similar to parsing. A custom writer class can inherit BaseWriter or one if its subclasses, such as RisWriter.

Examples:

class RisWriter(BaseWriter):
    """Subclass of BaseWriter for writing RIS files."""

    START_TAG = "TY"
    PATTERN = "{tag}  - {value}"
    DEFAULT_MAPPING = TAG_KEY_MAPPING
    DEFAULT_LIST_TAGS = LIST_TYPE_TAGS

    def set_header(self, count):
        return "{i}.".format(i=count)

Other functionality

Other various utilities included in rispy are documented below.

Reference type conversion

A method is available to convert common RIS reference types into more readable terms. It takes a list of references and returns a copy of that list with modified reference types. The map for this conversion is located in config.py.

>>> from rispy.utils import convert_reference_types
>>> refs = [{"type_of_reference": "JOUR"}]
>>> print(convert_reference_types(refs))
[{'type_of_reference': 'Journal'}]

Software for other RIS-like formats

Some RIS-like formats contain rich citation data, for example lists and nested attributes, that rispy does not support. Software specializing on these formats include:

• nbib parses the “PubMed” or “MEDLINE” format

Developer instructions

Common developer commands are in the provided Makefile; if you don’t have make installed, you can view the make commands and run the commands from the command-line manually:

# setup environment
python -m venv venv
source venv/bin/activate
pip install -e .[dev,test]

# check if code format changes are required
make lint

# reformat code
make format

# run tests
make test

Github Actions are currently enabled to run lint and test when submitting a pull-request.