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total_emoji_2018.py
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#============================================================================================================#
#******************************* HOW TO RUN? ************************************************************ #
# python3 total_emoji_2018.py <path to the input json file> <path to the output file> #
#*********************************************************************************************************** #
# Example: #
#python3 total_emoji_2018.py /Users/rajattan/venmo/dummy.json ./output.txt #
#============================================================================================================#
import re
import sys
import json
import nltk
import os
import time
import json
import nltk
import emoji
import pickle
import os.path
import numpy as np
import pandas as pd
from nltk import tokenize
#===============================================================#
BATCH = 10000000
#===============================================================#
current = 0
numbatch = 0
transactions = 0
#===============================================================#
cnt = 0
sender = {}
receiver = {}
keywords = set()
stopwords = set()
interjections = set()
date_category_stat = {}
date_personal_stat = {}
adult = set()
health = set()
dag = set()
race = set()
politics = set()
crime = set()
relation = set()
location = set()
#===============================================================#
SENDER_FILE = "checkpoint/sender.txt"
RECEIVER_FILE = "checkpoint/receiver.txt"
CHECKPOINT_FILE = "checkpoint/current.txt"
PATH_TO_STOPWORDS_LIST = "data/STOPWORDS.txt"
DATECAT_FILE = "checkpoint/date_category_stat.txt"
DATEPER_FILE = "checkpoint/date_personal_stat.txt"
PATH_TO_KEYWORDS_LIST = "data/UNIQ_KEYWORDS_LIST.txt"
PATH_TO_INTERJECTIONS_LIST = "data/INTERJECTIONS.txt"
PATH_TO_ADULT_EMOJI = "Emojis/Adult.txt"
PATH_TO_HEALTH_EMOJI = "Emojis/Health.txt"
PATH_TO_DAG_EMOJI = "Emojis/DAG.txt"
PATH_TO_RACE_EMOJI = "Emojis/Race.txt"
PATH_TO_POLITICS_EMOJI = "Emojis/Politics.txt"
PATH_TO_CRIME_EMOJI = "Emojis/Violence-Crime.txt"
PATH_TO_RELATION_EMOJI = "Emojis/Relations.txt"
PATH_TO_LOCATION_EMOJI = "Emojis/Location.txt"
#===============================================================#
pattern = re.compile(r"(.)\1{2,}")
pattern_rm1 = re.compile(r"(.)\1{1,}")
english_ch = re.compile("[A-Za-z0-9]+")
#===============================================================#
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 emoji.py ./dummy.json ./output.txt ")
print("==========================================================================")
sys.exit()
f = open(sys.argv[1])
if(os.path.exists(CHECKPOINT_FILE)):
with open(CHECKPOINT_FILE, "rb") as myFile:
current = pickle.load(myFile)
print("RESUMING FROM " + str(current))
if(current > 0):
dateper = DATEPER_FILE
with open(dateper, "rb") as myFile:
date_personal_stat = pickle.load(myFile)
if(len(date_personal_stat) == 0): # or len(sender) == 0 or len(receiver) == 0):
print("===================================================================")
print("****** COULD NOT SUCCESSFULLY LOAD THE CONTENTS USING PICKLE.******")
print("*** YOU NEED TO RECOMPUTE THINGS AGAIN. ***")
print("*** PLEASE remove the file checkpoint/current.txt and re-run.***")
print("===================================================================")
sys.exit()
else:
print("=========================================================")
print(" CHECKPOINT FILES AND DICTIONARIES LOADED SUCCESSFULLY!!!")
print("=========================================================")
#===============================================================#
"""
Creating stopwords set
"""
with open(PATH_TO_STOPWORDS_LIST,'r') as fp:
for l in fp:
stopwords.add(l.strip())
#===============================================================#
"""
Creating interjections set
"""
with open(PATH_TO_INTERJECTIONS_LIST,'r') as fp:
for l in fp:
interjections.add(l.strip())
#===================================================================================#
# A - ALL | AL - Average Length | C - CRYPTIC | ET - Emoji + Text | OE - Only Emoji #
# NC - Non Cryptic | L1 - 1-5 words | L2 - 6 to 10 words | L3 - 11 to 20 | #
# L4 - 21 to 30 | L5 - 31 to 50 | L6 - 50+ #
# E - English
#===================================================================================#
userfields = ['A']
#===================================================================================#
'''
Check if a token is an emoji
'''
def is_emoji(word):
if any(char in emoji.UNICODE_EMOJI for char in word):
return True
return False
#===================================================================================#
"""
Convert all letters to lower or upper case (common : lower case)
"""
def convert_letters(tokens, style = "lower"):
if (style == "lower"):
return [token.lower() for token in tokens]
else:
return [token.upper() for token in tokens]
#===============================================================#
"""
Eliminate all continuous duplicate characters more than twice
"""
def reduce_lengthening(tokens):
return [pattern.sub(r"\1\1", token) for token in tokens]
#===============================================================#
"""
Eliminate all continuous duplicate characters more than once
"""
def reduce_lengthening_rm1(tokens):
return [pattern_rm1.sub(r"\1", token) for token in tokens]
#===============================================================#
"""
Remove all digits and special characters
"""
def remove_special(tokens):
return [re.sub("(\\d|\\W)+", " ", token) for token in tokens]
#===============================================================#
"""
Remove blancs on words
"""
def remove_blanc(tokens):
return [token.strip() for token in tokens]
#===============================================================#
"""
Stopwords Removal
"""
def remove_stopwords(tokens):
return [token for token in tokens if token not in stopwords]
#===============================================================#
"""
Stopwords Removal
"""
def remove_interjections(tokens):
return [token for token in tokens if token not in interjections]
#===============================================================#
"""
Preprocessing Work
"""
def preprocessing(origtokens):
tokens = remove_blanc(origtokens)
tokens = reduce_lengthening(tokens)
return tokens
#===============================================================#
"""
More Preprocessing Work
"""
def preprocessing_cntd(tokens):
tokens = remove_special(tokens)
tokens = [t for t in tokens if len(t) != 0]
return tokens
#===============================================================#
with open(PATH_TO_KEYWORDS_LIST,'r') as fp:
for l in fp:
keywords.add(''.join(convert_letters(l.strip())))
#===============================================================#
with open(PATH_TO_ADULT_EMOJI,'r') as fp:
for l in fp:
adult.add(l.strip())
#===============================================================#
with open(PATH_TO_HEALTH_EMOJI,'r') as fp:
for l in fp:
health.add(l.strip())
#===============================================================#
with open(PATH_TO_DAG_EMOJI,'r') as fp:
for l in fp:
dag.add(l.strip())
#===============================================================#
with open(PATH_TO_RACE_EMOJI,'r') as fp:
for l in fp:
race.add(l.strip())
#===============================================================#
with open(PATH_TO_POLITICS_EMOJI,'r') as fp:
for l in fp:
politics.add(l.strip())
#===============================================================#
with open(PATH_TO_CRIME_EMOJI,'r') as fp:
for l in fp:
crime.add(l.strip())
#===============================================================#
with open(PATH_TO_RELATION_EMOJI,'r') as fp:
for l in fp:
relation.add(l.strip())
#===============================================================#
with open(PATH_TO_LOCATION_EMOJI,'r') as fp:
for l in fp:
location.add(l.strip())
#===============================================================#
#===============================================================#
# MAIN FLOW #
#===============================================================#
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()
for line in f:
data = json.loads(line)
transactions = transactions + 1
try:
#==============================#
### Checks for Invalid JSONs ###
#==============================#
if(data is None or data['created_time'] is None):
continue
if(data['message'] is None or data['message'] == ""):
continue
if('actor' not in data or 'username' not in data['actor'] or 'transactions' not in data or data['transactions'] is None or 'target' not in data['transactions'][0] or 'username' not in data['transactions'][0]['target']):
continue
username = data['actor']['username']
tusername = data['transactions'][0]['target']['username']
note = str(data['message'])
origtokens = nltk.word_tokenize(note)
tokens_partial = preprocessing(origtokens)
only_emojis = 0
for t in tokens_partial:
if(emoji.emoji_count(t) == len(t)):
only_emojis += 1
break
if(only_emojis == 0):
continue
datetim = str(data['created_time'])
date = datetim.split("T")
month = date[0][2:7]
if(date[0] not in date_personal_stat):
date_personal_stat[date[0]] = {col:0 for col in userfields}
date_personal_stat[date[0]]['A'] += 1
if cnt == (BATCH-1):
current = transactions
cnt = -1
strcurrent = "." + str(current)
dateper = DATEPER_FILE
with open(CHECKPOINT_FILE, "wb") as myFile:
pickle.dump(current, myFile,protocol=pickle.HIGHEST_PROTOCOL)
with open(dateper, "wb") as myFile:
pickle.dump(date_personal_stat, myFile,protocol=pickle.HIGHEST_PROTOCOL)
send = SENDER_FILE + strcurrent
with open(send, "wb") as myFile:
pickle.dump(sender, myFile,protocol=pickle.HIGHEST_PROTOCOL)
recv = RECEIVER_FILE + strcurrent
with open(recv, "wb") as myFile:
pickle.dump(receiver, myFile,protocol=pickle.HIGHEST_PROTOCOL)
df_stat = pd.DataFrame.from_dict(date_personal_stat, orient='index', columns=userfields)
df_stat = df_stat.rename_axis('Date').reset_index()
df_stat.to_csv(sys.argv[2] + "per.output", index=False)
outputfile = open(sys.argv[2],"w")
outputfile.write("TRANSACTIONS PROCESSED TILL NOW = " + str(current) + "\n")
scnt=-1
for k,v in sender.items():
if(v is None):
continue
scnt = scnt + 1
s = ""
try:
s = str(scnt) + "|"
if('joined' in sender[k]):
s = s + str(sender[k]['joined'])
s = s + "|"
if('dates' in sender[k]):
for kk,vv in sender[k]['dates'].items():
s = s + str(kk)
for kkk,vvv in sorted(vv.items()):
s = s + "," + str(kkk) + ":" + str(vvv)
s = s + ";"
s = s + "|"
if(k in receiver and 'dates' in receiver[k]):
for kk,vv in receiver[k]['dates'].items():
s = s + str(kk)
for kkk,vvv in sorted(vv.items()):
s = s + "," + str(kkk) + ":" + str(vvv)
s = s + ";"
outputfile.write(s + "\n")
except:
continue
outputfile.close()
outputfile1 = open(sys.argv[2] + "recv.output","w")
rcnt=-1
for k,v in receiver.items():
if(v is None or k in sender):
continue
rcnt = rcnt + 1
s = ""
try:
s = str(rcnt) + "|"
if('joined' in receiver[k]):
s = s + str(receiver[k]['joined'])
s = s + "|"
if('dates' in receiver[k]):
for kk,vv in receiver[k]['dates'].items():
s = s + str(kk)
for kkk,vvv in sorted(vv.items()):
s = s + "," + str(kkk) + ":" + str(vvv)
s = s + ";"
outputfile1.write(s + "\n")
except:
continue
outputfile1.close()
sender.clear()
receiver.clear()
cnt = cnt + 1
except:
continue
f.close()
strcurrent = "." + str(transactions)
datecat = DATECAT_FILE
dateper = DATEPER_FILE
with open(CHECKPOINT_FILE, "wb") as myFile:
pickle.dump(transactions, myFile,protocol=pickle.HIGHEST_PROTOCOL)
with open(dateper, "wb") as myFile:
pickle.dump(date_personal_stat, myFile,protocol=pickle.HIGHEST_PROTOCOL)
send = SENDER_FILE + strcurrent
with open(send, "wb") as myFile:
pickle.dump(sender, myFile,protocol=pickle.HIGHEST_PROTOCOL)
recv = RECEIVER_FILE + strcurrent
with open(recv, "wb") as myFile:
pickle.dump(receiver, myFile,protocol=pickle.HIGHEST_PROTOCOL)
df_stat = pd.DataFrame.from_dict(date_personal_stat, orient='index', columns=userfields)
df_stat = df_stat.rename_axis('Date').reset_index()
df_stat.to_csv(sys.argv[2] + "per.output", index=False)
outputfile = open(sys.argv[2],"w")
outputfile.write("TRANSACTIONS PROCESSED TILL NOW = " + str(transactions) + "\n")
scnt=-1
for k,v in sender.items():
if(v is None):
continue
scnt = scnt + 1
s = ""
try:
s = str(scnt) + "|"
if('joined' in sender[k]):
s = s + str(sender[k]['joined'])
s = s + "|"
if('dates' in sender[k]):
for kk,vv in sender[k]['dates'].items():
s = s + str(kk)
for kkk,vvv in sorted(vv.items()):
s = s + "," + str(kkk) + ":" + str(vvv)
s = s + ";"
s = s + "|"
if(k in receiver and 'dates' in receiver[k]):
for kk,vv in receiver[k]['dates'].items():
s = s + str(kk)
for kkk,vvv in sorted(vv.items()):
s = s + "," + str(kkk) + ":" + str(vvv)
s = s + ";"
outputfile.write(s + "\n")
except:
continue
outputfile.close()
outputfile1 = open(sys.argv[2] + "recv.output","w")
outputfile1.write("TRANSACTIONS PROCESSED TILL NOW = " + str(transactions) + "\n")
rcnt=-1
for k,v in receiver.items():
if(v is None or k in sender):
continue
rcnt = rcnt + 1
s = ""
try:
s = str(rcnt) + "|"
if('joined' in receiver[k]):
s = s + str(receiver[k]['joined'])
s = s + "|"
if('dates' in receiver[k]):
for kk,vv in receiver[k]['dates'].items():
s = s + str(kk)
for kkk,vvv in sorted(vv.items()):
s = s + "," + str(kkk) + ":" + str(vvv)
s = s + ";"
outputfile1.write(s + "\n")
except:
continue
outputfile1.close()