selector.py

import os

import re

import pandas as pd

from openpyxl import Workbook

from reportlab.lib.pagesizes import letter

from reportlab.lib import colors

from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer

from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle

from reportlab.platypus import PageBreak

from validate_email_address import validate_email


# Function to extract sentences containing key phrases, emails, and phone numbers

def extract_sentences(username, input_csv, output_pdf, target_phrases):
    username = username.strip("@")  # Remove "@" symbol from username

    input_csv_path = f"Collection/{username}/{username}_messages.csv"

    output_pdf_path = f"Collection/{username}/{username}_keyphrase_report.pdf"

    if not os.path.exists(input_csv_path):
        print(f"CSV file not found: {input_csv_path}")

        return

    # Read the CSV file into a DataFrame

    df = pd.read_csv(input_csv_path, encoding='utf-8')

    # Create a PDF document

    doc = SimpleDocTemplate(output_pdf_path, pagesize=letter)

    story = []

    # Define paragraph styles

    styles = getSampleStyleSheet()

    title_style = styles["Title"]

    normal_style = styles["Normal"]

    normal_style.leading = 14

    normal_style.alignment = 0  # Left alignment 

    citation_style = ParagraphStyle(name='CitationStyle', parent=normal_style)

    citation_style.leading = 6  # Decrease font size to 6

    # Define subheading style after normal_style

    subheading_style = styles["Heading2"]

    # Add the title to the PDF

    title = Paragraph("Key Phrase Extraction Report", title_style)

    story.append(title)

    story.append(Spacer(1, 12))

    # Create a regex pattern for each target phrase

    target_patterns = [re.compile(r'\b' + re.escape(phrase) + r'\b', re.IGNORECASE) for phrase in target_phrases]

    # Initialize variables for subheadings

    email_subheading_added = False

    phone_subheading_added = False

    other_subheading_added = False

    # Email pattern

    email_pattern = r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,7}\b'

    # Iterate through messages and extract sentences

    for index, row in df.iterrows():

        message = str(row['Text'])  # Convert to string to handle non-string values

        url = row['Message URL']

        # Remove URLs from the message text

        message = re.sub(r'http\S+', '', message)

        sentences = re.split(r'(?<=[.!?])\s+', message)

        for sentence in sentences:

            for pattern in target_patterns:

                if re.search(pattern, sentence):

                    # Check for subheadings and add them if not added yet

                    if not email_subheading_added:
                        story.append(Paragraph("Potential Email Addresses", subheading_style))

                        email_subheading_added = True

                    if not phone_subheading_added:
                        story.append(Paragraph("Potential Phone Numbers", subheading_style))

                        phone_subheading_added = True

                    if not other_subheading_added:
                        story.append(Paragraph("Other Content of Interest", subheading_style))

                        other_subheading_added = True

                    # Highlight target phrases

                    highlighted_sentence = re.sub(pattern, r'<font color="red">\g<0></font>', sentence)

                    story.append(Paragraph(highlighted_sentence, normal_style))

                    # Add URL end-note citation with size 6 font

                    citation = Paragraph(f"<font size='6'><b>Source:</b> <a href='{url}'>{url}</a></font>",
                                         citation_style)

                    story.append(citation)

                    # Add a gap between extracted posts/URLs

                    story.append(Spacer(1, 12))

        # Find and highlight valid email addresses

        email_addresses = re.findall(email_pattern, message)

        for email in email_addresses:

            if validate_email(email):  # Check email validity

                # Check for the email subheading and add it if not added yet

                if not email_subheading_added:
                    story.append(Paragraph("Potential Email Addresses", subheading_style))

                    email_subheading_added = True

                email_pattern = re.compile(re.escape(email), re.IGNORECASE)

                highlighted_email = re.sub(email_pattern, r'<font color="green">\g<0></font>', email)

                context_with_email = message.replace(email, highlighted_email)

                story.append(Paragraph(context_with_email, normal_style))

                # Add URL end-note citation with size 6 font and bold "Source:"

                email_url = f"<font size='6'><b>Source:</b> <a href='{url}'>{url}</a></font>"

                story.append(Paragraph(email_url, citation_style))

                # Add a gap between extracted email addresses

                story.append(Spacer(1, 12))

        # Find and highlight phone numbers

        phone_numbers = re.findall(r'\b\d{7,15}\b', message)  # Match phone numbers with 7 to 15 digits

        for phone in phone_numbers:

            # Check for the phone subheading and add it if not added yet

            if not phone_subheading_added:
                story.append(Paragraph("Potential Phone Numbers", subheading_style))

                phone_subheading_added = True

            phone_pattern = re.compile(re.escape(phone), re.IGNORECASE)

            highlighted_phone = re.sub(phone_pattern, r'<font color="blue">\g<0></font>', phone)

            context_with_phone = message.replace(phone, highlighted_phone)

            story.append(Paragraph(context_with_phone, normal_style))

            # Add URL end-note citation with size 6 font and bold "Source:"

            phone_url = f"<font size='6'><b>Source:</b> <a href='{url}'>{url}</a></font>"

            story.append(Paragraph(phone_url, citation_style))

            # Add a gap between extracted phone numbers

            story.append(Spacer(1, 12))

    # Create the PDF

    doc.build(story)

    print(f"Key phrase extraction report saved to {output_pdf_path}")


if __name__ == "__main__":
    target_phrases = [

        # List of target phrases here

        "where I work", "where I live", "where I grew up", "my wife", "my husband", "my children", "my kids", "my kid",

        "my child", "my sibling", "my siblings", "my significant other", "my SO", "my partner", "getting married",
        "getting engaged",

        "got married", "got engaged", "got divorced", "getting divorced", "my family", "my spouse", "my little ones",
        "my little one",

        "our children", "our kid", "our son", "our daughter", "my son", "my daughter", "my birthday", "born in",
        "my phone number",

        "my email", "my address", "my home address", "my house", "my school", "my university", "my job",
        "my profession", "work at",

        "new job", "job interview", "to school at", "to university at", "just visited", "went down to", "just visiting",
        "going down to",

        "went up to", "my hometown", "living in", "live in", "moved to", "my home", "my mother", "my father",
        "my stepmother", "my stepfather",

        "where I work", "where I live", "where I grew up", "my grandchildren", "my grandchild", "my grandson",
        "my granddaughter", "my brother",

        "my sister", "my nephew", "my niece", "my uncle", "my aunty", "my parents",

    ]

    # Get the target username from the user

    target_username = input("Enter the target username (with @): ")

    # Run the extraction and PDF generation

    extract_sentences(target_username, "input.csv", target_username + "_keyphrase_report.pdf", target_phrases)

# Ask if the user wants to return to the launcher

launcher = input('Do you want to return to the launcher? (y/n)')

if launcher == 'y':
    print('Restarting...')

    exec(open("launcher.py").read())