compete_jobs/common_task.py

import pandas as pd
import boto3
from datetime import datetime
import glob

from naukri.search_india import NaukriJobScraper
from naukri.jobdata_india import NaukriJobDetailScraper
from naukri.search_gulf_r import main as gulfSearch,  output_filename_csv as gulf_search_file
from naukri.jobdata_gulf_r import NaukriGulfJobDetailScraper
import time
import os

def upload_file_to_bucket(localFilePath, localFileName):
    s3 = boto3.client('s3')
    bucket_name = 'compete-syndication'
    file_path = localFilePath
    s3_key = f'naukri/{localFileName}'  
    s3.upload_file(file_path, bucket_name, s3_key)
    print(f'File "{file_path}" uploaded to S3 bucket "{bucket_name}" as "{s3_key}"')



def read_s3_file(filenameInS3):
    aws_access_key_id = 'AKIAWWHGITBE7XFXWA7U'
    aws_secret_access_key = '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'
    # bucket_name = 
    # file_key = 'naukri/test_data.csv'  
    # file_key = f'naukri/{filenameInS3}'  
    s3_bucket = 'compete-syndication'
    s3_file_key = f'naukri/{filenameInS3}'  
    session = boto3.Session(
        aws_access_key_id=aws_access_key_id,
        aws_secret_access_key=aws_secret_access_key
    )
    s3_client = session.client('s3')
    s3_object = s3_client.get_object(Bucket=s3_bucket, Key=s3_file_key)
    df = pd.read_csv(s3_object['Body'])
    print(df)
    # file_content = response['Body'].read()

    # # Print or process the file contents
    # print(file_content.decode('utf-8'))  # Assumes the file is text; adjust accordingly

def do_the_difference(today_file, last_file, column_for_diff, fresh_output, expired_output, common_output):
    today_df = pd.read_csv(today_file)
    last_file_df = pd.read_csv(last_file)
    print(today_df.shape, last_file_df.shape)
    today_df.drop_duplicates(subset=[column_for_diff], keep='first', inplace=True)
    # today_df.to_csv('unique Compete_1_09-10-2023.csv', index=False)
    last_file_df.drop_duplicates(subset=[column_for_diff], keep='first', inplace=True)
    # last_file_df.to_csv('unique Compete_1_29-09-2023.csv', index=False)
    print(today_df.shape, last_file_df.shape)
    new_df = pd.merge(today_df, last_file_df, on=column_for_diff, how='left', indicator=True,  suffixes=('', '_ignored')).query('_merge == "left_only"').drop(['_merge'], axis=1)
    new_df.to_csv(fresh_output, index=False)
    expired_df = pd.merge(last_file_df, today_df, on=column_for_diff, how='left', indicator=True,  suffixes=('', '_ignored')).query('_merge == "left_only"').drop(['_merge'], axis=1)
    expired_df.to_csv(expired_output, index=False)
    print(new_df.shape, expired_df.shape)
    common_df = pd.merge(today_df, last_file_df, on=column_for_diff, how='inner')
    print(common_df.shape)
    common_df.to_csv(common_output, index=False)

def extract_date_from_filename(filename):
    date_str = filename.split("_")[-1].replace(".csv", "")
    return datetime.strptime(date_str, "%d-%m-%Y")
    
def find_second_latest_file(folder_path, search_pattern):
    files = glob.glob(os.path.join(folder_path, search_pattern))
    files.sort(key=extract_date_from_filename, reverse=True)
    if len(files) >= 2:
        second_latest_file = files[1]
        print("Second latest file:", second_latest_file)
        return second_latest_file
    else:
        print("There are not enough files in the folder to find the second latest file.")
        return None

def run_india_scraper():
    current_date = datetime.now()
    today_date = current_date.strftime('%d-%m-%Y')
    india_search_input_file = "naukri/_industry_urls.csv"
    india_search_output_file = f"india_data/daily_search_results/search_result_india_{today_date}.csv"
    india_search_error_file = f"india_data/daily_error_folder/search_error_india_{today_date}.csv"
    india_search_stats_file = f"india_data/daily_stats_folder/stats_india_search_{today_date}.txt"
    start_time = time.time()
    scraper = NaukriJobScraper(india_search_input_file, india_search_output_file, india_search_error_file)
    scraper.scrape()
    end_time = time.time()
    duration_hours = (end_time - start_time) / 3600
    print(f"Search program took {duration_hours:.2f} hours to run.")
    with open(india_search_stats_file, "a") as stat:
        stat.write(f"Search program took {duration_hours:.2f} hours to run. \n")
    folder_path = "india_data/daily_search_results/"
    search_pattern = "search_result_india_*.csv"
    last_file = find_second_latest_file(folder_path, search_pattern)
    fresh_output = f"india_data/daily_process_folder/new_jobs_on_{today_date}.csv"
    expired_output = f"india_data/daily_upload_folder/expired_Compete_1_India_{today_date}.csv"
    common_output = f"india_data/daily_common_folder/common_data_on_{today_date}.csv"
    do_the_difference(india_search_output_file, last_file, 'jdURL', 
                      fresh_output, expired_output, common_output)
    india_detail_file = f"india_data/daily_upload_folder/Compete_1_India_{today_date}.csv"
    india_detail_error_file = f"india_data/daily_error_folder/error_on_India_detail_{today_date}.txt"
    start_time = time.time()
    scraper = NaukriJobDetailScraper(fresh_output, india_detail_file, india_detail_error_file) 
    scraper.scrape()
    end_time = time.time()
    duration_hours = (end_time - start_time) / 3600
    print(f"Jobdata program took {duration_hours:.2f} hours to run.")
    with open(f'india_data/daily_stats_folder/stats_file_of_{today_date}.txt', "a") as stat:
      stat.write(f"Jobdata program took {duration_hours:.2f} hours to run.\n")
    current_date = datetime.now()
    today_date = current_date.strftime('%d-%m-%Y')
    upload_file_to_bucket(expired_output, f"expired_Compete_1_India_{today_date}.csv" )
    upload_file_to_bucket(india_detail_file, f"Compete_1_India_{today_date}.csv" )

def run_gulf_scraper():
    gulfSearch()
    folder_path = "gulf_data/daily_search_results/"
    search_pattern = "search_result_gulf_*.csv"
    last_file = find_second_latest_file(folder_path, search_pattern)
    current_date = datetime.now()
    today_date = current_date.strftime('%d-%m-%Y')
    fresh_output = f"gulf_data/daily_process_folder/new_jobs_on_{today_date}.csv"
    expired_output = f"gulf_data/daily_upload_folder/expired_Compete_1_gulf_{today_date}.csv"
    common_output = f"gulf_data/daily_common_folder/common_data_on_{today_date}.csv"
    do_the_difference(gulf_search_file, last_file, "jdURL", fresh_output, expired_output, common_output)
    upload_file_to_bucket(expired_output, f"expired_Compete_1_Gulf_{today_date}.csv" )
    start_time = time.time()
    gulf_detail_file = f"gulf_data/daily_upload_folder/Compete_1_gulf_{today_date}.csv"
    gulf_detail_error_file = f"india_data/daily_error_folder/error_on_India_detail_{today_date}.txt"
    scraper = NaukriGulfJobDetailScraper(fresh_output, gulf_detail_file, gulf_detail_error_file)
    scraper.scrape()
    end_time = time.time()
    duration_hours = (end_time - start_time) / 3600
    print(f"Jobdata program took {duration_hours:.2f} hours to run.")
    with open(f'gulf_data/daily_stats_folder/stats_file_of_{today_date}.txt', "a") as stat:
        stat.write(f"Jobdata program took {duration_hours:.2f} hours to run.\n")
    upload_file_to_bucket(gulf_detail_file, f"Compete_1_Gulf_{today_date}.csv" )


if __name__ == "__main__":
    print("Choose which function to run:")
    print("1 for India Scraper")
    print("2 for Gulf scraper")
    choice = input("Enter your choice (1 or 2): ")
    if choice == "1":
        run_india_scraper()
    elif choice == "2":
        run_gulf_scraper()
    else:
        print("Invalid choice. Please enter 1 or 2.")