# pip install requests boto3

import boto3
import requests


def download_csv_from_github(url):
    response = requests.get(url)
    if response.status_code == 200:
        return response.content
    else:
        raise Exception(f"Failed to download file: HTTP status code {response.status_code}")

def upload_to_s3(bucket_name, file_content, s3_file_name):
    s3 = boto3.client('s3')  # aws configure stores the api credentials  boto integrates with aws cli
    s3.put_object(Bucket=bucket_name, Key=s3_file_name, Body=file_content)
    print(f"File uploaded successfully to {bucket_name}/{s3_file_name}")

# URL of the CSV file on GitHub (use the raw file URL)
github_csv_url = 'https://raw.githubusercontent.com/philipmatusiak/data/main/contacts.csv'

# S3 bucket details
bucket_name = 'drmdev'
from datetime import datetime
currentdate = datetime.now()
s3_file_name = 'contacts_' + str(currentdate) + '.csv'

try:

    file_content = download_csv_from_github(github_csv_url) # get the gfile from ext source
    # scan for vulneabilities with a comp library of choice
    upload_to_s3(bucket_name, file_content, s3_file_name) # put the file on s3
except Exception as e:
    print(f"An error occurred: {e}")

# Download the file form the S3 
    '''
    Loading data directly from an Amazon S3 bucket into an Oracle RDS database using 
    SQL*Loader involves a few additional steps, as SQL*Loader cannot directly access files in S3. 
    You'll first need to download the file from S3 to a location accessible to SQL*Loader 
    (like an EC2 instance or your local machine), and then use 
    SQL*Loader to load the data into Oracle RDS.
    '''

def download_file_from_s3(bucket_name, s3_file_name, local_file_path):
    s3 = boto3.client('s3')
    s3.download_file(bucket_name, s3_file_name, local_file_path)
    print(f"File downloaded successfully: {local_file_path}")

# S3 bucket details
# bucket_name = 'bucket_name_from_above'
# s3_file_name = 's3_file_name_from_above'

# create a folder in S3 called january IF it does not exist
# currentMonth = datetime.now().month
# newFolder = s3.md(currentMonth)

# Local path to save the file
# local_file_path = str(newFolder) + '/contacts.csv'
local_file_path = 'contacts.csv'

download_file_from_s3(bucket_name, s3_file_name, local_file_path)

# Prepare SQL*Loader command
import subprocess

def run_sqlldr(command):
    try:
        result = subprocess.run(command, shell=True, check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
        print("SQL*Loader executed successfully.")
        print("Output:", result.stdout.decode())
    except subprocess.CalledProcessError as e:
        print("Error occurred while executing SQL*Loader.")
        print("Error Code:", e.returncode)
        print("Error Message:", e.stderr.decode())

sqlldr_command = f"sqlldr userid=admin/password@dbserver1.cxoujydy3rce.us-east-1.rds.amazonaws.com control=contacts.ctl"

# Execute SQL*Loader command

# Run the command with error handling
run_sqlldr(sqlldr_command)