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Bumping version to 1.9.4
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README.md

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> An [AWS Professional Service](https://aws.amazon.com/professional-services/) open source initiative | [email protected]
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[![Release](https://img.shields.io/badge/release-1.9.3-brightgreen.svg)](https://pypi.org/project/awswrangler/)
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[![Release](https://img.shields.io/badge/release-1.9.4-brightgreen.svg)](https://pypi.org/project/awswrangler/)
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[![Python Version](https://img.shields.io/badge/python-3.6%20%7C%203.7%20%7C%203.8-brightgreen.svg)](https://anaconda.org/conda-forge/awswrangler)
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[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
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[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
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Please [send a Pull Request](https://github.com/awslabs/aws-data-wrangler/edit/master/README.md) with your resource reference and @githubhandle.
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* [Optimize Python ETL by extending Pandas with AWS Data Wrangler](https://aws.amazon.com/blogs/big-data/optimize-python-etl-by-extending-pandas-with-aws-data-wrangler/)
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* [Reading Parquet Files With AWS Lambda](https://aprakash.wordpress.com/2020/04/14/reading-parquet-files-with-aws-lambda/)
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* [Transform AWS CloudTrail data using AWS Data Wrangler](https://aprakash.wordpress.com/2020/09/17/transform-aws-cloudtrail-data-using-aws-data-wrangler/)
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* [Optimize Python ETL by extending Pandas with AWS Data Wrangler](https://aws.amazon.com/blogs/big-data/optimize-python-etl-by-extending-pandas-with-aws-data-wrangler/) [[@igorborgest](https://github.com/igorborgest)]
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* [Reading Parquet Files With AWS Lambda](https://aprakash.wordpress.com/2020/04/14/reading-parquet-files-with-aws-lambda/) [[@anand086](https://github.com/anand086)]
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* [Transform AWS CloudTrail data using AWS Data Wrangler](https://aprakash.wordpress.com/2020/09/17/transform-aws-cloudtrail-data-using-aws-data-wrangler/) [[@anand086](https://github.com/anand086)]
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* [Getting started on AWS Data Wrangler and Athena](https://medium.com/@dheerajsharmainampudi/getting-started-on-aws-data-wrangler-and-athena-7b446c834076) [[@dheerajsharma21](https://github.com/dheerajsharma21)]
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* [Simplifying Pandas integration with AWS data related services](https://medium.com/@bv_subhash/aws-data-wrangler-simplifying-pandas-integration-with-aws-data-related-services-2b3325c12188) [[@bvsubhash](https://github.com/bvsubhash)]
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awswrangler/__metadata__.py

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__title__: str = "awswrangler"
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__description__: str = "Pandas on AWS."
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__version__: str = "1.9.3"
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__version__: str = "1.9.4"
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__license__: str = "Apache License 2.0"

awswrangler/s3/_wait.py

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import concurrent.futures
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import itertools
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import logging
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from typing import List, Optional, Tuple, Union
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from typing import List, Optional, Tuple
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import boto3
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def _wait_objects(
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waiter_name: str,
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paths: List[str],
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delay: Optional[Union[int, float]] = None,
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delay: Optional[float] = None,
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max_attempts: Optional[int] = None,
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use_threads: bool = True,
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boto3_session: Optional[boto3.Session] = None,
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def wait_objects_exist(
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paths: List[str],
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delay: Optional[Union[int, float]] = None,
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delay: Optional[float] = None,
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max_attempts: Optional[int] = None,
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use_threads: bool = True,
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boto3_session: Optional[boto3.Session] = None,
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def wait_objects_not_exist(
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paths: List[str],
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delay: Optional[Union[int, float]] = None,
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delay: Optional[float] = None,
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max_attempts: Optional[int] = None,
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use_threads: bool = True,
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boto3_session: Optional[boto3.Session] = None,

tests/test_metadata.py

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def test_metadata():
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assert wr.__version__ == "1.9.3"
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assert wr.__version__ == "1.9.4"
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assert wr.__title__ == "awswrangler"
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assert wr.__description__ == "Pandas on AWS."
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assert wr.__license__ == "Apache License 2.0"

tox.ini

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[testenv]
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passenv = AWS_PROFILE AWS_DEFAULT_REGION AWS_ACCESS_KEY_ID AWS_SECRET_ACCESS_KEY
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deps =
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pytest==6.0.1
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pytest==6.0.2
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pytest-xdist==2.1.0
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pytest-timeout==1.4.2
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moto==1.3.14
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moto==1.3.16
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s3fs==0.4.2
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commands =
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pytest -n 16 --timeout=300 tests

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