Data-Science/classify.py at main · tirgue/Data-Science · GitHub

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import csv, json, sys, datetime
from clearDatas import extract_mails

def createDate(data):
    year = int(data.get('Date')[0:4])
    month = int(data.get('Date')[5:7])
    day = int(data.get('Date')[8:10])
    hour = int(data.get('Date')[11:13])
    minute = int(data.get('Date')[14:16])
    return datetime.datetime(year, month, day, hour, minute)

def retrieve_sending_month(date):
    return date.strftime("%b")

def retrieve_sending_day(date):
    return date.strftime("%a")

def retrieve_sending_time(date):
    if date.hour > 22 or date.hour == 0:
        return "bet-22-00"
    if date.hour > 20:
        return "bet-20-22"
    if date.hour > 18:
        return "bet-18-20"
    if date.hour > 14:
        return "bet-14-18"
    if date.hour > 11:
        return "bet-11-14"
    if date.hour > 8:
        return "bet-08-11"
    if date.hour > 5:
        return "bet-05-08"
    if date.hour > 0:
        return "bet-00-05"

def retrieve_long_subject(data):
    # Moyenne de lettres par mot : 4.65
    # On estime qu'un sujet est long au delà d'une dizaine de mots (10 * 4.65 = 46)
    # Donc 46 caractères est la limite entre un sujet long et court
    return "long" if len(data.get('Subject')) > 46 else "short"

def retrieve_content_size(data):
    if len(data.get('content')) < 150:
        return "small"
    elif len(data.get('content')) > 300:
        return "high"
    else:
        return "medium"

def retrieve_formal(data):
    with open("formules.txt", "r") as file:
        content = data.get('content').lower()
        for formule in file:
            if formule in content:
                return "yes"

    return "no"

def retrieve_time_until_answer(data_r, data_s):
    respondingDate = createDate(data_r)
    sendingDate = createDate(data_s)
    delta = respondingDate - sendingDate
    if delta < datetime.timedelta():
        return -1

    return str(delta.total_seconds()/3600)

if __name__ == "__main__":
    maxInt = sys.maxsize
    while True:
        try:
            csv.field_size_limit(maxInt)
            break
        except OverflowError:
            maxInt = int(maxInt/10)

    try:
        filename = sys.argv[1]
        with open(filename, "r") as file:
            print("Loading...")
            datas = csv.DictReader(file)
            datas = list(datas)
    except :
        print("*** Invalid filename ***\nUsage : python classify.py FILENAME")
        exit(-1)

    emails = []

    print("Computing...")
    for data in datas:
        subject = data.get("Subject")
        if subject.startswith("Re:"):
            sender = extract_mails(data.get('From'))
            d_subject = data.get("Subject")[4:]
            for d in datas:
                if d.get("Subject")  == d_subject:
                    receivers = extract_mails(d.get("To"))
                    if sender[0] in receivers:
                        time_until_answer = retrieve_time_until_answer(data, d)

                        if time_until_answer != -1:
                            sendingDate = createDate(d)
                            sending_month = retrieve_sending_month(sendingDate)
                            sending_day = retrieve_sending_day(sendingDate)
                            sending_time = retrieve_sending_time(sendingDate)
                            long_subject = retrieve_long_subject(d)
                            content_size = retrieve_content_size(d)
                            formal = retrieve_formal(d)

                            email = {
                                "sending_month" : sending_month,
                                "sending_day" : sending_day,
                                "sending_time" : sending_time,
                                "long_subject" : long_subject,
                                "content_size" : content_size,
                                "formal" : formal,
                                "time_until_answer" : time_until_answer,
                            }
                            emails.append(email)

                            break

    output = {
        "emails" : emails
    }

    print("Writing...")
    outputFile = open("classesDatas.json", "w")
    json.dump(output, outputFile)

    print("Done")