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Baram

Python based AWS Framework which leverages boto3 and awswrangler.

Baram means "wind" in Korean which makes cloud move conveniently.

Features

  • TBD
  • Convenient S3 Usage(KMS setting, delete directory ...)
  • Athena Iceberg
  • Athena Performance Management(cache, ctas_approach control)
  • Glue Job Management

Quick Start

> pip install awswrangler

For Beginner

S3 Usage

# import S3Manager
from baram.s3_manager import S3Manager

sm = S3Manager("my_bucket_name")

# Upload local file to S3
sm.upload_file(local_file_path="local_file_path",
               s3_file_path="s3_file_path")

# Emphasize Directory Deletion
sm.download_dir(s3_dir_path="s3_directory_path",
                local_dir_path="local_directory_path")

# Copy S3 object
sm.copy_object(from_key="from_s3_key",
               to_key="to_s3_key")

For Data Scientist

S3 Usage

# Read csv from s3

# EDA

# Merging Datasets from S3(https://aws-sdk-pandas.readthedocs.io/en/stable/tutorials/013%20-%20Merging%20Datasets%20on%20S3.html)

# write dataframe to s3

Athena Usage

# Read rows from Athena

# EDA

# write dataframe to Another Athena Table without schema input.

# Batching(Good for restricted memory environments), https://aws-sdk-pandas.readthedocs.io/en/stable/tutorials/006%20-%20Amazon%20Athena.html

# big table dump to s3

For Data Engineer

Manage S3

# check_s3_object_exists

# count_csv_row_count

# rename_file

Read The Docs

Metadata

Release files for baram 0.5.0

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Table of built distributions (wheels) for baram 0.5.0
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Total release size: 58.3 kB

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