structure_graphs/large_corpus.py

'''
Development Notes
the program temporarily works with word.json to test the viability of
working with large corpus organized as json. 

'''
import json
from pprint import pprint

def parse_json(filename):
    data = json.load(open(filename,'r'))
    return data

def save_json(data):
    with open('corpus/corpus_cn.json','w', encoding='utf-8') as w_file:
        json.dump(data,w_file, indent=4, ensure_ascii = False)

def intify(data):
    for i in data:
        print("converting to int")
        i["strokes"] = int(i["strokes"]) 
        print(type(i["strokes"]))
    return data

# data sciency methods are not all that interesting, cautiously stay away. 
    # think of what do people do with a dictionary
    # look for a radical; return results with that radical; like Bok.
    # some general usages of using dictionary   

# def remix_lookup():

# def radical_lookup():

# def stroke_lookup():

# save corpus as separate file to work with 


# browse methods to parse large quantity of corpus 

if __name__== "__main__":
    parsed_json = parse_json(filename="corpus/corpus_cn.json")
    intified_data = intify(parsed_json)
    save_json(data = intified_data)