Conduct Legal Research with AI: Part 5
Transforming the Library of Congress results into individual json documents contaning case information.
pythonlegaljsonscotusautomation
1 Minute, 22 Seconds
2022-05-21 14:30 +0000
Legal Research with AI: Part 5"
In the previous posts in this series, I have downloaded the data required to build the neo4j graph. In this post, I will arrange the data into a data structure that will permit me to easily create graph nodes and most importantly relationships.
The Runner Program
The raw structure of the data is organized by the results of the api requests. There are thus 80 cases per file. I want them organized by individual cases to facilitate integration with another dataset that will be detailed in the next post.
Glob the input older
The program below simply reads thedownloaded json data from a folder to create a list of file paths to read.
Modify The Case Data
It then traverses that list to find the individual case data to write to file.
Add loc_id to the Dictionary
For each case it create the loc_id key that will be used to join with another dataset.
Write to File
Finally, it writes the new case dictionary to file.
import pandas as pd
import glob
import os
import json
import numpy as np
from pprint import pprint
import re
#from neoModelAPI import NeoNodes as nn
def get_cwd():
cwd = os.getcwd()
return cwd
def get_files(cwd =os.getcwd(), input_directory = 'loc_cases'):
path = os.sep.join([cwd,input_directory])
file_list= [f for f in glob.glob(path + "**/*.json", recursive=True)]
return file_list
def load_json_data(file):
f = open (file, "r")
# Reading from file
data = json.loads(f.read())
return data
def citation_output(file_list,cwd):
outpath = os.sep.join([cwd,'loc_cited'])
for file in file_list:
data = load_json_data(file=file)
data = data['results']
#data = create_citation(data)
for result in data:
split = result['id'].split('/')
result['loc_id'] = split[4]
outfile = split[4] + '.json'
outfile = os.sep.join([outpath,outfile])
pprint(outfile)
with open(outfile, 'w') as f:
json.dump(result, f)
if __name__ == "__main__":
#neo_applified = instantiate_neo_model_api()
cwd = get_cwd()
file_list = get_files(cwd = cwd)
output_files = citation_output(file_list,cwd)