# Configure your S3 Access and Secret keys
aws configure set aws_access_key_id Your-Access-Key
aws configure set aws_secret_access_key Your-Secret-Key

# List
aws s3 ls s3://flatfiles/ --endpoint-url https://files.polygon.io

# Copy
aws s3 cp s3://flatfiles/us_stocks_sip/trades_v1/2024/03/2024-03-07.csv.gz . --endpoint-url https://files.polygon.io

# Set up your rclone configuration
rclone config create s3polygon s3 env_auth=false access_key_id=ACCESS_KEY_ID secret_access_key=SECRET_ACCESS_KEY endpoint=https://files.polygon.io

# List
rclone ls s3polygon:flatfiles

# Copy
rclone copy s3polygon:flatfiles/us_stocks_sip/trades_v1/2024/03/2024-03-07.csv.gz .

# Enter S3 Access and Secret keys in config file ~/.mc/config.json
mc alias set s3polygon https://files.polygon.io Your-Access-Key Your-Secret-Key

# List
mc ls s3polygon/flatfiles

# View
mc cat s3polygon/flatfiles/us_stocks_sip/trades_v1/2024/03/2024-03-07.csv.gz | gzcat | head -4

# Copy
mc cp s3polygon/flatfiles/us_stocks_sip/trades_v1/2024/03/2024-03-07.csv.gz .

import boto3
from botocore.config import Config

# Initialize a session using your credentials
session = boto3.Session(
   aws_access_key_id='Your-Access-Key',
   aws_secret_access_key='Your-Secret-Key',
)

# Create a client with your session and specify the endpoint
s3 = session.client(
   's3',
   endpoint_url='https://files.polygon.io',
   config=Config(signature_version='s3v4'),
)

# List Example
# Initialize a paginator for listing objects
paginator = s3.get_paginator('list_objects_v2')

# Choose the appropriate prefix depending on the data you need:
# - 'global_crypto' for global cryptocurrency data
# - 'global_forex' for global forex data
# - 'us_indices' for US indices data
# - 'us_options_opra' for US options (OPRA) data
# - 'us_stocks_sip' for US stocks (SIP) data
prefix = 'us_stocks_sip'  # Example: Change this prefix to match your data need

# List objects using the selected prefix
for page in paginator.paginate(Bucket='flatfiles', Prefix=prefix):
    for obj in page['Contents']:
        print(obj['Key'])

# Copy example
# Specify the bucket name
bucket_name = 'flatfiles'

# Specify the S3 object key name
object_key = 'us_stocks_sip/trades_v1/2024/03/2024-03-07.csv.gz'

# Specify the local file name and path to save the downloaded file
# This splits the object_key string by '/' and takes the last segment as the file name
local_file_name = object_key.split('/')[-1]

# This constructs the full local file path
local_file_path = './' + local_file_name

# Download the file
s3.download_file(bucket_name, object_key, local_file_path)