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python binding for using s5cmd to download and upload files to s3 efficiently
The S5CmdRunner
class provides a Python interface for interacting with s5cmd
, a command-line tool designed for efficient data transfer to and from Amazon S3.
For more information about s5cmd, please refer to the original s5cmd repository.
s5cmd
and download it if necessary.s5cmd
commands cp
, mv
, and run
.s5cmd
.To use S5CmdRunner
, ensure that Python 3.10 or higher is installed. The project itself can be installed from pip:
pip install s5cmdpy
or from source:
git clone https://github.com/trojblue/s5cmd-python
cd s5cmd-python
pip install -e .
Here are some examples of how to use the S5CmdRunner
class:
from s5cmdpy import S5CmdRunner
runner = S5CmdRunner()
# local_txt: `cp s3://dataset-artstation-uw2/artists/__andrey__/1841730##GZGgW.json .`
local_txt_path = "s5cmd_test.txt"
runner.run(local_txt_path)
# Useful in environments like SageMaker or for reproducibility;
# Extends `s5cmd run something.txt` to support command files stored in S3
txt_s3_uri = "s3://dataset-artstation-uw2/s5cmd_test.txt"
runner.run(txt_s3_uri)
Without any arguments, the progress bar created by run()
assumes that each line in the txt is for downloading a single file, therefore n lines in txt will result in n lines of console output.
For a more accurate progress bar, you can pass in the actual total number of files being downloaded, using the total
argument:
# the txt uses a wildcard to download multiple files, so 1 command downloads many files:
# `cp s3://bucket-external/dataset/dataset_lcm/moonbeam_150k_min512x768/*.webp ./webps/`
s5cmdpy.run("test_run_file.txt", total=10000)
# Input a series of S3 URIs to create the necessary commands.txt for `s5cmd run`,
# then execute `s5cmd run <commands.txt>`
s3_uris = [
's3://dataset-artstation-uw2/artists/__andrey__/1841730##GZGgW.json',
's3://dataset-artstation-uw2/artists/__andrey__/2249992##q5Y22.json'
]
destination_dir = '/home/ubuntu/datasets/s5cmd_test'
runner.download_from_s3_list(s3_uris, destination_dir)
cp
command also works with a file from internet:
# Download a file from internet and upload to S3
target_url = "https://huggingface.co/kiriyamaX/mld-caformer/resolve/main/ml_caformer_m36_dec-5-97527.onnx"
dst_s3_uri = "s3://dataset-artstation-uw2/_dev/"
runner.cp(target_url, dst_s3_uri)
Uses s5cmd to efficiently list files under s3. Has around twice the speed compared to boto3:
s3_uri = "s3://dataset-artstation-uw2/_dev/"
files_under_dir = runner.ls(s3_uri)
# returns Dict {"file_path": (size, date)}
Common commands can be called directly, without initializing a runner first:
s5cmdpy.download_from_s3_list(...)
s5cmdpy.mv(...)
s5cmdpy.cp(...)
s5cmdpy.run(...)
s5cmdpy.sync(...)
s5cmdpy.ls(...)
# runner is initialized automatically
import s5cmdpy
s5cmdpy.run("some_runfile.txt")
S5cmd itself is MIT licensed. This project is also MIT licensed.
FAQs
python binding for using s5cmd to download and upload files to s3 efficiently
We found that s5cmdpy demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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