remove labda version .1.

lambda_definition.1.py

@@ -1,57 +0,0 @@
-import urllib.parse
-import awswrangler as wr
-import pandas as pd
-
-
-def etl_function(event, context):
-    processed_zone_prefix = "processed-zone"
-
-    record = event["Records"][0]
-    bucket = record["s3"]["bucket"]["name"]
-    key = urllib.parse.unquote(record["s3"]["object"]["key"])
-    event_prefix = key.split('/')[1]
-    full_src_path = 's3://{bucket}/{key}'.format(bucket=bucket, key=key)
-
-    print(f'Processing key = {full_src_path}')
-    df = wr.s3.read_json(path=full_src_path, lines=True)
-
-    filename = key.split('/')[-1][-36:]
-    dest_prefix = f"s3://{bucket}/{processed_zone_prefix}/{event_prefix}"
-    print('Dest_pref: ')
-    print(f"s3://{bucket}/{processed_zone_prefix}/{event_prefix}")
-    print(dest_prefix.replace('raw','processed'))
-
-    df['transaction_date'] = pd.to_datetime(df['transaction_ts'], unit='s')
-    df['year'] = df['transaction_date'].dt.year
-    df['month'] = df['transaction_date'].dt.month
-    df['day'] = df['transaction_date'].dt.day
-    df['hour'] = df['transaction_date'].dt.hour
-
-    cols_to_return = ["transaction_date", "price", "amount", "dollar_amount", "type", "trans_id"]
-
-    new_keys = []
-    for [symbol, year, month, day, hour], data in df.groupby(['symbol', 'year', 'month', 'day', 'hour']):
-        partitions = f"symbol={symbol}/year={year}/month={month}/day={day}/hour={hour}"
-        full_key_name = '/'.join([dest_prefix, partitions, filename + '.parquet'])
-
-        print(f'Saving a new key = {full_key_name}')
-        new_keys.append(full_key_name)
-
-        wr.s3.to_parquet(
-            df=data[cols_to_return],
-            path=full_key_name,
-            compression='snappy'
-        )
-
-    return {
-        'key': key,
-        'statusCode': 200,
-        'new_keys': new_keys
-    }
-
-
-if __name__ == "__main__":
-    event = ""
-    context = ""
-
-    response = etl_function(event, context)