Conduct Legal Research with AI: Part 5

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)