datewise_textual_transactions_count.py

#============================================================================================================#
#*******************************   HOW TO RUN?  ************************************************************ #
# python3 datewise_textual_transactions_count.py <path to the input json file>  <path to the output file>    #
#*********************************************************************************************************** #
# Example:                                                                                                   #
#python3 datewise_textual_transactions_count.py /Users/rajattan/venmo/dummy.json ./transactions_date_wise.txt#
#============================================================================================================#
import re
import sys
import json
import nltk
from nltk import tokenize

transactions = 0
textual_transactions = 0
transactions_date_wise = {}
pattern = re.compile("[A-Za-z0-9]+")

def tokenize_word_text(text):
    tokens = nltk.word_tokenize(text)
    tokens = [token.strip() for token in tokens]
    return tokens

"""
Remove blancs on words
"""
def remove_blanc(tokens):
    tokens = [token.strip() for token in tokens]
    return(tokens)



if(len(sys.argv) != 3):
    print("==========================================================================")
    print("SORRY!! Please provide the path to the INPUT json file and the OUTPUT file")
    print("==========================================================================")
    print("Example: python3 datewise_transactions_count.py ./dummy.json ./output.txt ")
    print("==========================================================================")
    sys.exit()



f = open(sys.argv[1])
outputfile = open(sys.argv[2],"w")

for line in f:
    data = json.loads(line)
    transactions = transactions + 1
    try:

        if(data is None or data['created_time'] is None):
            continue
        datetime = str(data['created_time'])
        date = datetime.split("T")
        if(data is None or data['message'] is None or data['message'] == ""):
            continue
        msg = str(data['message'])
        msg = msg.strip()
        tokens = nltk.word_tokenize(msg)
        tokens = remove_blanc(tokens)
        string = ""
        for t in tokens:
            t = re.sub('[\W_]+', '', t)
            if(not (t == " ")):
                string = string + t
        if(date[0] not in transactions_date_wise):
            transactions_date_wise[date[0]] = 0
        if(string != "" and pattern.search(string)):
            transactions_date_wise[date[0]] = transactions_date_wise[date[0]] + 1
            textual_transactions = textual_transactions + 1
    except:
        continue        
f.close()

outputfile.write("DATE #TEXTUAL_TRANSACTIONS \n")
for k,v in sorted(transactions_date_wise.items()):
    outputfile.write(str(k) + " " + str(v) + "\n")

outputfile.write("TOTAL NUMBER OF TRANSACTIONS ARE :" + str(transactions))
outputfile.write("\nTOTAL NUMBER OF TEXTUAL TRANSACTIONS IN ENGLISH ARE :" + str(textual_transactions))
outputfile.close()