Skip to main content

for saving dictionaries using s3 with bz2 compression

Project description


save and load dictionary to s3 using bz compression

full docs here


pip install s3bz

How to use

Create a bucket and make sure that it has transfer acceleration enabled

create a buket

aws s3 mb s3://<bucketname>

put transfer acceleration

aws s3api put-bucket-accelerate-configuration --bucket <bucketname> --accelerate-configuration Status=Enabled

First, import the s3 module

import package

from importlib import reload
from s3bz.s3bz import S3

set up dummy data

BZ2 compression

save object using bz2 compression

result = = key, 
       objectToSave = sampleDict,
       bucket = bucket,
       pw = PW,
       accelerate = True)
print(('failed', 'success')[result])

load object with bz2 compression

result = S3.load(key = key,
       bucket = bucket,
       user = USER,
       pw = PW,
       accelerate = True)
{'ib_prcode': '23238', 'ib_brcode': '1015', 'ib_cf_qty': '703', 'new_ib_vs_stock_cv': '768'}

other compressions

Zl : zlib compression with json string encoding pklzl : zlib compression with pickle encoding

%time S3.saveZl(key,sampleDict,bucket)
%time S3.loadZl(key,bucket)
%time S3.savePklZl(key,sampleDict,bucket)
%time result =S3.loadPklZl(key,bucket)
CPU times: user 23.9 ms, sys: 559 µs, total: 24.5 ms
Wall time: 155 ms
CPU times: user 28.3 ms, sys: 3.04 ms, total: 31.4 ms
Wall time: 154 ms
CPU times: user 21.6 ms, sys: 228 µs, total: 21.9 ms
Wall time: 151 ms
CPU times: user 31.6 ms, sys: 0 ns, total: 31.6 ms
Wall time: 114 ms

Bring your own compressor and encoder

import gzip, json
compressor=lambda x: gzip.compress(x)
encoder=lambda x: json.dumps(x).encode()
decompressor=lambda x: gzip.decompress(x)
decoder=lambda x: json.loads(x.decode())

%time S3.generalSave(key, sampleDict, bucket = bucket, compressor=compressor, encoder=encoder )
%time result = S3.generalLoad(key, bucket , decompressor=decompressor, decoder=decoder)
assert result == sampleDict, 'not the same as sample dict'
CPU times: user 31 ms, sys: 0 ns, total: 31 ms
Wall time: 155 ms
CPU times: user 32.5 ms, sys: 51 µs, total: 32.5 ms
Wall time: 115 ms

check if an object exist

result = S3.exist('', bucket, user=USER, pw=PW, accelerate = True)
print(('doesnt exist', 'exist')[result])

presign download object

url = S3.presign(key=key,
              expiry = 1000,

download using signed link

from s3bz.s3bz import Requests
result = Requests.getContentFromUrl(url)

File operations

save without compression

inputPath = '/tmp/tmpFile.txt'
key = 'tmpFile'
downloadPath = '/tmp/downloadTmpFile.txt'
with open(inputPath , 'w')as f:
  f.write('hello world')
S3.saveFile(key =key ,path = inputPath,bucket = bucket)

load without compression

S3.loadFile(key= key , path = downloadPath, bucket = bucket)
with open(downloadPath, 'r') as f:
hello world


result = S3.deleteFile(key, bucket)
## test

save and load pandas dataframe

### please install in pandas, 
### this is not include in the requirements to minimize the size impact
import pandas as pd
df = pd.DataFrame({'test':[1,2,3,4,5],'test2':[2,3,4,5,6]})
<style scoped> .dataframe tbody tr th:only-of-type { vertical-align: middle; }
.dataframe tbody tr th {
    vertical-align: top;

.dataframe thead th {
    text-align: right;
Unnamed: 0 test test2
0 0 1 2
1 1 2 3
2 2 3 4
3 3 4 5
4 4 5 6

presign post with conditions

from s3bz.s3bz import ExtraArgs, S3
bucket = 'pybz-test'
key = 'test.dict'
fields = {**ExtraArgs.jpeg}
S3.presignUpload(bucket, key, fields=fields)
{'url': '',
 'fields': {'Content-Type': 'image/jpeg',
  'key': 'test.dict',
  'policy': 'eyJleHBpcmF0aW9uIjogIjIwMjEtMDMtMjVUMTA6MjQ6NTJaIiwgImNvbmRpdGlvbnMiOiBbeyJidWNrZXQiOiAicHliei10ZXN0In0sIHsia2V5IjogInRlc3QuZGljdCJ9XX0=',
  'signature': 'hwC8kIjmjNPU0KT3BE54/TUQ/7w='}}

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for s3bz, version 0.1.27
Filename, size File type Python version Upload date Hashes
Filename, size s3bz-0.1.27-py3-none-any.whl (12.8 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size s3bz-0.1.27.tar.gz (15.7 kB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page