corpus-base 0.1.2

Add justice, decision, citation, voting, and opinion tables to pre-existing corpus-pax database.

Corpus-Base

flowchart LR

subgraph main
  local(local machine)--setup corpus-base tables--->db[(db from corpus-pax)]
end
subgraph github/corpus
  folder1(justices)--data via api---local
  folder2(decisions/sc)--data via local copy---local
  folder3(decisions/legacy)--data via local copy---local
end

With the database used in corpus-pax, create additional tables related to decisions of the Philippine Supreme Court.

>>> from corpus_base import build_sc_tables
>>> build_sc_tables(c)

This creates additional tables associated with:

1. Justices
2. Decisions
   • Citations
   • Votelines
   • Titletags
   • Opinions

>>> from corpus_base import init_sc_cases
>>> init_sc_cases(c, test_only=10)

Parse through a locally downloaded repository to populate tables. Since there are thousands of cases, can limit the number of downloads via the test_only function attribute. The path location of the downloaded repository is hard-coded since this package is intended to be run locally. Instructions for downloading and updating the repository are discussed elsewhere.

Build from scratch

>>> from corpus_base import setup_base_db
>>> setup_base_db('x.db') # creates the database in present working directory

Limited to 3.11.0

See citation-report on reason why Python version is limited to 3.11.0 in both:

1. pyproject.toml; and
2. github workflow

Related features

Insert records

Can add all pydantic validated records from the local copy of justices to the database.

>>> from corpus_base import Justice
>>> Justice.init_justices_tbl(c) # c = instantiated Connection
<Table justices_tbl (first_name, last_name, suffix, full_name, gender, id, alias, start_term, end_term, chief_date, birth_date, retire_date, inactive_date)>

Clean raw ponente string

Each ponente name stored in decisions_tbl of the database has been made uniform, e.g.:

>>> from corpus_base import RawPonente
>>> RawPonente.clean("REYES , J.B.L, Acting C.J.") # sample name 1
"reyes, j.b.l."
>>> RawPonente.clean("REYES, J, B. L. J.") # sample name 2
"reyes, j.b.l."

We can see most common names in the ponente field and the covered dates, e.g. from 1954 to 1972 (dates found in the decisions), there have been 1053 decisions marked with jbl (as cleaned):

>>> from corpus_base.helpers import most_popular
>>> [i for i in most_popular(c, db)] # excluding per curiams and unidentified cases
[
    ('1994-07-04', '2017-08-09', 'mendoza', 1297), # note multiple personalities named mendoza, hence long range from 1994-2017
    ('1921-10-22', '1992-07-03', 'paras', 1287), # note multiple personalities named paras, hence long range from 1921-1992
    ('2009-03-17', '2021-03-24', 'peralta', 1243),
    ('1998-06-18', '2009-10-30', 'quisumbing', 1187),
    ('1999-06-28', '2011-06-02', 'ynares-santiago', 1184),
    ('1956-04-28', '2008-04-04', 'panganiban', 1102),
    ('1936-11-19', '2009-11-05', 'concepcion', 1058), # note multiple personalities named concepcion, hence long range from 1936-2009
    ('1954-07-30', '1972-08-18', 'reyes, j.b.l.', 1053),
    ('1903-11-21', '1932-03-31', 'johnson', 1043),
    ('1950-11-16', '1999-05-23', 'bautista angelo', 1028), # this looks like bad data
    ('2001-11-20', '2019-10-15', 'carpio', 1011),
    ...
]

Isolate active justices on date

When selecting a ponente or voting members, create a candidate list of justices based on date:

>>> from corpus_base import Justice
>>> Justice.get_active_on_date(c, 'Dec. 1, 1995') # target date
[
    {
        'id': 137,
        'surname': 'panganiban',
        'alias': None,
        'start_term': '1995-10-05', # since start date is greater than target date, record is included
        'inactive_date': '2006-12-06',
        'chief_date': '2005-12-20'
    },
    {
        'id': 136,
        'surname': 'hermosisima',
        'alias': 'hermosisima jr.',
        'start_term': '1995-01-10',
        'inactive_date': '1997-10-18',
        'chief_date': None
    },
]

Designation as chief or associate

Since we already have candidates, we can cleaning desired option to get the id and designation:

>>> from corpus_base import RawPonente
>>> RawPonente.clean('Panganiban, Acting Cj')
'panganiban'
>>> Justice.get_justice_on_date(c, '2005-09-08', 'panganiban')
{
    'id': 137,
    'surname': 'Panganiban',
    'start_term': '1995-10-05',
    'inactive_date': '2006-12-06',
    'chief_date': '2005-12-20',
    'designation': 'J.' # note variance
}

Note that the raw information above contains 'Acting Cj' and thus the designation is only 'J.'

At present we only track 'C.J.' and 'J.' titles.

With a different date, we can get the 'C.J.' designation.:

>>> Justice.get_justice_on_date('2006-03-30', 'panganiban')
{
    'id': 137,
    'surname': 'Panganiban',
    'start_term': '1995-10-05',
    'inactive_date': '2006-12-06',
    'chief_date': '2005-12-20',
    'designation': 'C.J.' # corrected
}

View chief justice dates

>>> from corpus_base import Justice
>>> Justice.view_chiefs(c)
[
    {
        'id': 178,
        'last_name': 'Gesmundo',
        'chief_date': '2021-04-05',
        'max_end_chief_date': None,
        'actual_inactive_as_chief': None,
        'years_as_chief': None
    },
    {
        'id': 162,
        'last_name': 'Peralta',
        'chief_date': '2019-10-23',
        'max_end_chief_date': '2021-04-04',
        'actual_inactive_as_chief': '2021-03-27',
        'years_as_chief': 2
    },
    {
        'id': 163,
        'last_name': 'Bersamin',
        'chief_date': '2018-11-26',
        'max_end_chief_date': '2019-10-22',
        'actual_inactive_as_chief': '2019-10-18',
        'years_as_chief': 1
    },
    {
        'id': 160,
        'last_name': 'Leonardo-De Castro',
        'chief_date': '2018-08-28',
        'max_end_chief_date': '2018-11-25',
        'actual_inactive_as_chief': '2018-10-08',
        'years_as_chief': 0
    }...
]