172 lines
8.2 KiB
Python
172 lines
8.2 KiB
Python
import pandas as pd
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import boto3
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from datetime import datetime
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import glob
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from naukri.search_india import NaukriJobScraper
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from naukri.jobdata_india import NaukriJobDetailScraper
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from naukri.search_gulf_r import main as gulfSearch, output_filename_csv as gulf_search_file
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from naukri.jobdata_gulf_r import NaukriGulfJobDetailScraper
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import time
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import os
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import sys
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def upload_file_to_bucket(localFilePath, localFileName, today_date):
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s3 = boto3.client('s3')
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bucket_name = 'compete-syndication'
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file_path = localFilePath
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s3_key = f'naukri/{today_date}/{localFileName}'
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s3.upload_file(file_path, bucket_name, s3_key)
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print(f'File "{file_path}" uploaded to S3 bucket "{bucket_name}" as "{s3_key}"')
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def read_s3_file(filenameInS3):
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aws_access_key_id = 'AKIAWWHGITBE7XFXWA7U'
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aws_secret_access_key = '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'
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# bucket_name =
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# file_key = 'naukri/test_data.csv'
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# file_key = f'naukri/{filenameInS3}'
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s3_bucket = 'compete-syndication'
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s3_file_key = f'naukri/{filenameInS3}'
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session = boto3.Session(
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aws_access_key_id=aws_access_key_id,
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aws_secret_access_key=aws_secret_access_key
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)
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s3_client = session.client('s3')
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s3_object = s3_client.get_object(Bucket=s3_bucket, Key=s3_file_key)
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df = pd.read_csv(s3_object['Body'])
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print(df)
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# file_content = response['Body'].read()
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# # Print or process the file contents
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# print(file_content.decode('utf-8')) # Assumes the file is text; adjust accordingly
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def do_the_difference(today_file, last_file, column_for_diff, fresh_output, expired_output, common_output):
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today_df = pd.read_csv(today_file)
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last_file_df = pd.read_csv(last_file)
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print(today_df.shape, last_file_df.shape)
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today_df.drop_duplicates(subset=[column_for_diff], keep='first', inplace=True)
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# today_df.to_csv('unique Compete_1_09-10-2023.csv', index=False)
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last_file_df.drop_duplicates(subset=[column_for_diff], keep='first', inplace=True)
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# last_file_df.to_csv('unique Compete_1_29-09-2023.csv', index=False)
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print(today_df.shape, last_file_df.shape)
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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)
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new_df.to_csv(fresh_output, index=False)
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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)
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expired_df.to_csv(expired_output, index=False)
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print(new_df.shape, expired_df.shape)
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common_df = pd.merge(today_df, last_file_df, on=column_for_diff, how='inner')
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print(common_df.shape)
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common_df.to_csv(common_output, index=False)
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def extract_date_from_filename(filename):
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date_str = filename.split("_")[-1].replace(".csv", "")
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return datetime.strptime(date_str, "%d-%m-%Y")
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def find_second_latest_file(folder_path, search_pattern):
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files = glob.glob(os.path.join(folder_path, search_pattern))
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files.sort(key=extract_date_from_filename, reverse=True)
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if len(files) >= 2:
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second_latest_file = files[1]
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print("Second latest file:", second_latest_file)
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return second_latest_file
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else:
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print("There are not enough files in the folder to find the second latest file.")
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return None
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def run_india_scraper(today_date):
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# current_date = datetime.now()
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# today_date = current_date.strftime('%d-%m-%Y')
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india_search_input_file = "naukri/_industry_urls.csv"
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india_search_output_file = f"india_data/daily_search_results/search_result_india_{today_date}.csv"
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india_search_error_file = f"india_data/daily_error_folder/search_error_india_{today_date}.csv"
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india_search_stats_file = f"india_data/daily_stats_folder/stats_india_search_{today_date}.txt"
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start_time = time.time()
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scraper = NaukriJobScraper(india_search_input_file, india_search_output_file, india_search_error_file)
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scraper.scrape()
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end_time = time.time()
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duration_hours = (end_time - start_time) / 3600
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print(f"Search program took {duration_hours:.2f} hours to run.")
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with open(india_search_stats_file, "a") as stat:
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stat.write(f"Search program took {duration_hours:.2f} hours to run. \n")
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folder_path = "india_data/daily_search_results/"
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search_pattern = "search_result_india_*.csv"
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last_file = find_second_latest_file(folder_path, search_pattern)
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fresh_output = f"india_data/daily_process_folder/new_jobs_on_{today_date}.csv"
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expired_output = f"india_data/daily_upload_folder/Compete_1_India_Archive_{today_date}.csv"
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common_output = f"india_data/daily_common_folder/common_data_on_{today_date}.csv"
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do_the_difference(india_search_output_file, last_file, 'jdURL',
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fresh_output, expired_output, common_output)
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india_detail_file = f"india_data/daily_upload_folder/Compete_1_India_Active_{today_date}.csv"
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india_detail_error_file = f"india_data/daily_error_folder/error_on_India_detail_{today_date}.txt"
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start_time = time.time()
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scraper = NaukriJobDetailScraper(fresh_output, india_detail_file, india_detail_error_file)
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scraper.scrape()
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end_time = time.time()
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duration_hours = (end_time - start_time) / 3600
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print(f"Jobdata program took {duration_hours:.2f} hours to run.")
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with open(f'india_data/daily_stats_folder/stats_file_of_{today_date}.txt', "a") as stat:
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stat.write(f"Jobdata program took {duration_hours:.2f} hours to run.\n")
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current_date = datetime.now()
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today_date = current_date.strftime('%d-%m-%Y')
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upload_file_to_bucket(expired_output, f"Compete_1_India_Archive_{today_date}.csv" , today_date)
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upload_file_to_bucket(india_detail_file, f"Compete_1_India_Active_{today_date}.csv" , today_date)
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def run_gulf_scraper(today_date):
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gulfSearch()
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folder_path = "gulf_data/daily_search_results/"
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search_pattern = "search_result_gulf_*.csv"
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last_file = find_second_latest_file(folder_path, search_pattern)
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# current_date = datetime.now()
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# today_date = current_date.strftime('%d-%m-%Y')
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fresh_output = f"gulf_data/daily_process_folder/new_jobs_on_{today_date}.csv"
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expired_output = f"gulf_data/daily_upload_folder/Compete_1_Gulf_Archive_{today_date}.csv"
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common_output = f"gulf_data/daily_common_folder/common_data_on_{today_date}.csv"
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do_the_difference(gulf_search_file, last_file, "jdURL", fresh_output, expired_output, common_output)
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upload_file_to_bucket(expired_output, f"Compete_1_Gulf_Archive_{today_date}.csv" ,today_date)
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start_time = time.time()
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gulf_detail_file = f"gulf_data/daily_upload_folder/Compete_1_Gulf_Active_{today_date}.csv"
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gulf_detail_error_file = f"india_data/daily_error_folder/error_on_India_detail_{today_date}.txt"
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scraper = NaukriGulfJobDetailScraper(fresh_output, gulf_detail_file, gulf_detail_error_file)
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scraper.scrape()
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end_time = time.time()
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duration_hours = (end_time - start_time) / 3600
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print(f"Jobdata program took {duration_hours:.2f} hours to run.")
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with open(f'gulf_data/daily_stats_folder/stats_file_of_{today_date}.txt', "a") as stat:
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stat.write(f"Jobdata program took {duration_hours:.2f} hours to run.\n")
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upload_file_to_bucket(gulf_detail_file, f"Compete_1_Gulf_Active_{today_date}.csv" , today_date)
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if __name__ == "__main__":
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aws_access_key_id = 'AKIAWWHGITBE7XFXWA7U'
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aws_secret_access_key = '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'
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current_date = datetime.now()
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today_date = current_date.strftime('%d-%m-%Y')
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bucket_name = 'compete-syndication'
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folder_name = f'naukri/{today_date}' # Replace with your desired folder name
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s3 = boto3.client('s3', aws_access_key_id=aws_access_key_id, aws_secret_access_key=aws_secret_access_key)
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folder_key = folder_name + '/' # Note the trailing slash
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s3.put_object(Bucket=bucket_name, Key=folder_key)
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if len(sys.argv) != 2:
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print("Usage: python common_task.py [gulf|india]")
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sys.exit(1)
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option = sys.argv[1].lower()
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if option == 'gulf':
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run_gulf_scraper(today_date)
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elif option == 'india':
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run_india_scraper(today_date)
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else:
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print("Invalid argument. Please use 'gulf' or 'india' as the argument.")
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