import os
import sys 

# https://docs.aws.amazon.com/lambda/latest/dg/current-supported-versions.html
workdir = os.getenv('LAMBDA_TASK_ROOT')
version = f'{sys.version_info[0]}.{sys.version_info[1]}'
additionals = [f'{workdir}/venv/lib64/python{version}/site-packages',
               f'{workdir}/venv/lib64/python{version}/lib-dynload',
               f'{workdir}/venv/lib64/python{version}/dist-packages',
               f'{workdir}/venv/lib/python{version}/dist-packages',
               f'{workdir}/venv/lib/python{version}/site-packages']

# We need to setup the Python search path in order to make use of the 
# virtual environment. These `additionals` can be found by inspecting
# `sys.path` from any Python in an active virtual environment.
sys.path = additionals + sys.path

import pandas_datareader as pdr
import boto3

def handle_one(event, context):

    symbol = event['symbol']

    # To obtain a free API key, go to https://www.quandl.com
    reader = pdr.quandl.QuandlReader(symbols=[f'WIKI/{symbol}'], 
                                     start=event['start'],
                                     end=event['end'],
                                     api_key=event['apikey'])

    df = reader.read()
    df.to_csv(f'/tmp/{symbol}.csv')

    s3 = boto3.resource('s3')
    bucket = s3.Bucket(event['bucket'])
    
    # This line requries premission to create a bucket.
    # If the bucket is already there, this line merely gets the bucket.
    bucket.create()
    bucket.wait_until_exists()

    with open(f'/tmp/{symbol}.csv', 'rb') as f:
        ret = bucket.put_object(Key=f'WIKI/{symbol}.csv',
                                Body=f.read())

    return {
        'statusCode': 200,
        'body': {
            'bucket': event['bucket'],
            'path': f'WIKI/{symbol}.csv'
        }
    }