Created
July 27, 2020 22:54
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Given a CSV file that's inside a tar.gz file on AWS S3, read it into a Pandas dataframe without downloading or extracting the entire tar file
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# checked against python 3.7.3, pandas 0.24.2, s3fs 0.4.2 | |
import tarfile | |
import io | |
import s3fs | |
import pandas as pd | |
tar_path = f"s3://my-bucket/debug.tar.gz" # path in s3 | |
metadata_path = "debug/metadata.csv" # path inside of the tar file | |
s3 = s3fs.S3FileSystem() | |
# this is in my experience, but it does work! | |
with s3.open(tar_path, 'rb') as debug_tar: | |
with tarfile.open(mode='r:gz', fileobj=debug_tar) as tar: | |
csv_contents = tar.extractfile(metadata_path).read() | |
df = pd.read_csv(io.BytesIO(csv_contents), encoding='utf8') |
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