Package: eyecite
eyeciteeyecite is an open source tool for extracting legal citations from text. It is used, among other things, to process millions of legal documents in the collections ofCourtListenerand Harvard’sCaselaw Access Project, and has been developed in collaboration with both projects.eyecite recognizes a wide variety of citations commonly appearing in American legal decisions, including:full case:Bush v. Gore, 531 U.S. 98,99-100(2000)short case:531 U.S., at 99statutory:Mass. Gen. Laws ch. 1, § 2law journal:1 Minn. L. Rev. 1supra:Bush, supra, at 100id.:Id., at 101All contributors, corrections, and additions are welcome!If you use eyecite for your research, please consider citing our paper:@article{eyecite,
    title = {eyecite: A Tool for Parsing Legal Citations},
    author = {Cushman, Jack and Dahl, Matthew and Lissner, Michael},
    year = {2021},
    journal = {Journal of Open Source Software},
    volume = {6},
    number = {66},
    pages = {3617},
    url = {https://doi.org/10.21105/joss.03617},
}Functionalityeyecite offers four core functions:Extraction: Recognize and extract citations from text, using a database that has been trained on over 55 million existing citations (see all of the citation patterns eyecite looks for over inreporters_db).Aggregation: Aggregate citations with common references (e.g.,supraandid.citations) based on their logical antecedents.Annotation: Annotate citation-laden text with custom markup surrounding each citation, using a fast diffing algorithm.Cleaning: Clean and pre-process text for easy use with eyecite.Read on below for how to get started quickly or for a short tutorial in using eyecite.Contributions & SupportPlease see the issues list on GitHub for things we need, or start a conversation if you have questions or need support.If you are fixing bugs or adding features, before you make your first contribution, we’ll need a signed contributor license agreement. See the template in the root of the repo for how to get that taken care of.APIThe API documentation is located here:https://freelawproject.github.io/eyecite/It is autogenerated whenever we release a new version. Unfortunately, for now we do not support old versions of the API documentation, but it can be browsed in the gh-pages branch if needed.QuickstartInstall eyecite:pip install eyeciteHere’s a short example of extracting citations and their metadata from text using eyecite’s mainget_citations()function:from eyecite import get_citations

text = """
    Mass. Gen. Laws ch. 1, § 2 (West 1999) (barring ...).
    Foo v. Bar, 1 U.S. 2, 3-4 (1999) (overruling ...).
    Id. at 3.
    Foo, supra, at 5.
"""

get_citations(text)

# returns:
[
    FullLawCitation(
        'Mass. Gen. Laws ch. 1, § 2',
        groups={'reporter': 'Mass. Gen. Laws', 'chapter': '1', 'section': '2'},
        metadata=Metadata(parenthetical='barring ...', pin_cite=None, year='1999', publisher='West', ...)
    ),
    FullCaseCitation(
        '1 U.S. 2',
        groups={'volume': '1', 'reporter': 'U.S.', 'page': '2'},
        metadata=Metadata(parenthetical='overruling ...', pin_cite='3-4', year='1999', court='scotus', plaintiff='Foo', defendant='Bar,', ...)
    ),
    IdCitation(
        'Id.',
        metadata=Metadata(pin_cite='at 3')
    ),
    SupraCitation(
        'supra,',
        metadata=Metadata(antecedent_guess='Foo', pin_cite='at 5', ...)
    )
]TutorialFor a more full-featured walkthrough of how to use all of eyecite’s functionality,
please see thetutorial.Documentationeyecite’s full API is documentedhere, but here are details regarding its four core functions, its tokenization logic, and its debugging tools.Extracting Citationsget_citations(), the main executable function, takes three parameters.plain_text==> str: The text to parse. Should be cleaned first.remove_ambiguous==> bool, defaultFalse: Whether to remove citations
that might refer to more than one reporter and can’t be narrowed down by date.tokenizer==> Tokenizer, defaulteyecite.tokenizers.default_tokenizer: An instance of a Tokenizer object (see “Tokenizers” below).Cleaning Input TextFor a given citation text such as “… 1 Baldwin’s Rep. 1 …”, eyecite expects that the text
will be “clean” before being passed toget_citation. This means:Spaces will be single space characters, not multiple spaces or other whitespace.Quotes and hyphens will be standard quote and hyphen characters.No junk such as HTML tags inside the citation.You can useclean_textto help with this:from eyecite import clean_text, get_citations

source_text = '<p>foo   1  U.S.  1   </p>'
plain_text = clean_text(text, ['html', 'inline_whitespace', my_func])
found_citations = get_citations(plain_text)See theAnnotating Citationssection for how to insert links into the original text using
citations extracted from the cleaned text.clean_textcurrently accepts these values as cleaners:inline_whitespace: replace all runs of tab and space characters with a single space characterall_whitespace: replace all runs of any whitespace character with a single space characterunderscores: remove two or more underscores, a common error in text extracted from PDFshtml: remove non-visible HTML content using the lxml libraryCustom function: any function taking a string and returning a string.Annotating CitationsFor simple plain text, you can insert links to citations using theannotate_citationsfunction:from eyecite import get_citations, annotate_citations

plain_text = 'bob lissner v. test 1 U.S. 12, 347-348 (4th Cir. 1982)'
citations = get_citations(plain_text)
linked_text = annotate_citations(plain_text, [[c.span(), "<a>", "</a>"] for c in citations])

returns:
'bob lissner v. test <a>1 U.S. 12</a>, 347-348 (4th Cir. 1982)'Each citation returned by get_citations keeps track of where it was found in the source text.
As a result,annotate_citationsmust be called with thesamecleaned text used byget_citationsto extract citations. If you do not, the offsets returned by the citation’sspanmethod will
not align with the text, and your annotations will be in the wrong place.If you want to clean text and then insert annotations into the original text, you can pass
the original text in assource_text:from eyecite import get_citations, annotate_citations, clean_text

source_text = '<p>bob lissner v. <i>test   1 U.S.</i> 12,   347-348 (4th Cir. 1982)</p>'
plain_text = clean_text(source_text, ['html', 'inline_whitespace'])
citations = get_citations(plain_text)
linked_text = annotate_citations(plain_text, [[c.span(), "<a>", "</a>"] for c in citations], source_text=source_text)

returns:
'<p>bob lissner v. <i>test   <a>1 U.S.</i> 12</a>,   347-348 (4th Cir. 1982)</p>'The above example extracts citations fromplain_textand applies them tosource_text, using a diffing algorithm to insert annotations in the correct locations
in the original text.There is also afull_spanattribute that can be used to get the indexes of the full citation, including the
pre- and post-citation attributes.Wrapping HTML TagsNote that the above example includes mismatched HTML tags: “<a>1 U.S.</i> 12</a>”.
To specify handling for unbalanced tags, use theunbalanced_tagsparameter:unbalanced_tags="skip": annotations that would result in unbalanced tags will not be inserted.unbalanced_tags="wrap": unbalanced tags will be wrapped, resulting in<a>1 U.S.</a></i><a> 12</a>Important:unbalanced_tags="wrap"uses a simple regular expression and will only work for HTML where
angle brackets are properly escaped, such as the HTML emitted bylxml.html.tostring. It is intended for
regularly formatted documents such as case text published by courts. It may have
unpredictable results for deliberately-constructed challenging inputs such as citations containing partial HTML
comments or<pre>tags.Customizing AnnotationIf inserting text before and after isn’t sufficient, supply a callable under theannotatorparameter
that takes(before, span_text, after)and returns the annotated text:def annotator(before, span_text, after):
    return before + span_text.lower() + after
linked_text = annotate_citations(plain_text, [[c.span(), "<a>", "</a>"] for c in citations], annotator=annotator)

returns:
'bob lissner v. test <a>1 u.s. 12</a>, 347-348 (4th Cir. 1982)'Resolving CitationsOnce you have extracted citations from a document, you may wish to resolve them to their common references.
To do so, just pass the results ofget_citations()intoresolve_citations(). This function will
do its best to resolve each “full,” “short form,” “supra,” and “id” citation to a commonResourceobject,
returning a dictionary that maps resources to lists of associated citations:from eyecite import get_citations, resolve_citations

text = 'first citation: 1 U.S. 12. second citation: 2 F.3d 2. third citation: Id.'
found_citations = get_citations(text)
resolved_citations = resolve_citations(found_citations)

returns (pseudo):
{
    <Resource object>: [FullCaseCitation('1 U.S. 12')],
    <Resource object>: [FullCaseCitation('2 F.3d 2'), IdCitation('Id.')]
}Importantly, eyecite performs these resolutions using only its immanent knowledge about each citation’s
textual representation. If you want to perform more sophisticated resolution (e.g., by augmenting each
citation with information from a third-party API), simply pass customresolve_id_citation(),resolve_supra_citation(),resolve_shortcase_citation(), andresolve_full_citation()functions toresolve_citations()as keyword arguments. You can also configure those functions to
return a more complex resource object (such as a Django model), so long as that object inherits theeyecite.models.ResourceTypetype (which simply requires hashability). For example, you might implement
a custom full citation resolution function as follows, using the default resolution logic as a fallback:def my_resolve(full_cite):
    # special handling for resolution of known cases in our database
    resource = MyOpinion.objects.get(full_cite)
    if resource:
        return resource
    # allow normal clustering of other citations
    return resolve_full_citation(full_cite)

resolve_citations(citations, resolve_full_citation=my_resolve)

returns (pseudo):
{
    <MyOpinion object>: [<full_cite>, <short_cite>, <id_cite>],
    <Resource object>: [<full cite>, <short cite>],
}TokenizersInternally, eyecite works by applying a list of regular expressions to the source text to convert it to a list
of tokens:In [1]: from eyecite.tokenizers import default_tokenizer

In [2]: list(default_tokenizer.tokenize("Foo v. Bar, 123 U.S. 456 (2016). Id. at 457."))
Out[2]:
['Foo',
 StopWordToken(data='v.', ...),
 'Bar,',
 CitationToken(data='123 U.S. 456', volume='123', reporter='U.S.', page='456', ...),
 '(2016).',
 IdToken(data='Id.', ...),
 'at',
 '457.']Tokens are then scanned to determine values like the citation year or case name for citation resolution.Alternate tokenizers can be substituted by providing a tokenizer instance toget_citations():from eyecite.tokenizers import HyperscanTokenizer
hyperscan_tokenizer = HyperscanTokenizer(cache_dir='.hyperscan')
cites = get_citations(text, tokenizer=hyperscan_tokenizer)test_FindTest.py includes a simplified example of using a custom tokenizer that uses modified
regular expressions to extract citations with OCR errors.eyecite ships with two tokenizers:AhocorasickTokenizer (default)The default tokenizer uses the pyahocorasick library to filter down eyecite’s list of
extractor regexes. It then performs extraction using the builtinrelibrary.HyperscanTokenizerThe alternate HyperscanTokenizer compiles all extraction regexes into a hyperscan database
so they can be extracted in a single pass. This is far faster than the default tokenizer
(exactly how much faster depends on how many citation formats are included in the target text),
but requires the optionalhyperscandependency that has limited platform support.
See the “Installation” section for hyperscan installation instructions and limitations.Compiling the hyperscan database takes several seconds, so short-running scripts may want to
provide a cache directory where the database can be stored. The directory should be writeable
only by the user:hyperscan_tokenizer = HyperscanTokenizer(cache_dir='.hyperscan')DebuggingIf you want to see what metadata eyecite is able to extract for each citation, you can usedump_citations.
This is primarily useful for developing eyecite, but may also be useful for exploring what data is available to you:In [1]: from eyecite import dump_citations, get_citations

In [2]: text="Mass. Gen. Laws ch. 1, § 2. Foo v. Bar, 1 U.S. 2, 3-4 (1999). Id. at 3. Foo, supra, at 5."

In [3]: cites=get_citations(text)

In [4]: print(dump_citations(get_citations(text), text))
FullLawCitation: Mass. Gen. Laws ch. 1, § 2. Foo v. Bar, 1 U.S. 2, 3-4 (1
  * groups
    * reporter='Mass. Gen. Laws'
    * chapter='1'
    * section='2'
FullCaseCitation: Laws ch. 1, § 2. Foo v. Bar, 1 U.S. 2, 3-4 (1999). Id. at 3. Foo, s
  * groups
    * volume='1'
    * reporter='U.S.'
    * page='2'
  * metadata
    * pin_cite='3-4'
    * year='1999'
    * court='scotus'
    * plaintiff='Foo'
    * defendant='Bar,'
  * year=1999
IdCitation: v. Bar, 1 U.S. 2, 3-4 (1999). Id. at 3. Foo, supra, at 5.
  * metadata
    * pin_cite='at 3'
SupraCitation: 2, 3-4 (1999). Id. at 3. Foo, supra, at 5.
  * metadata
    * antecedent_guess='Foo'
    * pin_cite='at 5'In the real terminal, thespan()of each extracted citation will be highlighted.
You can use thecontext_chars=30parameter to control how much text is shown before and after.InstallationInstalling eyecite is easy.poetry add eyeciteOr via pip:pip install eyeciteOr install the latest dev version from github:pip install https://github.com/freelawproject/eyecite/archive/main.zip#egg=eyeciteHyperscan installationTo useHyperscanTokenizeryou must additionally install the pythonhyperscanlibrary and its dependencies.python-hyperscan officially supports only x86 linux,though other configurations may be
possible.Hyperscan installation example on x86 Ubuntu 20.04:apt install libhyperscan-dev
pip install hyperscanHyperscan installation example on x86 Debian Buster:echo 'deb http://deb.debian.org/debian buster-backports main' > /etc/apt/sources.list.d/backports.list
apt install -t buster-backports libhyperscan-dev
pip install hyperscanHyperscan installation example with homebrew on x86 MacOS:brew install hyperscan
pip install hyperscanDeploymentUpdate CHANGES.md.Update version info inpyproject.tomlby runningpoetry version [major, minor, patch].For an automated deployment, tag the commit with vx.y.z, and push it to main.
An automated deploy and documentation update will be completed for you.For a manual deployment, run:poetry publish --buildYou will probably also need to push new documentation files to the gh-pages branch.Testingeyecite comes with a robust test suite of different citation strings that it is equipped to handle. Run these tests as follows:python3 -m unittest discover -s tests -p 'test_*.py'If you would like to create mock citation objects to assist you in writing your own local tests, import and use the following functions for convenience:from eyecite.test_factories import (
    case_citation,
    id_citation,
    supra_citation,
    unknown_citation,
)DevelopmentWhen a pull request is generated for changes from changes to eyecite, a github
workflow will automatically trigger.  The workflow, benchmark.yml will
test improvements in accuracy and speed against the current main branch.The results are committed to an artifacts branch, and an ever updating comment
in the PR comments with the output.LicenseThis repository is available under the permissive BSD license, making it easy and safe to incorporate in your own libraries.Pull and feature requests welcome. Online editing in GitHub is possible (and easy!).